Knowledge Base

Undo Track Edits

Aim

To revert to previously saved data after you have changed the data further and you do not want to keep the last edits.

Note: The procedure below is also valid when you edit data in the Manual Scoring screen. There you also find the Save and Undo buttons.

Prerequisites

• In the Track Editor, or in the Manual Scoring screen, you have done edits after saving the data at least one time.

Procedure

1. Click the Undo button on the toolbar. A message appears, asking you whether you want to lose the changes since the last save.
2. If you click Yes, the original track plot is restored. If you click No, you return to the main screen without losing the changes.

Notes

• To return to the original data, click Undo All. However, keep in mind that you lose all changes.
• If you edit data in one trial and then select another trial in the trial selection list on the toolbar, the changes you have made to that trial are saved automatically, including those you made after saving.
• If you open another EthoVision XT screen, for example to calculate statistics, or close the experiment after making changes to the track, those changes are saved and retained when you switch back to the Track Editor screen. However, the saved copy (restore point) is always deleted when closing the experiment. Therefore, you cannot revert to the saved copy.

Consider the following sequence of actions:

1. Edit data, then click Save.
2. Make a second run of changes, then close the experiment.
3. Re-open the experiment and choose Acquisition > Edit Tracks.

The screen also shows the second set of changes made, but you cannot revert to the saved copy (restore point).

Smooth the Tracks

Why Smooth the Tracks?

In any tracking system, there are three sources of noise that potentially affect the values of dependent variables such as Distance Moved or Velocity:

• System noise. The noisy output of tracking systems means that when you track an object that does not move, the position of the object irregularly oscillates between two or more locations. This way the track may show continuous movement of the object that corresponds to a real-world distance of, for example, 1 cm, while in fact the animal is sitting still. As a result, the data show that the immobile object traveled quite a distance.
• Outliers resulting from tracking noise. Occasionally the tracking system generates a single outlier which obviously affects a dependent variable such as Velocity.
• Small movements of the animal ('body wobble'). When you track a moving animal using a high sample rate, sideways movements from the wobbling of the animal's body are also tracked. This results in an overestimation of, for instance, the total distance moved.

Smoothing Methods

Smoothing (Lowess)

Use this method to eliminate small movements, such as body wobbling during locomotion, that might affect dependent variables such as total distance moved.

Minimal Distance Moved

Use Minimal Distance Moved when the animal sits still, yet the body points move slightly due to system noise or breathing.

Maximal Distance Moved

Use Maximal Distance Moved to remove outliers due to erratic detection, for example in a water maze test when some water reflection is detected as the subject, or in DanioVision experiments when the subject does not move and EthoVision XT detects the margins of the well as the subject.

Track Smoothing During Acquisition

The track smoothing methods listed above affect the tracks after acquisition. In some cases you may already want to smooth the track during acquisition. This may especially be the case if you use Trial and Hardware Control. As an example, if the center-point of an animal is detected in a zone, you want the pellet dispenser to drop a pellet. If the detected center-point is moving rapidly because of noise, this may result in a number of consecutive pellets being dropped, every time the center-point crosses the border of the zone. Track smoothing does not solve this problem. Instead, use Track Noise Reduction in the detection settings to smooth the tracks during data acquisition.