Frontiers in Behavioral Neuroscience (May 2023)

AlphaTracker: a multi-animal tracking and behavioral analysis tool

  • Zexin Chen,
  • Ruihan Zhang,
  • Ruihan Zhang,
  • Hao-Shu Fang,
  • Yu E. Zhang,
  • Yu E. Zhang,
  • Aneesh Bal,
  • Aneesh Bal,
  • Haowen Zhou,
  • Rachel R. Rock,
  • Nancy Padilla-Coreano,
  • Nancy Padilla-Coreano,
  • Laurel R. Keyes,
  • Laurel R. Keyes,
  • Haoyi Zhu,
  • Yong-Lu Li,
  • Takaki Komiyama,
  • Kay M. Tye,
  • Kay M. Tye,
  • Cewu Lu,
  • Cewu Lu

DOI
https://doi.org/10.3389/fnbeh.2023.1111908
Journal volume & issue
Vol. 17

Abstract

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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.

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