Population modelling of the functional connectome in autism spectrum disorder

Population modelling of the functional connectome in autism spectrum disorder | 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 Population modelling of the functional connectome in autism spectrum disorder Hilary Sweatman, Jong-eun Lee, Hongxiu Jiang, Zeus Gracia Tabuenca, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7780004/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 Background. Autism spectrum disorder (ASD) is marked by heterogeneity in cognitive and social functioning, yet traditional case-control approaches often overlook this variability. In this study, we apply population reference modeling to functional connectivity (FC) data to better capture individual differences in ASD. Methods. Using movie-watching fMRI data from neurotypical (NT) participants, we derived age- and sex-specific trajectories of system segregation across large-scale brain networks. We then computed deviation indices for autistic individuals and examined their relationship to behavioural measures including IQ, memory, language, and social responsiveness. Results. Our results show that autistic participants exhibit significantly negative deviations in system segregation across most networks, suggesting delayed functional specialization. These deviations were behaviourally meaningful: greater negative deviation in the salience network correlated with higher social symptom severity, while positive deviations in control and default networks were associated with stronger nonverbal IQ and language skills. Episodic memory accuracy from a self-referential encoding task also tracked with deviations in the salience network, highlighting the relevance of network development to self- and other-referential processing. Limitations. Although our population reference model was derived from the moderate-sized, diverse HBN dataset, its generalizability is limited by demographic and geographic biases. Additionally, the small McGill dataset may have constrained our ability to detect additional effects. Conclusions. These findings support the utility of FC-based population modeling with child-friendly movie-fMRI in identifying meaningful individual differences in ASD. By moving beyond group averages, we can begin to characterize distinct developmental trajectories and cognitive profiles within the spectrum. This approach may inform early detection and personalized intervention strategies and ultimately help refine our understanding of the neural basis of autism. Autism spectrum disorder fMRI normative modeling population modeling brain networks system segregation Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.docx 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-7780004","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":531794782,"identity":"2e3485ec-40cf-4dd4-a782-91fb587b948d","order_by":0,"name":"Hilary Sweatman","email":"data:image/png;base64,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","orcid":"","institution":"McGill University","correspondingAuthor":true,"prefix":"","firstName":"Hilary","middleName":"","lastName":"Sweatman","suffix":""},{"id":531794783,"identity":"912b96d2-05df-47e1-b8ff-5cbd5a3d1a42","order_by":1,"name":"Jong-eun Lee","email":"","orcid":"","institution":"Center for Neuroscience Imaging Research","correspondingAuthor":false,"prefix":"","firstName":"Jong-eun","middleName":"","lastName":"Lee","suffix":""},{"id":531794784,"identity":"daaf33ed-7c50-44b8-b259-57f2c4886bc9","order_by":2,"name":"Hongxiu Jiang","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Hongxiu","middleName":"","lastName":"Jiang","suffix":""},{"id":531794785,"identity":"d1c1f5d9-95fa-46c5-8542-92fcd80ee614","order_by":3,"name":"Zeus Gracia Tabuenca","email":"","orcid":"","institution":"University of Zaragoza","correspondingAuthor":false,"prefix":"","firstName":"Zeus","middleName":"Gracia","lastName":"Tabuenca","suffix":""},{"id":531794786,"identity":"92477add-9326-4a61-b687-41fe74ee0f33","order_by":4,"name":"Kristen Chang","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Kristen","middleName":"","lastName":"Chang","suffix":""},{"id":531794787,"identity":"a502db19-c8eb-4083-a08c-fdff11859231","order_by":5,"name":"Isaac Bouhdana","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Isaac","middleName":"","lastName":"Bouhdana","suffix":""},{"id":531794788,"identity":"85e2101d-5994-4f45-813b-bba4bacfc37e","order_by":6,"name":"Haoran Yin","email":"","orcid":"","institution":"Concordia University","correspondingAuthor":false,"prefix":"","firstName":"Haoran","middleName":"","lastName":"Yin","suffix":""},{"id":531794789,"identity":"355171b0-427e-4eb1-8e58-42b925b59e81","order_by":7,"name":"Pascale Patenaude","email":"","orcid":"","institution":"McGill University","correspondingAuthor":false,"prefix":"","firstName":"Pascale","middleName":"","lastName":"Patenaude","suffix":""},{"id":531794790,"identity":"b693a836-60d4-4a02-9e4c-2b53227059b0","order_by":8,"name":"Seok-Jun Hong","email":"","orcid":"","institution":"Sungkyunkwan University","correspondingAuthor":false,"prefix":"","firstName":"Seok-Jun","middleName":"","lastName":"Hong","suffix":""},{"id":531794791,"identity":"879a5f8c-57be-4228-a466-353908598a99","order_by":9,"name":"Richard A.I. 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disorder","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"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":"Autism spectrum disorder, fMRI, normative modeling, population modeling, brain networks, system segregation","lastPublishedDoi":"10.21203/rs.3.rs-7780004/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7780004/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground.\u003c/b\u003e Autism spectrum disorder (ASD) is marked by heterogeneity in cognitive and social functioning, yet traditional case-control approaches often overlook this variability. In this study, we apply population reference modeling to functional connectivity (FC) data to better capture individual differences in ASD.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods.\u003c/b\u003e Using movie-watching fMRI data from neurotypical (NT) participants, we derived age- and sex-specific trajectories of system segregation across large-scale brain networks. We then computed deviation indices for autistic individuals and examined their relationship to behavioural measures including IQ, memory, language, and social responsiveness.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults.\u003c/b\u003e Our results show that autistic participants exhibit significantly negative deviations in system segregation across most networks, suggesting delayed functional specialization. These deviations were behaviourally meaningful: greater negative deviation in the salience network correlated with higher social symptom severity, while positive deviations in control and default networks were associated with stronger nonverbal IQ and language skills. Episodic memory accuracy from a self-referential encoding task also tracked with deviations in the salience network, highlighting the relevance of network development to self- and other-referential processing.\u003c/p\u003e\u003cp\u003eLimitations.\u003c/p\u003e\u003cp\u003eAlthough our population reference model was derived from the moderate-sized, diverse HBN dataset, its generalizability is limited by demographic and geographic biases. Additionally, the small McGill dataset may have constrained our ability to detect additional effects.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions.\u003c/b\u003e These findings support the utility of FC-based population modeling with child-friendly movie-fMRI in identifying meaningful individual differences in ASD. By moving beyond group averages, we can begin to characterize distinct developmental trajectories and cognitive profiles within the spectrum. This approach may inform early detection and personalized intervention strategies and ultimately help refine our understanding of the neural basis of autism.\u003c/p\u003e","manuscriptTitle":"Population modelling of the functional connectome in autism spectrum disorder","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-22 13:49:58","doi":"10.21203/rs.3.rs-7780004/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":"473bd1c6-41ca-457a-88ce-b817fe37f366","owner":[],"postedDate":"October 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-10T09:09:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-22 13:49:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7780004","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7780004","identity":"rs-7780004","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}