AUTHOR=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 TITLE=AlphaTracker: a multi-animal tracking and behavioral analysis tool JOURNAL=Frontiers in Behavioral Neuroscience VOLUME=17 YEAR=2023 URL=https://www.frontiersin.org/journals/behavioral-neuroscience/articles/10.3389/fnbeh.2023.1111908 DOI=10.3389/fnbeh.2023.1111908 ISSN=1662-5153 ABSTRACT=

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.