Replay builds an efficient cognitive map offline to avoid computation online

Replay builds an efficient cognitive map offline to avoid computation online | 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 Biological Sciences - Article Replay builds an efficient cognitive map offline to avoid computation online Yunzhe Liu, Jianxin Ou, Yukun Qu, Yue Xu, Timothy Behrens This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4742040/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Experiences are often fragmented. Reorganizing them into a coherent structure, or cognitive map, allows for inferences about unobserved relationships. A prominent theory suggests that offline replay is important for this reorganization of knowledge. However, testing this idea is hard because it requires tracking neural activity throughout the entire course of learning and reorganization. Here, we measured replay in humans throughout this process using Magnetoencephalography (MEG). This takes about 8 hours. We show that replay learns the cognitive map offline during rest, reducing the need for online computation during inferences. Subjects first experienced fragmented information along one-dimensional slices of a two-dimensional (2D) map. During rest, fast offline replay played trajectories in the 2D space - forming links that had never been experienced. This offline replay predicted the later emergence of a compact grid-cell-like code online. It is a generalizable schema representation across maps. During inference, we observed two different speeds of replay. Slow replay preferentially played out the immediate inference and was localized to the prefrontal cortex. Fast replay, developing later, played the background map and was associated with the medial temporal lobe. Fast replay was positively correlated with grid-cell-like representations, while slow replay was negatively correlated and linked to poorer inference performance. This indicates that the learned cognitive map reduces the need for slow, trial-specific computation online. Overall, these findings suggest that offline replay reorganizes sporadic experiences into structured knowledge, enabling efficient behavior. Biological sciences/Neuroscience/Cognitive neuroscience Biological sciences/Neuroscience/Learning and memory Biological sciences/Psychology/Human behaviour replay cognitive map learning inference grid-like code Full Text Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Under Review 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. 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-4742040","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Biological Sciences - Article","associatedPublications":[],"authors":[{"id":331805638,"identity":"f0f780ce-d840-4c1d-a827-adc701951460","order_by":0,"name":"Yunzhe Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYJACZiCWYQMSBz5UMDDwQQQTCGrhAWphPDjjDAMDG9FaQPRhzjYitBjcyD38uaCCgYdPIoHhMOO8w/JsDMwPPzC2peHRkpdgDHQPDxtIS+G2w4ZtDGzGEoxtOXi05Bgk87ZBtczcdjgB6DAzBsa2CrxaDvP+g2rhnQPSwv6NkBbDZt4GmJYGkBYekC24HSZ55o0xM88xCR42nocNB2ccSzdsY+Yplkg4h9v7fMdzjD/z1NjIybcnH/7wocZanp+9feOHD2XJOLUoHABTEkDM2AARAkVTAk4NDAzyDXgkR8EoGAWjYBSAAQBvBUisYTyhuQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-0836-9403","institution":"Beijing Normal University","correspondingAuthor":true,"prefix":"","firstName":"Yunzhe","middleName":"","lastName":"Liu","suffix":""},{"id":331805639,"identity":"a80fb608-db30-49e6-8c62-4f20f21d20f7","order_by":1,"name":"Jianxin Ou","email":"","orcid":"https://orcid.org/0000-0003-4934-3736","institution":"Beijing Normal University","correspondingAuthor":false,"prefix":"","firstName":"Jianxin","middleName":"","lastName":"Ou","suffix":""},{"id":331805640,"identity":"380fd75a-b08d-4585-b151-f96b1c3ef2d5","order_by":2,"name":"Yukun Qu","email":"","orcid":"","institution":"Beijing Normal University","correspondingAuthor":false,"prefix":"","firstName":"Yukun","middleName":"","lastName":"Qu","suffix":""},{"id":331805641,"identity":"bde32b5a-20ac-4064-bdf8-5aa07f34798e","order_by":3,"name":"Yue Xu","email":"","orcid":"","institution":"Chinese Institute for Brain Research","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Xu","suffix":""},{"id":331805642,"identity":"2c2c2e92-81d7-4d93-b676-17799926992c","order_by":4,"name":"Timothy Behrens","email":"","orcid":"","institution":"University of Oxford","correspondingAuthor":false,"prefix":"","firstName":"Timothy","middleName":"","lastName":"Behrens","suffix":""}],"badges":[],"createdAt":"2024-07-15 10:00:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4742040/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4742040/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84520516,"identity":"9f109de5-b91a-4f8d-bdeb-012af159ce92","added_by":"auto","created_at":"2025-06-13 03:16:58","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2525431,"visible":true,"origin":"","legend":"Article File","description":"","filename":"ReplayMapFinal.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4742040/v1_covered_7383dc37-c9eb-4549-9a2c-0c759916e3a2.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Replay builds an efficient cognitive map offline to avoid computation online","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"replay, cognitive map, learning, inference, grid-like code","lastPublishedDoi":"10.21203/rs.3.rs-4742040/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4742040/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Experiences are often fragmented. 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