Alternations in resting-state neural networks in subacute non-fluent aphasia after stroke: A fNIRS study

Alternations in resting-state neural networks in subacute non-fluent aphasia after stroke: A fNIRS study | 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 Alternations in resting-state neural networks in subacute non-fluent aphasia after stroke: A fNIRS study Qingze Li, Maoqing Chen, Yi Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8771551/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Post-stroke aphasia is a prevalent and often disabling language impairment. Despite its high incidence, the precise neuropathological mechanisms underlying the condition, as well as the neural substrates that support functional recovery, remain incompletely understood. Understanding these mechanisms is essential for developing targeted rehabilitation strategies. Methods In this study, we employed fNIRS to collect the resting data of three groups of subjects. First, Pearson correlation coefficient analysis was used to calculate the functional connectivity of the whole brain, and then graph theory analysis was used to study the changes in the overall and regional characteristics of the three groups of brain networks. Results Compared with the healthy control (HC) group, the aphasia group exhibited significantly reduced whole-brain functional connectivity and a lower global clustering coefficient. Further nodal analysis revealed alterations in both node degree and nodal efficiency within the aphasia group. Notably, the local efficiency of the right-hemisphere homologue of Broca‘s area and the right dorsolateral prefrontal cortex (DLPFC) was significantly higher than that in the HC group. Furthermore, network hub analysis identified the right supplementary motor area (SMA) as a prominent global hub, demonstrating its elevated centrality within the overall network of the aphasia group. Conclusions This study demonstrates that patients with post-stroke non-fluent aphasia in the subacute stage exhibit significant alterations in brain network topology. These findings provide a novel neurophysiological basis for identifying and refining neuroregulatory targets in aphasia rehabilitation. Stroke Subacute aphasia Functional near-infrared spectroscopy Functional connectivity Neuromechanism Graph theory Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 30 Mar, 2026 Reviews received at journal 27 Mar, 2026 Reviews received at journal 24 Mar, 2026 Reviewers agreed at journal 24 Mar, 2026 Reviewers agreed at journal 06 Mar, 2026 Reviewers invited by journal 24 Feb, 2026 Editor invited by journal 16 Feb, 2026 Editor assigned by journal 09 Feb, 2026 Submission checks completed at journal 08 Feb, 2026 First submitted to journal 08 Feb, 2026 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. 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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-8771551","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":597208614,"identity":"7537e059-c86e-402a-a2bd-304d5b9f7fa6","order_by":0,"name":"Qingze Li","email":"","orcid":"","institution":"Panzhihua University","correspondingAuthor":false,"prefix":"","firstName":"Qingze","middleName":"","lastName":"Li","suffix":""},{"id":597208615,"identity":"566a2cf9-779f-4222-9ca5-e2daa12898ab","order_by":1,"name":"Maoqing Chen","email":"","orcid":"","institution":"Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Maoqing","middleName":"","lastName":"Chen","suffix":""},{"id":597208619,"identity":"0dff1d44-99f0-4441-b6f5-2d052f889268","order_by":2,"name":"Yi Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYDACCQgpx8DAA2IwE6/FmGQtDIkNRGuRn9387OHXNov07fxnj0kwVFgnNrCfPYBXC+OcY+bGsm0SuTsbzqVJMJxJT2zgyUvAq4VZIsFMWhKoZcPBHjMJxrbDiQ0SPAZ4tbBJpH8DaUk3OMwD1PKPCC08Ejlmkh/bJBIMjoG0NBChRUIip0ya4ZyE4c4eHmOLhGPpxm08Ofi1yM9I3yb5o6xO3pz/jOGNDzXWsv3sZ/BrAQFmXjYGBrCyBJDvCKoHAsYff6BaRsEoGAWjYBRgAwCuiTxod6I+twAAAABJRU5ErkJggg==","orcid":"","institution":"Panzhihua University","correspondingAuthor":true,"prefix":"","firstName":"Yi","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2026-02-03 06:08:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8771551/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8771551/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104398330,"identity":"aae69b24-260d-459a-9cfe-73e883cbe836","added_by":"auto","created_at":"2026-03-11 12:01:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":909956,"visible":true,"origin":"","legend":"","description":"","filename":"manuscriptnonanonymisedrevision1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8771551/v1_covered_9ccb3e9b-bf6e-4468-9602-5bb2f0b16ab7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Alternations in resting-state neural networks in subacute non-fluent aphasia after stroke: A fNIRS study","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-neurology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurl","sideBox":"Learn more about [BMC Neurology](http://bmcneurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurl","title":"BMC Neurology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Stroke, Subacute aphasia, Functional near-infrared spectroscopy, Functional connectivity, Neuromechanism, Graph theory","lastPublishedDoi":"10.21203/rs.3.rs-8771551/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8771551/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePost-stroke aphasia is a prevalent and often disabling language impairment. Despite its high incidence, the precise neuropathological mechanisms underlying the condition, as well as the neural substrates that support functional recovery, remain incompletely understood. Understanding these mechanisms is essential for developing targeted rehabilitation strategies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this study, we employed fNIRS to collect the resting data of three groups of subjects. First, Pearson correlation coefficient analysis was used to calculate the functional connectivity of the whole brain, and then graph theory analysis was used to study the changes in the overall and regional characteristics of the three groups of brain networks.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCompared with the healthy control (HC) group, the aphasia group exhibited significantly reduced whole-brain functional connectivity and a lower global clustering coefficient. Further nodal analysis revealed alterations in both node degree and nodal efficiency within the aphasia group. Notably, the local efficiency of the right-hemisphere homologue of Broca\u0026lsquo;s area and the right dorsolateral prefrontal cortex (DLPFC) was significantly higher than that in the HC group. Furthermore, network hub analysis identified the right supplementary motor area (SMA) as a prominent global hub, demonstrating its elevated centrality within the overall network of the aphasia group.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study demonstrates that patients with post-stroke non-fluent aphasia in the subacute stage exhibit significant alterations in brain network topology. 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