Knowledge Base

Introduction

The Novel Object Recognition (NOR) test was first described by Ennaceur and Delacour (1988). Rats or mice are exposed first to two identical objects and then one of the objects is replaced by a new (novel) object. The time spent exploring each of the objects is measured. The test has become popular for assessing visual memory in rodents in general and to test the effects of amnesic drugs in particular.

The test is based on spontaneous behavior with no reinforcement such as food or shock. Non-amnesic animals will spend more time exploring the novel object than the familiar one. An absence of any difference in exploration time can be interpreted as a memory defect or, in case an amnesic drug is tested, a non-effective drug. This chapter describes how a NOR test can be conducted with EthoVision XT.

On the downloads section of the Noldus website my.noldus.com, you can find a number of sample experiments, including one that features a NOR test.

The Sample Experiment

To see how a Novel Object Recognition test is carried out in EthoVision XT, see also the sample experiment Novel Object Recognition test XT175 on the downloads section of the Noldus website (my.noldus.com). Download this file and save it on your computer. In EthoVision XT, choose File > Restore Backup and select the file. For more information, see the document Description of sample experiments of EthoVision XT.pdf.

References

• Ennaceur, A.; Delacour, J. (1988) A new one-trial test for neurobiological studies of memory in rats, 1: Behavioral data. Behavioral Brain Research, 31, 47-59.
• Benice, T.J.; Raber, J. (2008). Object recognition analysis in mice using nose-point digital video tracking. Journal of Neuroscience Methods, 168, 422-430.
• McDowell, K.A.; Hutchinson, A.N.; Wong-Goodrich, S.J.E.; Presby, M.M.; Su, D.; Rodriguiz, R.M.; Law, K.C.; Williams, C.L.; Wetsel, W.C.; West, A.E. (2010). Reduced cortical BDNF expression and aberrant memory in Carf knock-out mice. The Journal of Neuroscience, 30(22), 7453-7465.
• Siegel, J.A.; Park, B.S.; Raber, J. (2011). Long-term effects of neonatal methamphetamine exposure on cognitive function in adolescent mice. Behavioural Brain Research, 219, 159-164.
• Simmons, D.A.; Rex, C.S.; Palmer, L.; Pandyarajan, V.; Fedulov, V.; Gall, C.M.; Lynch, G. (2009). Up-regulating BDNF with an ampakine rescues synaptic plasticity and memory in Huntington's disease knock-in mice. PNAS, 106, 4906-4911.

For a complete list of publications, see the results of Google Scholar.

Physical Setup

The following suggestions are specifically to optimize video tracking. For general information, see the Physical Setup section in the chapter on The Open Field Test.

• The objects should contrast with the animal. If necessary, use a different setup for light and dark colored animals.
• Make sure that the objects do not move due to the activity of the animal.
• Either make sure the sides of the box are not reflective (for example, sand the box to make it matte), or exclude the sides from the arena. If your objects are close to the sides, you will need to track the animal when it is against the side.

EthoVision XT Settings

Create an experiment from a template (Ctrl+T). Choose Open field (round or square) as Arena template, and Novel object zones as Zone template.

For details, see Chapter 1 of this manual, or in EthoVision XT press F1 and see Setup an Experiment in the EthoVision XT Help.

Experiment Settings

Choose Setup > Experiment Settings.

Under Video Source and Tracked Features, make sure that the options selected correspond to your needs.

If you want to use the Deep Learning technique to track the subject's nose, under Body point detection technique choose Deep learning. Note that in order to use this technique there are additional requirements. The PC must have a powerful graphics card which supports additional software (CUDA). See Deep learning: Requirements and Limitations in the EthoVision XT Help.

Manual Scoring Settings

These settings enable you to record behaviors manually using keystrokes. This is useful for example to record exploratory behaviors like sniffing.

Choose Setup > Manual Scoring Settings.

If you created the experiment from the template with novel object zones, the Manual Scoring Settings already includes one behavior, Sniffing object. This is defined as "start-stop", which means that you press a key (default: q) to score the start of sniffing, and then you press the same key once again to score the end of sniffing.

