We applied the software to an analysis of the effects of ethanol on thigmotaxis (wall-hugging) behavior on adult zebrafish, and found that acute ethanol treatment decreased thigmotaxis behaviors without affecting overall amounts of motion. These tests highlight the capacity of our software for long-term data acquisition, parallel analysis of multiple animals, and application to animal species of different sizes and movement patterns. We validated this software through four tests on a variety of animal species, including larval and adult zebrafish ( Danio rerio), Siberian dwarf hamsters ( Phodopus sungorus), and wild birds. Here, we present a new video-tracking system built on Python-based software that is free, open source, and cross-platform, and that can analyze video input from widely available video capture devices such as smartphone cameras and webcams. Automated tracking of animal movement is less labor-intensive and bias-prone than direct observation, and allows for simultaneous analysis of multiple animals, high spatial and temporal resolution, and data collection over extended periods of time. Measurements of animal locomotion enable the quantification of these differences. Differences in nervous system function can result in differences in behavioral output.
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