Abstract

The complexity of exploratory behavior creates a need for a visualization and analysis tool that will highlight regularities and help generating new hypotheses about the structure of this behavior. The hypotheses can then be formulated as algorithms that capture the patterns and quantify them. SEE is a Mathematica based software developed by us for the exploration of exploratory behavior. The raw data for SEE are a time series of the animal ‘s coordinates in space sampled at a rate that allows a meaningful computation of speeds. SEE permits: (i) a visualization of the path of the animal and a computation of the dynamics of activity; (ii) a decomposition of the path into several modes of motion (1st gear, 2nd gear, etc.) and a computation of the typical maximal speeds, the spatial spread, and the proportion of each of these modes; and(iii) a visualization of the location in the environment of stopping episodes, along with their dwell time. These visualizations highlight the presence of preferred places, including the animal's so-called home base, and permits a computation of the spatio-temporal diversity in the location of stopping episodes. The software also: (i) decomposes the animal's path into round trips from the home base, called ‘excursions’, and computes the number of stops per excursion; (ii) generates a visualization of the phase space (path+speed, traced in a three-dimensional graph) of any progression segment or list of such segments; and (iii) produces a visualization of the way places in the animal's operational world are connected to each other. SEE also permits the definition and computation of behavioral endpoints across any section of any database of raw data. The range of applicability of SEE to various experimental setups, tracking procedures, species, and preparations is addressed in the discussion.

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