For more information, see Manual Scoring Settings in the EthoVision XT Help.

With the Rat or Mouse Behavior Recognition add-on, you can have EthoVision XT detect sniffing and other behaviors without the need to score them manually.

Arena Settings

Choose Setup > Arena Settings > Open Arena Settings 1.

To set up your Arena Settings:

1. Click the Grab Background Image button to grab an image of the empty enclosure from the camera image.
2. Click 1. Draw Scale to calibrate your arena (for details, see the EthoVision XT Help). Draw the double-arrow so that it points to two opposite walls of the open field, at the level where the animal moves (not at the top of the walls). When done, enter the distance in real world units between the tips of the arrow.
3. Click 2. Select Shape and Draw Arena. Check that the arena covers the whole area in which you want to track the animal. Remember to include enough of the walls so that the animal is still tracked when it rears, but exclude any bright reflective rims that might interfere with tracking. Make sure the label stays inside the arena. If the arena is not yet defined and you want to divide it into equal zones, choose the tool that applies depending on the shape of your open field and draw the outline of the arena.
4. If you used the Zone template Novel object zones, click 3. Select Shape and Draw Zones. Click the layer Zone group Objects. Check that the 'object 1' zone and 'object 1 boundary' zone cover the object. If the predefined zones do not have the correct shape, delete the zones and draw new ones.
5. If necessary, draw additional zone groups and zones.

Additional Zones

• Zone group Floor and Wall. Check that the 'Floor' zone covers the whole floor area of the open field.
• Zone group Halves. Check that the 'West' and 'East' zones divide the 'Floor' zone into two equal halves. Make sure that the vertical line crosses the entire arena.

Trial Control Settings

In the Trial Control Settings you can define conditions for the start and stop of the track.

Choose Setup > Trial Control Settings. The template contains the following profiles:

• Default. When you use this profile, tracking starts automatically two seconds after the animal has been placed in the arena. Tracking stops when you click the Stop trial button.
• Track duration 10 min. When you use this profile, tracking starts automatically two seconds after the animal has been placed in the arena. Tracking stops automatically after 10 minutes.

Stopping Tracking When Exploration Exceeds a Specified Time

You can also stop tracking when the subject has spent some time around an object. For example, when the protocol specifies that in pre-test trials the animal must explore an object for at least 30 seconds.

Make a new Trial Control Settings profile and, immediately before the Stop track box, insert a Condition box based on the variable In zone, or another variable, or a combination of variables using Multi condition. In the Condition settings, specify that Cumulative duration in the boundary zone for that object must be greater than N seconds for the nose point.

If you use Multi condition, you can define "exploration" as a combination of variables. For example: In Zone for the nose point in the "object zone" is true + Head directed to Zone "object" is true + Velocity lower than 5 cm/s is true. The trial stops only when the cumulative time that all three criteria are met reaches the specified value.

Stopping Tracking Automatically When No Exploration Occurs

To stop tracking automatically even when the animal does not explore the object, add another condition in parallel with the first one that specifies stopping tracking after some time (for example, 10 minutes), and combine the two conditions with an Operator box of type "ANY".

Detection Settings

Choose Setup > Detection Settings > Detection Settings 1.

If detection of the subject is not optimal after using the Automated setup function, do the following:

1. Check that the sample rate is set to at least 25 samples per second when tracking the nose and tail.
2. Check that either Dynamic subtraction or Differencing is selected as the detection method. Differencing is the preferred option if you work with hooded animals.
3. When using Dynamic subtraction, move the slider to define the animal's contrast. The animal must be fully detected in all parts of the arena and the noise must be minimal. Specify the Current frame weight. A low value (for instance, 1 to 10) usually works well. A novel object test normally has a duration of a few minutes in which the background does not change much. When using Differencing, set the Sensitivity slider. The slider determines what difference in contrast from the background is seen as the animal.
4. When detection is still not satisfactory, select Rodents / For occlusions as the tracking method and repeat step 2 above.

