Structured experience shapes strategy learning and neural dynamics in the medial entorhinal cortex

Structured experience shapes strategy learning and neural dynamics in the medial entorhinal cortex | 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 Structured experience shapes strategy learning and neural dynamics in the medial entorhinal cortex James Heys, John Bowler, Dua Azhar, Cambria Jensen, Hyun-Woo Lee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6658028/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 Animals can solve new, complex tasks by reusing and adapting what they’ve learned before. This kind of flexibility depends not just on having prior experience, but on how that experience was structured in the first place. The design of early training curriculum is especially important: poorly structured experiences can hinder abstraction and limit generalization, while carefully structured training promotes more flexible and adaptive behavior. Yet, the neural mechanisms supporting this process remain unclear. To investigate how early training shapes learning we first trained recurrent neural networks (RNNs) on variants of an odor-timing task previously used to study complex timing behavior in mice. We then tested the RNN predictions on how previous experience affects generalization using behavioral and electrophysiological recordings in mice trained on the same task using staged training sequences. RNNs and mice trained without well-structured early experience developed rigid strategies and made repeated errors. In contrast, those given more balanced early training were better able to generalize and showed similar neural activity patterns that reflected the task’s underlying temporal structure. Using dynamical systems approaches, we reveal a mechanism for this effect: networks trained with appropriately structured curricula developed distinct dynamical motifs that support the correct abstractions when complexity was increased. Networks that lacked early training or received remedial curricula developed single fixed-point solutions that failed to generalize beyond the training stimuli. Together, these findings demonstrate that it is not just the presence of prior experience, but its structure, that governs how flexible and generalizable knowledge emerges in both biological systems and computational models. Biological sciences/Neuroscience/Learning and memory/Hippocampus Biological sciences/Neuroscience/Computational neuroscience/Dynamical systems 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-6658028","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":462623500,"identity":"30c832c4-c833-425b-8fab-52ece90dda23","order_by":0,"name":"James Heys","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYBACxmYGBmYQgx8hxgPEbERokWyAayCgBQTAWgwOEKuFuZ07gbmg4rC98e3mY9IVFQyJ+9nPHmD4UHYYj8N4NzDPOHM4cdudY2mSZ84wJPbw5CUwzjhHQAtv2+EEsxs5ZpKNbUAtDDkGIBECWv4BHTYj/xtEC/8bA+a/BLU0HGbcIJHDBtEiAbSFkYCWwzzH0hNn3Egztmw4I2Hcc+ONwcGec+k4tRj2n934mKfG2p5/RvLDmw0VNrLt/TmGD36UWePW0sDAcICBoRnGlwCTB3CqBwJ5CFWHT80oGAWjYBSMdAAA+EpSJv5k5kgAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-0323-3777","institution":"University of Utah","correspondingAuthor":true,"prefix":"","firstName":"James","middleName":"","lastName":"Heys","suffix":""},{"id":462623501,"identity":"9012d3e4-1cc4-4ee4-8dea-2d293e05f70e","order_by":1,"name":"John Bowler","email":"","orcid":"","institution":"University of Utah","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Bowler","suffix":""},{"id":462623502,"identity":"1cdd77f7-1371-42dc-88be-ca62e213a31c","order_by":2,"name":"Dua Azhar","email":"","orcid":"","institution":"University of Utah","correspondingAuthor":false,"prefix":"","firstName":"Dua","middleName":"","lastName":"Azhar","suffix":""},{"id":462623503,"identity":"ab6c0366-faf5-4f91-8530-968ecdb19eeb","order_by":3,"name":"Cambria Jensen","email":"","orcid":"","institution":"University of Utah","correspondingAuthor":false,"prefix":"","firstName":"Cambria","middleName":"","lastName":"Jensen","suffix":""},{"id":462623504,"identity":"66a008b7-331b-431f-a397-f29709b8b533","order_by":4,"name":"Hyun-Woo Lee","email":"","orcid":"https://orcid.org/0000-0002-2070-3286","institution":"University of Utah","correspondingAuthor":false,"prefix":"","firstName":"Hyun-Woo","middleName":"","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2025-05-13 18:10:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6658028/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6658028/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83571990,"identity":"935c63c6-1215-47e6-abff-5ed1abb16106","added_by":"auto","created_at":"2025-05-28 17:10:25","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":20381869,"visible":true,"origin":"","legend":"Article File","description":"","filename":"BowleretalStructuredExperienceShapesLearningFinalMay13.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6658028/v1_covered_300d1a0b-0e3d-4990-9015-fd8c52fbca62.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Structured experience shapes strategy learning and neural dynamics in the\r\nmedial entorhinal cortex","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":"","lastPublishedDoi":"10.21203/rs.3.rs-6658028/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6658028/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Animals can solve new, complex tasks by reusing and adapting what they’ve learned before. 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