Predicting cognition using estimated structural and functional connectivity networks and artificial intelligence in multiple sclerosis

Predicting cognition using estimated structural and functional connectivity networks and artificial intelligence in multiple sclerosis | 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 Predicting cognition using estimated structural and functional connectivity networks and artificial intelligence in multiple sclerosis Ceren Tozlu, Dylan Ong, Christopher Piccirillo, Hannah Schwartz, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6214708/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 Our prior work demonstrated that estimated structural and functional connectomes (eSC and eFC) generated using multiple sclerosis (MS) lesion masks and artificial intelligence (AI) models can predict disability as effectively as SC and FC derived from diffusion and functional MRI in MS. The goal of this study was to assess the ability of eSC and eFC in predicting baseline and 4-year follow-up cognition in MS patients. The Network Modification tool was performed to estimate SC from the clinical MRI-derived lesion masks. The eSC was then used as an input to Krakencoder, an encoder-decoder model, to estimate FC. The highest accuracy was obtained when predicting the follow-up Symbol Digit Modalities Test (SDMT) using regional eSC or eFC with a median Spearman's correlation of 0.58 for eSC and 0.56 for eFC, which is higher or similar to other studies that predicted cognition in healthy and diseased cohorts. Decreased eSC and eFC in the cerebellum and increased eFC in the default mode network were associated with lower follow-up SDMT scores. Our findings demonstrate that eSC and eFC derived from clinically acquired MRI and AI models can effectively predict cognition. The use of lesion-based estimates of connectome disruptions may potentially improve cognition-related individualized treatment planning. Health sciences/Neurology/Neurological disorders/Multiple sclerosis Health sciences/Medical research/Biomarkers/Predictive markers Multiple sclerosis cognition functional connectivity structural connectivity artificial intelligence brain mapping Full Text Additional Declarations Yes there is potential Competing Interest. A.J. was previously a paid consultant for Axem Neurotechnology Inc. and receives royalties from Oxford University Press, unrelated to the current work. Other co-authors declare that they have no competing interests. Supplementary Files MSBICAMSKrakencodermanuscript20250306cleanSI.pdf 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-6214708","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":436322415,"identity":"823132ca-1b03-4255-ba62-585bae4cbba8","order_by":0,"name":"Ceren Tozlu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYHACxgMQmhlES8gQVM8DxFAtbAkgLTykaOExgAngB/bs7Q8O89TY5PNL93x+daPGgoeB/fDRDXht4TmQcJjnWJrlzDlnt1nnHAM6jCct7QZeLRIJBw7zNhw2MLiRu804hw2oRYLHjICWxAaglv8G9jdynhnn/CNKSzIDUMsBAwOJHObHuW3EaDlzjOHgnGPJBhI30syYc/skeNgI+YW9vf3hgzc1dgb8M5Iff875VifHz374GF4tyIBNAkwSqxwEmD+QonoUjIJRMApGDgAA7QBEnOm9jQAAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-6828-886X","institution":"Weill Cornell Medicine","correspondingAuthor":true,"prefix":"","firstName":"Ceren","middleName":"","lastName":"Tozlu","suffix":""},{"id":436322416,"identity":"b5e70171-1bcf-48c1-b141-b56a0813edf0","order_by":1,"name":"Dylan Ong","email":"","orcid":"","institution":"Cornell University","correspondingAuthor":false,"prefix":"","firstName":"Dylan","middleName":"","lastName":"Ong","suffix":""},{"id":436322417,"identity":"c2ba7194-e013-42b2-adf6-ea17022c25cf","order_by":2,"name":"Christopher Piccirillo","email":"","orcid":"","institution":"Cornell University","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"","lastName":"Piccirillo","suffix":""},{"id":436322418,"identity":"fd67cfc4-ea35-49ec-8efc-0b3755c54650","order_by":3,"name":"Hannah Schwartz","email":"","orcid":"","institution":"Weill Cornell Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hannah","middleName":"","lastName":"Schwartz","suffix":""},{"id":436322419,"identity":"59d4e771-2647-46ac-b5c9-c5b478cc3be1","order_by":4,"name":"Abhishek Jaywant","email":"","orcid":"","institution":"Weill Cornell Medicine","correspondingAuthor":false,"prefix":"","firstName":"Abhishek","middleName":"","lastName":"Jaywant","suffix":""},{"id":436322420,"identity":"a3a4d7b5-5d45-42b9-80b3-10c514a66236","order_by":5,"name":"Thanh Nguyen","email":"","orcid":"https://orcid.org/0000-0002-1411-7694","institution":"Weill Cornell Medical College","correspondingAuthor":false,"prefix":"","firstName":"Thanh","middleName":"","lastName":"Nguyen","suffix":""},{"id":436322421,"identity":"617c36cb-4276-4f57-9bda-a0e75665a180","order_by":6,"name":"Keith Jamison","email":"","orcid":"https://orcid.org/0000-0001-7139-6661","institution":"Weill Cornell Medicine","correspondingAuthor":false,"prefix":"","firstName":"Keith","middleName":"","lastName":"Jamison","suffix":""},{"id":436322422,"identity":"09e73bc6-9a7b-4fcf-82c8-43de9fc53d6a","order_by":7,"name":"Susan Gauthier","email":"","orcid":"","institution":"Weill Cornell Medical College","correspondingAuthor":false,"prefix":"","firstName":"Susan","middleName":"","lastName":"Gauthier","suffix":""},{"id":436322423,"identity":"ca508acd-7f2e-455d-bec6-f47c80a8bb3f","order_by":8,"name":"Amy Kuceyeski","email":"","orcid":"https://orcid.org/0000-0002-5050-8342","institution":"Weill Cornell Medicine","correspondingAuthor":false,"prefix":"","firstName":"Amy","middleName":"","lastName":"Kuceyeski","suffix":""}],"badges":[],"createdAt":"2025-03-12 20:10:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6214708/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6214708/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79630100,"identity":"9289542c-3dd2-42bb-87d7-ad60bec6e42a","added_by":"auto","created_at":"2025-04-01 02:54:47","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4689493,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"MSBICAMSKrakencodermanuscript20250306cleanSI.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6214708/v1/6bf238ad92a1e8965fb7c394.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nA.J. was previously a paid consultant for Axem Neurotechnology Inc. and receives royalties from Oxford University Press, unrelated to the current work. 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