If you want to use the Deep Learning technique to track the subject's nose, note that there are additional requirements and limitations. Among other things, you need a powerful graphics card. See Deep learning: Requirements and Limitations in the EthoVision XT Help.

Trial List

Choose Setup > Trial List.

Defining Independent Variables

Enter your independent variables such as:

• Subject ID with the ID of your animals as predefined values.
• Phase with Acclimation, T1, and T2 as predefined values, where:
  • Acclimation marks trials where the animal is free to explore the arena with no objects present.
  • T1 marks trials where the animal is presented with a pair of identical objects.
  • T2 marks trials where one of the familiar objects is replaced with a new novel object.
• Treatment with Treated and Control as predefined values.

If you want, you can predefine all your trials here, or you can enter the independent variable values as you carry out the trials. You can also prepare the trials in Excel, randomize them, and then paste the values into your Trial List.

Furthermore, you can define a list of trials for batch acquisition. See Batch Data Acquisition in the EthoVision XT Help.

Acquiring Data

Protocol

A typical NOR test consists of three phases:

• Acclimation. The animal is placed in an empty arena for 10 minutes to habituate to the environment. Tracking in this phase is optional. After 10 minutes, the animal is taken out of the arena and put back in its home cage.
• T1. After 15 minutes in the home cage, the animal is put back in the arena in which two identical objects have been placed. The animal is placed at a position midway between the objects with its nose pointing towards the wall. The animal is tracked for 3 minutes and is then taken out of the arena and put back in its home cage. Define a Trial Control Settings profile for this phase, then assign this profile to the trials of type T1.
• T2. One of the objects in the open field is replaced with a novel object (sometimes the other object is also replaced with an identical one) and the animal is placed in the arena again. Tracking is done for 3 minutes. Define a Trial Control Settings profile for this phase, then assign this profile to the trials of type T2.

Score Behaviors Manually

To score sniffing and other behaviors defined under Manual Scoring Settings, open the Manual Scoring tab on the Acquisition screen. There you will find the key codes and the buttons for the behaviors.

To score an instance of the behavior or its end, either press the key or click the corresponding button on the screen.

• If you are tracking from video, make sure you deselect DDS in the Playback Control window.
• You can also score behaviors after tracking. See Acquire Data > Score behaviors manually in the EthoVision XT Help.

Data Analysis

Data Preparation

Track Editing

Choose Acquisition > Edit Tracks.

You can fix tracking errors and swap back nose-points and tail-points that have been swapped during tracking. Normally you will not need to edit your data.

Track Smoothing

Choose Acquisition > Track Smoothing Profile > open MDM Filter 2 mm.

In this profile, the Minimal Distance Moved filter is used (option set to Direct, with a threshold of 2 mm). When the animal sits still, the body points may still move slightly due to system noise. This results in an overestimation of, for example, the total distance moved. With the minimal distance moved filter, you measure the total distance moved over the time periods in which the animal was really walking. Adjust the threshold if necessary, based on your setup and sample rate.

Review Video and Behaviors

If you have scored behaviors manually, you can review the video and if necessary edit the data. Choose Acquisition > Score behaviors manually. For details, see Score behaviors manually in the EthoVision XT Help.

Selecting Data

Choose Analysis > Data Profile.

You can select (Filter) your tracks according to your independent variable values (for example, Treated animals only) and also select parts of tracks (Nesting). You can create a data profile to compare Novel Object and Familiar Object trials using Filters, creating groups of tracks to obtain group statistics for each group.

Analysis Profiles

The template experiment contains four analysis profiles:

• Touching objects. This analysis profile contains an In zone variable Nose touching objects to calculate the frequency, duration, and latency of when the nose-point of the animal touches the objects. The variable Distance to objects is used to calculate the mean and standard error of the animal's nose-point distance to the objects. The manually-scored behavior Sniffing object calculates the frequency and duration, with standard errors, of the instances when Sniffing object was scored during the trials.
• In halves. In this analysis profile, the In zone variable In Halves is used to calculate the frequency, duration, and latency of time spent in each half of the arena.

Source: EthoVision XT 17.5 Application Manual - The Novel Object Recognition Test