Adrien Jouary, Alexandre Laborde, Pedro T. Silva, J. Miguel Mata, Joao C. Marques, Elena Collins, Randall T. Peterson, Christian K. Machens, Michael B. Orger
{"title":"Megabouts: a flexible pipeline for zebrafish locomotion analysis","authors":"Adrien Jouary, Alexandre Laborde, Pedro T. Silva, J. Miguel Mata, Joao C. Marques, Elena Collins, Randall T. Peterson, Christian K. Machens, Michael B. Orger","doi":"10.1101/2024.09.14.613078","DOIUrl":null,"url":null,"abstract":"Accurate quantification of animal behavior is crucial for advancing neuroscience and for defining reliable physiological markers. We introduce Megabouts (megabouts.ai), a software package standardizing zebrafish larvae locomotion analysis across experimental setups. Its flexibility, achieved with a Transformer neural network, allows the classification of actions regardless of tracking methods or frame rates. We demonstrate Megabouts' ability to quantify sensorimotor transformations and enhance sensitivity to drug-induced phenotypes through high-throughput, high-resolution behavioral analysis.","PeriodicalId":501210,"journal":{"name":"bioRxiv - Animal Behavior and Cognition","volume":"5 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv - Animal Behavior and Cognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.09.14.613078","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Accurate quantification of animal behavior is crucial for advancing neuroscience and for defining reliable physiological markers. We introduce Megabouts (megabouts.ai), a software package standardizing zebrafish larvae locomotion analysis across experimental setups. Its flexibility, achieved with a Transformer neural network, allows the classification of actions regardless of tracking methods or frame rates. We demonstrate Megabouts' ability to quantify sensorimotor transformations and enhance sensitivity to drug-induced phenotypes through high-throughput, high-resolution behavioral analysis.