Knowledge Base

Activity Analysis

Aim

Activity measures temporal changes in the video image that may have biological meaning. For example, a sudden drop in the levels of activity in an open field may indicate freezing in a fear conditioning experiment. This can be detected automatically by EthoVision XT, based on the amount of temporal change in the gray scale value of each pixel in the arena. Pixels with temporal change in their gray scale value indicate subject movement; no pixel change indicates the subject is completely immobile.

Additional examples:

• Detect immobility in a Porsolt swim test. When the subject stays still in the cylinder, activity is reduced to a minimal level.
• Detect activity of insects flying around a target object. The more insects are flying around the target, the higher the level of activity.

Procedure

1. Choose Setup > Experiment Settings, and under Analysis Options select Activity Analysis.
2. In the Arena Settings, define the arena.
3. In the Detection Settings, define the level of significant activity.
4. Run your trials. During acquisition, you can monitor the level of activity and, if necessary, use this information to adjust the activity settings to better detect the behavior you are interested in.
5. To analyze activity, in the Analysis Profile choose the variables Activity and Activity State.

Notes

• Activity analysis is only available when in the Experiment Settings, under Subjects, you select 1 Subject per arena.

See Also

• Activity and Activity State as Dependent Variables
• Fear Conditioning: View Activity State

Behavior Recognition

Aim

To activate the functions Rat Behavior Recognition and Mouse Behavior Recognition.

Prerequisites

• You have the Rat/Mouse Behavior Recognition module.

Procedure

1. Choose Setup > Experiment Settings.
2. Under Subjects, choose 1.
3. Under Tracked Features, select Center-point, nose-point and tail-base detection.
4. Under Body Point Detection Technique, select Contour-based.
5. Under Analysis Options, select Behavior Recognition and choose the function Rat Behavior Recognition or Mouse Behavior Recognition.
6. Select the options that apply (see below).

Options

• Feeder. Select this if you want to analyze eating behavior at the feeder. In the Arena Settings, you must draw a zone over the feeder.
• Drinking Bottle. Select this if you want to detect drinking. In the Arena Settings, you must draw a point over the tip of each drinking bottle spout.
• Arena Walls. To have EthoVision XT discriminate between rearing to the walls and rearing unsupported. In the Arena Settings, you must draw a zone over the walls.
• Settings (for Mouse Behavior Recognition). When you select Mouse Behavior Recognition, click the Settings button and select the options that apply to your setup:
  • Select Bedding Present if the cage includes bedding material and you want to detect digging behavior.
  • Select Food Available if there is food for the mice and you want to detect eating behavior.

Next Steps

1. In the Arena Settings, draw the zones important for behavior recognition.
2. In the Detection Settings, set a sample rate between 25 and 31 samples per second, and specify the detection settings for Behavior Recognition.
3. Run your trials.

See Also

• Behavior Recognition: Requirements
• Choose Help > Video Tutorial and watch the tutorial about Behavior Recognition.

Trial Control Hardware

Aim

To set the EthoVision XT experiment to control hardware devices.

Prerequisites

You must have one of the following interface devices:

• The USB-IO box.
• The Mini USB-IO box.
• The DanioVision DVOC-00xx observation chamber.

Procedure

1. Connect the interface device (USB-IO box, Mini USB-IO box, or DanioVision Observation Chamber) to the EthoVision XT computer. For details and connection schemes, see the EthoVision XT 19 - Trial and Hardware Control - Reference Manual.
2. Select Trial Control Hardware and click Settings.