Knowledge Base

Data Preparation

Data Editing

Choose Acquisition > Edit Tracks. You can fix tracking errors and swap back nose-points and tail-points that have been swapped in tracking. Normally you will not need to edit your data.

Smoothing Data

Choose Acquisition > Track Smoothing Profile and open MDM Filter 0.2 cm. In this profile, the Minimal Distance Moved filter is used with a value of 2 mm and option Direct.

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 Acquire Data > Score behaviors manually in the EthoVision XT Help.

Selecting Data

Choose Analysis > Data Profile. You can select your tracks according to your independent variable values (for example, Treated animals vs. Controls) and also select parts of tracks (data nesting). The Data Profile Treated vs. Control from the template compares 'Treated animals' and 'Control animals' trials. This way you create groups of tracks to obtain group statistics for each group.

For more information and to create your own data selection, see the EthoVision XT Help.

Trial Statistics will be displayed per trial, and Group Statistics will be displayed per group of trials, according to the treatment level assigned to them.

If you have more treatment groups (e.g. Sham), to create more treatment groups click the Common Elements - Result button in the Components pane, and place the new box somewhere on your screen. Create a new branch by connecting the first (Start) box to this new box. Click the button next to Treatment and select the new treatment level. Insert the box in the new branch.

Visualizing Data

You can visualize your tracks in three ways:

• Plot Tracks. You can view your tracks on a still image of the background. Tracks can be shown in different colors according to the values of independent variables (for example, blue for animals treated with saline and red for drug-treated animals). Sample points can be shown in different colors according to the values of dependent variables, for example red when the animal was moving fast.
• Plot Integrated Data. You can look at a track with the video file in the background. When you plot integrated data you can also view Time Event plots of your independent variables. Just like with plotting tracks, you can show tracks or sample points in different colors.
• Heatmaps. You can make heatmaps of the location of your animals during the test.

Analysis Profiles

The template experiment contains three analysis profiles:

• Time in Arms – This analysis profile contains two In Zone variables:
  • In Closed Arms to calculate the frequency and duration of when the animal was in the closed arms.
  • In Open Arms to calculate the frequency, duration and latency of when the animal was in the open arms. Here, latency (the time to the first visit in any open arm) is used as an indication of anxiety.

  For all variables, the animal is considered to be in a zone when all its body points are found in the zone simultaneously.

• Behaviors – In this analysis profile, four variables have been defined:
  • Head Dipping and Rearing provide statistics of the behaviors manually scored.
  • Body Elongation is used to quantify the time that the animal shows stretching behavior.
  • Nose in Head Dip Area is an In Zone variable to calculate the frequency and duration of when the nose point of the animal was in the head dip areas.

  The last two variables are present when you set the experiment to track the three body points or you select the zone template with the head dip area.

• Velocity and Distance – With the variables Distance Moved and Velocity, the total distance moved and the mean velocity and the group means and their standard errors are calculated. Movement is based on a velocity threshold, and quantifies the time that the animal has moved significantly.

For more information, see the EthoVision XT Help.

False Positives in Arm Entry Statistics

Sometimes the center point of the animal fluctuates around the border line between the center and the arm zones. This may be caused by jitter or exploration behavior, and results in false positives when calculating the number of zone entries.

To prevent this from happening, set the Zone Exit Threshold for the In Zone variable.

To Set a Zone Exit Threshold

1. In the Analysis profile, add the In Zone variable. Specify the arm zones you are interested in, and the body points that define a zone entry (when tracking the center, nose and tail base points).
2. Under Threshold, enter a value for Zone Exit Threshold. This is the distance from the border of the arm zone that the animal must be in order to be considered outside the zone. Use the Zone Exit Threshold to filter out small movements of the body points that result from jitter or exploration behavior.
3. Visualize the data (Analysis > Results > Plot Integrated Data).

Example

In the following example, slight movements of the mouse's center point result in multiple open arm entries. In the Analysis profile, In Zone is set with Zone Exit Threshold = 0 cm.

• Left: Mouse enters the open zone.
• Middle: The center point is detected out of the zone.
• Right: The center point is inside the zone; a second arm entry is scored.

To remove false positives of zone entries, in the Analysis profile, In Zone is set with Zone Exit Threshold = 2 cm. This means that when the center point is outside the zone by less than 2 cm from the border, it is still considered in the zone.

Result: This time, one arm entry is scored.

For more information on the Zone Exit Threshold, see In Zone in the EthoVision XT Help.

Source: EthoVision XT 18 - Application Manual, Noldus Information Technology