Structural Crystallization: A Unified Computational Framework for Memory Formation, Persistence, and Modification

Structural Crystallization: A Unified Computational Framework for Memory Formation, Persistence, and Modification | 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 Structural Crystallization: A Unified Computational Framework for Memory Formation, Persistence, and Modification Po-Ting Lin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9387132/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract Prevailing models of memory treat strength as a unitary quantity that increases with learning and decreases with forgetting or extinction. We argue that this conflation obscures a fundamental distinction: memory has separable dimensions of structural accumulation and representational fidelity, which are differentially modified by retrieval. Structural accumulation captures how much of a memory trace has been consolidated; representational fidelity captures how faithfully that trace preserves its original encoding. The two can change independently---a memory can retain its full structural extent while becoming progressively distorted, or dissolve while remaining perfectly faithful. This distinction, combined with a second distinction between structurally protective retrieval (externally guided, high-constraint) and structurally risky retrieval (internally generated, low-constraint), resolves several phenomena that have resisted unified explanation: why extinction is temporary but retrieval-extinction can produce lasting change, why stress-enhanced fear memories persist for orders of magnitude longer than ordinary memories, and why fear extinction is fragile while appetitive extinction is durable. We formalize these distinctions in a system of four coupled differential equations (the Structural Crystallization framework), calibrate it to two datasets, and show that it correctly predicts---without parameter adjustment---outcomes across five independent benchmarks where competing models (Rescorla-Wagner; latent cause) fail. Extensions to human declarative memory capture the testing effect crossover, while an explicit failure on the spacing effect reveals interpretable boundary conditions. The results demonstrate that separating accumulation from fidelity is not merely a modeling convenience but a theoretical necessity for any account of both the persistence and the modifiability of memory. Psychology Cognitive Neuroscience Computational Neuroscience memory consolidation reconsolidation fear conditioning computational modeling Full Text Additional Declarations The authors declare no competing interests. Supplementary Files CHANGELOG.pdf Version History Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions 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-9387132","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":622706584,"identity":"91bcdf83-f269-45d2-bc20-72098c49e8e9","order_by":0,"name":"Po-Ting Lin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwUlEQVRIiWNgGAWjYBACAyA+wFAgwcAP4iUUEKWFGajFQIJBsgGkxYBILWC7DA7ALCUEzNn7Dx66YWCRZ3x+deKHBwYM8vxiB/Brsew5zHA4x0Ci2OzG280SQIcZzpydQMBhN5LBWhK33Ti7AaQlweA2sVo2zzi7+QdpWjbw924jzhagXwzAWmbc4N1mkWAgQdgv5uyNjz/nVNQl9vef3XzzR4WNPL80AS0IIAFWKUGschDgP0CK6lEwCkbBKBhJAAC4ukWhh06OJgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0002-4825-6905","institution":"independent researcher","correspondingAuthor":true,"prefix":"","firstName":"Po-Ting","middleName":"","lastName":"Lin","suffix":""}],"badges":[],"createdAt":"2026-04-11 10:46:31","currentVersionCode":2,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9387132/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-9387132/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108006064,"identity":"dfac84c8-fbc9-49cc-8415-a0e161adbcab","added_by":"auto","created_at":"2026-04-28 12:52:40","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1333059,"visible":true,"origin":"","legend":"","description":"","filename":"ASTRUCTURALCRYSTALLIZATIONFRAMEWORKPRPreprintfix.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9387132/v2_covered_926b7450-336c-455a-acc7-7f8024a50e68.pdf"},{"id":107750815,"identity":"25513afd-49e5-4c31-99b3-7db9c814fe68","added_by":"auto","created_at":"2026-04-24 17:12:39","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":145699,"visible":true,"origin":"","legend":"\u003cp\u003eVersion History\u003c/p\u003e","description":"","filename":"CHANGELOG.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9387132/v2/3e213203c0abf832c7a778d9.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"Structural Crystallization: A Unified Computational Framework for Memory Formation, Persistence, and Modification","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Independent","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"memory consolidation, reconsolidation, fear conditioning, computational modeling","lastPublishedDoi":"10.21203/rs.3.rs-9387132/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9387132/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePrevailing models of memory treat strength as a unitary quantity that increases with learning and decreases with forgetting or extinction. We argue that this conflation obscures a fundamental distinction: memory has separable dimensions of structural accumulation and representational fidelity, which are differentially modified by retrieval. Structural accumulation captures how much of a memory trace has been consolidated; representational fidelity captures how faithfully that trace preserves its original encoding. The two can change independently---a memory can retain its full structural extent while becoming progressively distorted, or dissolve while remaining perfectly faithful. This distinction, combined with a second distinction between structurally protective retrieval (externally guided, high-constraint) and structurally risky retrieval (internally generated, low-constraint), resolves several phenomena that have resisted unified explanation: why extinction is temporary but retrieval-extinction can produce lasting change, why stress-enhanced fear memories persist for orders of magnitude longer than ordinary memories, and why fear extinction is fragile while appetitive extinction is durable. We formalize these distinctions in a system of four coupled differential equations (the Structural Crystallization framework), calibrate it to two datasets, and show that it correctly predicts---without parameter adjustment---outcomes across five independent benchmarks where competing models (Rescorla-Wagner; latent cause) fail. Extensions to human declarative memory capture the testing effect crossover, while an explicit failure on the spacing effect reveals interpretable boundary conditions. The results demonstrate that separating accumulation from fidelity is not merely a modeling convenience but a theoretical necessity for any account of both the persistence and the modifiability of memory.\u003c/p\u003e","manuscriptTitle":"Structural Crystallization: A Unified Computational Framework for Memory Formation, Persistence, and Modification","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2026-04-24 17:12:34","doi":"10.21203/rs.3.rs-9387132/v2","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2026-04-14 05:21:54","doi":"10.21203/rs.3.rs-9387132/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"be3fa48c-2c03-4fd4-b417-32880112fac7","owner":[],"postedDate":"April 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":66262926,"name":"Psychology"},{"id":66262927,"name":"Cognitive Neuroscience"},{"id":66262928,"name":"Computational Neuroscience"}],"tags":[],"updatedAt":"2026-04-14T05:21:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-24 17:12:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-9387132","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9387132","identity":"rs-9387132","version":["v2"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}