期刊
SCIENTIFIC REPORTS
卷 9, 期 -, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41598-019-56408-9
关键词
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资金
- McKnight Memory and Cognitive Disorders Award
- Klingenstein-Simons Fellowship
- Brain Research Foundation Award
- NARSAD Young Investigator Award
- Friedman Scholar Award
- Botanical Center Pilot Award from the NCCIH [P50 AT008661-01]
- Botanical Center Pilot Award from ODS [P50 AT008661-01]
- NIMH [1DP2MH122399-01]
- CURE Taking Flight Award
- American Epilepsy Society Junior Investigator Award
- NIDA [5T32DA007135, 5T32AG049688-02]
- [1 R01 MH120162-01A1]
Tracking animal behavior by video is one of the most common tasks in the life sciences. Although commercial software exists for executing this task, they often present enormous cost to the researcher and can entail purchasing hardware that is expensive and lacks adaptability. Additionally, the underlying code is often proprietary. Alternatively, available open-source options frequently require model training and can be challenging for those inexperienced with programming. Here we present an open-source and platform independent set of behavior analysis pipelines using interactive Python that researchers with no prior programming experience can use. Two modules are described. One module can be used for the positional analysis of an individual animal, amenable to a wide range of behavioral tasks. A second module is described for the analysis of freezing behavior. For both modules, a range of interactive plots and visualizations are available to confirm that chosen parameters produce the anticipated results. Moreover, batch processing tools for the fast analysis of multiple videos is provided, and frame-by-frame output makes alignment with biological recording data simple. Lastly, options for cropping video frames to mitigate the influence of fiberoptic/electrophysiology cables, analyzing specified portions of time, and defining regions of interest, are readily implemented.
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