PrecisionTrack: A Platform for Automated Long-Term Social Behavior Analysis in Naturalized Environments

PrecisionTrack: A Platform for Automated Long-Term Social Behavior Analysis in Naturalized Environments | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article PrecisionTrack: A Platform for Automated Long-Term Social Behavior Analysis in Naturalized Environments Benoit Labonté, Vincent Coulombe, Mohammad Monfared, Khadijeh Aghel, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7721935/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Large-scale ethological behavioral studies can provide insights into the neuronal processes underlying complex and social behaviors, potentially opening new avenues for mental health research. However, these studies remain tedious and time-consuming, relying on manual annotation of predefined features. Despite recent advances, automatically monitoring complex behaviors in socially interacting animals remains challenging, limiting the scope and scale of experiments. Here, we present PrecisionTrack, an open-source framework designed to track and monitor large groups of interacting animals over prolonged periods. PrecisionTrack shows high spatiotemporal accuracy in crowded social settings, maintains consistent tracking performance over time and supports real-time, online responsiveness. We also introduce the Multi-animal Action Recognition Transformer (MART), which can be seamlessly integrated with PrecisionTrack to extract behavioral insights beyond spatiotemporal localization, including individual actions and social interactions. The entire system is open source and accessible. Overall, combined with a step-by-step guide, PrecisionTrack enables users to train, test and deploy their own social behavior monitoring systems, offering novel possibilities to study complex social behaviors in crowded naturalized environments. Biological sciences/Neuroscience/Social behaviour Biological sciences/Neuroscience/Social neuroscience Full Text Additional Declarations There is NO Competing Interest. Supplementary Files Otherspecies.mp4 Tracking example on other species MICE.mp4 Tracking example on mice PrecisionTrackMARTTailtags.mp4 Behavioral analysis example Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7721935","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":543718370,"identity":"627c56bb-22e4-4ee3-b678-4c85cf382fc8","order_by":0,"name":"Benoit 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