# Mobility state

Definition

A discrete (state event) variable with three possible states: Highly mobile, Mobile and Immobile, depending on where the changed pixels of the detected subject between current sample and previous sample (referred to as changed area) lay relative to two user-defined thresholds.

▪For the difference between Mobility and Movement, see Frequently asked questions about Mobility.

▪For the difference between Mobility and Activity, see Frequently asked questions about Activity

note Mobility state is not available if your experiment is set to:

▪Live Mouse Tracker.

▪Center-point, nose-point and tail-base detection, when you track two subjects per arena with Deep learning.

Calculation

The Mobility state variable is calculated for each sample according to the value of the running average Rotation relative to the thresholds:

▪Below the Immobile threshold, the state is Immobile.

▪Between the Immobile threshold and the Highly mobile threshold, the state is Mobile.

▪Above the Highly mobile threshold, the state is Highly mobile.

When the subject goes missing for more than three samples, the current Mobility state is ended and the remaining missing samples are ignored.

See also Frequently asked questions about Mobility

How to specify Mobility state

1.Open an Analysis profile and in the Dependent Variables panel, under Body, click the Add button next to Mobility state and click the Mobility State tab.

2.Enter the following:

▪Averaging Interval: The number of samples over which the running average mobility is based. The default value is 1, that is, the mobility measure is not smoothed before determining the Mobility state variable.

▪Highly mobile threshold: The percentage of change in body area above which the subject is considered to be Highly mobile.

▪Immobile threshold: The percentage of change in body area below which the subject is considered Immobile. You can enter a number with up to two decimals.

3.Under Calculate statistics for, select at least one of the three following options:

▪Highly mobile: Statistics are calculated for when the subject is considered Highly mobile.

▪Mobile: Statistics are calculated for when the subject is considered Mobile.

▪Immobile: Statistics are calculated for when the subject is considered Immobile.

4.Complete the procedure to add the variable. See Calculate statistics: procedure.

Notes

▪To find the optimal Highly mobile and Immobile threshold, run a few test trials and check in the Analysis Results and Scoring pane the values of Mobility when the animal shows such behavior. These values are calculated real-time during acquisition. See an example in Porsolt swim test: view the Mobility state variable.

▪Since Mobility is calculated on the detected subject, the gray-scale threshold values used in detection also have an influence on the mobility variable. If your detection settings are such that only part of the animal is detected, then only the mobility for that part is calculated.

▪In some cases the number of samples available for smoothing can be less than the averaging interval entered. For example, when there are missing samples or at the beginning of the track. In such cases EthoVision XT uses the samples available in the specified interval. For example, the value of Mobility for the first sample of the track is always calculated over one sample. See Averaging interval

▪You set the thresholds during acquisition, but you can override them when calculating statistics to produce new values for Mobility. To see what the original values of Mobility thresholds were (unless you have changed them while acquiring data), open the Acquisition module and click the button next to Mobility in the Analysis results and Scoring pane.

Applications

▪Mobility can be used to assess general activity, and changes in behaviors in specific paradigms. For example, in Porsolt swim tests (for example, Russig et al. 2003, Behav. Pharm. 14: 1-18) it allows to detect changes in behavior, for example from swimming to floating, more objectively than when observing directly.

▪You can also use Mobility to detect freezing behavior in which case you need to set a very low value of Immobile threshold. Mobility can also be used to quantify movement of zebra fish embryos within their eggs in a 24-well plate with back-lighting.

See also

▪Frequently asked questions about Mobility