AlphaTracker: a multi-animal tracking and behavioral analysis tool

Computer vision has emerged as a powerful tool to elevate behavioral research. This protocol describes a computer vision machine learning pipeline called AlphaTracker, which has minimal hardware requirements and produces reliable tracking of multiple unmarked animals, as well as behavioral clusterin...

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Bibliographic Details
Published in:	Frontiers in behavioral neuroscience Vol. 17; p. 1111908
Main Authors:	Chen, Zexin, Zhang, Ruihan, Fang, Hao-Shu, Zhang, Yu E, Bal, Aneesh, Zhou, Haowen, Rock, Rachel R, Padilla-Coreano, Nancy, Keyes, Laurel R, Zhu, Haoyi, Li, Yong-Lu, Komiyama, Takaki, Tye, Kay M, Lu, Cewu
Format:	Journal Article
Language:	English
Published:	Switzerland Frontiers Media S.A 30-05-2023
Subjects:	animal behavior animal tracking behavioral clustering Behavioral Neuroscience computer vision neuroscience animal behavior behavioral clustering neuroscience animal tracking computer vision
Online Access:	Get full text
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Summary:	Computer vision has emerged as a powerful tool to elevate behavioral research. This protocol describes a computer vision machine learning pipeline called AlphaTracker, which has minimal hardware requirements and produces reliable tracking of multiple unmarked animals, as well as behavioral clustering. AlphaTracker pairs a top-down pose-estimation software combined with unsupervised clustering to facilitate behavioral motif discovery that will accelerate behavioral research. All steps of the protocol are provided as open-source software with graphic user interfaces or implementable with command-line prompts. Users with a graphical processing unit (GPU) can model and analyze animal behaviors of interest in less than a day. AlphaTracker greatly facilitates the analysis of the mechanism of individual/social behavior and group dynamics.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Reviewed by: Eric Horstick, West Virginia University, United States; Moriel Zelikowsky, The University of Utah, United States; Keegan Dohm, University of Utah, United States, in collaboration with reviewer MZ Edited by: Daniela Schulz, Boğaziçi University, Türkiye These authors have contributed equally to this work and share first authorship This article was submitted to Individual and Social Behaviors, a section of the journal Frontiers in Behavioral Neuroscience
ISSN:	1662-5153 1662-5153
DOI:	10.3389/fnbeh.2023.1111908