A Review of the Evolution of Rodent Tracking and Behaviour Analysis

A Review of the Evolution of Rodent Tracking and Behaviour Analysis | 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 Research Article A Review of the Evolution of Rodent Tracking and Behaviour Analysis Raul Alfredo de Sousa Silva, Rabah Iguernaissi, Djamal Merad, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8904710/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Advances in computational power, miniaturisation, and cost reduction of electronic devices have profoundly transformed behavioural neuroscience, enabling automated, high-throughput data acquisition. In rodent behaviour analysis, computer vision and sensor-based systems now allow continuous tracking and pose estimation over extended periods, reducing human bias and improving reproducibility. Over the past 25 years, tracking methods have evolved from simple 2D single-animal approaches to sophisticated multi-animal systems capable of markerless identification and 3D pose estimation. These developments were driven by innovations in image processing, physics-based modelling, and, more recently, deep learning architectures that enable precise skeletal estimation and real-time inference. Behaviour recognition has similarly progressed, moving beyond rule-based systems to supervised machine learning and unsupervised clustering techniques that uncover latent behavioural patterns without predefined categories. This review retraces these technological and algorithmic milestones, highlighting how they shaped modern computational ethology and opened new avenues for studying complex social interactions and disease models. By examining trends and challenges, we provide insights into future directions for scalable, interpretable, and consensus-driven behaviour analysis. Animal Behaviour Analysis Animal Tracking Multi-object Tracking Machine Learning Deep Learning Computer Vision. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 08 Apr, 2026 Reviewers agreed at journal 16 Mar, 2026 Reviewers agreed at journal 16 Mar, 2026 Reviewers invited by journal 16 Mar, 2026 Editor assigned by journal 18 Feb, 2026 Submission checks completed at journal 18 Feb, 2026 First submitted to journal 17 Feb, 2026 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8904710","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":608387101,"identity":"20be69b4-3d00-4629-a45b-732e9e252e89","order_by":0,"name":"Raul Alfredo de Sousa Silva","email":"data:image/png;base64,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","orcid":"","institution":"Aix-Marseille University","correspondingAuthor":true,"prefix":"","firstName":"Raul","middleName":"Alfredo de Sousa","lastName":"Silva","suffix":""},{"id":608387102,"identity":"9329d917-1738-48f4-90c8-4091f1c3ee24","order_by":1,"name":"Rabah Iguernaissi","email":"","orcid":"","institution":"Aix-Marseille University","correspondingAuthor":false,"prefix":"","firstName":"Rabah","middleName":"","lastName":"Iguernaissi","suffix":""},{"id":608387108,"identity":"5e4aa259-24c7-49d7-8cfa-be0b6bcc0fed","order_by":2,"name":"Djamal Merad","email":"","orcid":"","institution":"Aix-Marseille University","correspondingAuthor":false,"prefix":"","firstName":"Djamal","middleName":"","lastName":"Merad","suffix":""},{"id":608387110,"identity":"83399579-ce26-4d45-aabc-b6e6dc8f0919","order_by":3,"name":"Séverine Dubuisson","email":"","orcid":"","institution":"Aix-Marseille University","correspondingAuthor":false,"prefix":"","firstName":"Séverine","middleName":"","lastName":"Dubuisson","suffix":""}],"badges":[],"createdAt":"2026-02-17 23:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8904710/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8904710/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104996167,"identity":"3a17292a-ca15-4253-a219-b1cd222ff9e2","added_by":"auto","created_at":"2026-03-19 16:11:32","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":554529,"visible":true,"origin":"","legend":"","description":"","filename":"ReviewAnimalBehaviourAnalysis.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8904710/v1_covered_0b05b5a4-c16b-4bdf-a236-8a6d28c38bd6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Review of the Evolution of Rodent Tracking and Behaviour Analysis","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"machine-vision-and-applications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mvap","sideBox":"Learn more about [Machine Vision and Applications](https://www.springer.com/journal/138)","snPcode":"138","submissionUrl":"https://submission.springernature.com/new-submission/138/3","title":"Machine Vision and Applications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Animal Behaviour Analysis, Animal Tracking, Multi-object Tracking, Machine Learning, Deep Learning, Computer Vision.","lastPublishedDoi":"10.21203/rs.3.rs-8904710/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8904710/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Advances in computational power, miniaturisation, and cost reduction of electronic devices have profoundly transformed behavioural neuroscience, enabling automated, high-throughput data acquisition. 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