Global Brain Connectivity Alterations After Stroke: A Microstate-Based Community Analysis

Global Brain Connectivity Alterations After Stroke: A Microstate-Based Community Analysis | 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 Global Brain Connectivity Alterations After Stroke: A Microstate-Based Community Analysis Xiaoling Chen, Wenhao Hu, Yuhao Cai, Yingying Hao, Ying Wang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6476023/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 Quantifying the dynamic changes in brain function after stroke is essential for understanding its neural mechanisms. Stroke disrupts global brain connectivity and alters the spatiotemporal properties of brain network interactions. However, most research focuses on time-frequency methods to study dynamic connections within localized brain regions, leaving a gap in understanding the global topological complexity of brain networks after stroke. This study integrates resting-state EEG microstate analysis to build a microstate brain network and then propose a new community detection model based on microstate brain network (CDM-MBN) with the Louvain-PSI algorithm focusing on quasi-stability and network topology. We validated its effectiveness through comparison, and applied it to explore how the brain processes and integrates information after stroke. Simulation results showed that the Louvain-PSI algorithm outperforms other methods in detecting communities in complex networks, making it more suitable for brain network analysis. Further experimental results showed that the stroke patient group had stronger connectivity in the occipital lobe but weaker connectivity in the frontal lobe, while the elderly group showed similar connectivity to the young group. Differences in community structure were also observed, with the patient group displaying a more chaotic network, especially in the occipital lobe. In the healthy population, the elderly group had fewer communities than the young group. The community division results indicate that age-related changes speed up brain damage and hinder recovery in stroke patients. Abnormal brain activity patterns reflect the stroke's impact on brain function. The correlation with rehabilitation metrics underscores the clinical importance of these findings, offering a clearer understanding of brain function in stroke patients. Community Detection Microstate Network Model Spatiotemporal Complexity Stroke Full Text Additional Declarations No competing interests reported. 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. 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-6476023","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":452841669,"identity":"db1b1d55-fd6f-4006-848e-a4f9c2bb63f6","order_by":0,"name":"Xiaoling Chen","email":"","orcid":"","institution":"The Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Yanshan University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoling","middleName":"","lastName":"Chen","suffix":""},{"id":452841670,"identity":"c5326276-8abe-48fc-b4e4-4167a3623420","order_by":1,"name":"Wenhao 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