Functional brain growth trajectories across the first decade of life from a single longitudinal cohort

Functional brain growth trajectories across the first decade of life from a single longitudinal cohort | 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 Functional brain growth trajectories across the first decade of life from a single longitudinal cohort Wei Gao, Haitao Chen, Janelle Liu, Yifan Gao, Kaiqiao Han, Joseph Blocher, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9557891/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 The first decade of life is marked by rapid reorganization of functional brain networks, yet normative longitudinal trajectories of key properties characterizing brain functional connectivity remain poorly defined. Using 1,436 resting-state fMRI scans from 633 children followed from birth to 10 years, we derived the first normative growth trajectories of functional connectivity maturation, network topology, and large-scale functional gradients. Network development followed a hierarchical, nonlinear pattern from primary to transmodal systems. Children later diagnosed with neurodevelopmental disorders showed disrupted functional gradient trajectories. Early measures of functional connectivity predicted later socioemotional and cognitive outcomes at 8 and 10 years of age. A deep learning brain-age prediction model revealed disorder-specific deviations, distinguishing risk groups in early childhood. Together, these findings establish normative reference curves for functional brain development and demonstrate the prognostic value of early functional connectivity measures, offering novel imaging biomarkers for the early identification of neurodevelopmental risk. Biological sciences/Neuroscience/Cognitive neuroscience Health sciences/Medical research/Paediatric research Full Text Additional Declarations There is NO Competing Interest. Supplementary Files NatHumBehavSupplement20260422.pdf Supplementary Information 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-9557891","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":638984235,"identity":"9b82e7a6-a8ce-4d28-96c9-efb520c2d94d","order_by":0,"name":"Wei 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