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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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266280/ https://www.ncbi.nlm.nih.gov/pubmed/37324523 http://dx.doi.org/10.3389/fnbeh.2023.1111908 |
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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 |
author_facet | 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 |
author_sort | Chen, Zexin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10266280 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102662802023-06-15 AlphaTracker: a multi-animal tracking and behavioral analysis tool 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 Front Behav Neurosci Behavioral Neuroscience 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. Frontiers Media S.A. 2023-05-30 /pmc/articles/PMC10266280/ /pubmed/37324523 http://dx.doi.org/10.3389/fnbeh.2023.1111908 Text en Copyright © 2023 Chen, Zhang, Fang, Zhang, Bal, Zhou, Rock, Padilla-Coreano, Keyes, Zhu, Li, Komiyama, Tye and Lu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Behavioral Neuroscience 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 AlphaTracker: a multi-animal tracking and behavioral analysis tool |
title | AlphaTracker: a multi-animal tracking and behavioral analysis tool |
title_full | AlphaTracker: a multi-animal tracking and behavioral analysis tool |
title_fullStr | AlphaTracker: a multi-animal tracking and behavioral analysis tool |
title_full_unstemmed | AlphaTracker: a multi-animal tracking and behavioral analysis tool |
title_short | AlphaTracker: a multi-animal tracking and behavioral analysis tool |
title_sort | alphatracker: a multi-animal tracking and behavioral analysis tool |
topic | Behavioral Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266280/ https://www.ncbi.nlm.nih.gov/pubmed/37324523 http://dx.doi.org/10.3389/fnbeh.2023.1111908 |
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