{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T19:28:44Z","timestamp":1788377324364,"version":"build-2803163510"},"reference-count":45,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T00:00:00Z","timestamp":1695859200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging Neurosci."],"abstract":"<jats:sec><jats:title>Objectives<\/jats:title><jats:p>More than half of patients with acute ischemic stroke develop post-stroke cognitive impairment (PSCI), a significant barrier to future neurological recovery. Thus, predicting cognitive trajectories post-AIS is crucial. Our primary objective is to determine whether brain network properties from electroencephalography (EEG) can predict post-stroke cognitive function using machine learning approach.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We enrolled consecutive stroke patients who underwent both EEG during the acute stroke phase and cognitive assessments 3\u2009months post-stroke. We preprocessed acute stroke EEG data to eliminate low-quality epochs, then performed independent component analysis and quantified network characteristics using iSyncBrain\u00ae. Cognitive function was evaluated using the Montreal cognitive assessment (MoCA). We initially categorized participants based on the lateralization of their lesions and then developed machine learning models to predict cognitive status in the left and right hemisphere lesion groups.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Eighty-seven patients were included, and the accuracy of lesion laterality prediction using EEG attributes was 97.0%. In the left hemispheric lesion group, the network attributes of the theta band were significantly correlated with MoCA scores, and higher global efficiency, clustering coefficient, and lower characteristic path length were associated with higher MoCA scores. Most features related to cognitive scores were selected from the frontal lobe. The predictive powers (<jats:italic>R<\/jats:italic>-squared) were 0.76 and 0.65 for the left and right stroke groups, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Estimating EEG-based network properties in the acute phase of ischemic stroke through a machine learning model has a potential to predict cognitive outcomes after ischemic stroke.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fnagi.2023.1238274","type":"journal-article","created":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T03:59:40Z","timestamp":1695959980000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":24,"title":["Machine learning-based prediction of post-stroke cognitive status using electroencephalography-derived brain network attributes"],"prefix":"10.3389","volume":"15","author":[{"given":"Minwoo","family":"Lee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuseong","family":"Hong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sungsik","family":"An","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ukeob","family":"Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaekang","family":"Shin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeongjae","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mi Sun","family":"Oh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Byung-Chul","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyung-Ho","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jae-Sung","family":"Lim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seung Wan","family":"Kang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,9,28]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"3063","DOI":"10.1093\/brain\/aww194","article-title":"Brain networks under attack: robustness properties and the impact of lesions","volume":"139","author":"Aerts","year":"2016","journal-title":"Brain"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/s11517-017-1734-7","article-title":"Discrimination of stroke-related mild cognitive impairment and vascular dementia using eeg signal analysis","volume":"56","author":"Al-Qazzaz","year":"2018","journal-title":"Med. 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Neurosci."},{"key":"ref6","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1111\/epi.12044","article-title":"Frontal lobe connectivity and cognitive impairment in pediatric frontal lobe epilepsy","volume":"54","author":"Braakman","year":"2013","journal-title":"Epilepsia"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"11678","DOI":"10.1073\/pnas.1422487112","article-title":"Dynamic reconfiguration of frontal brain networks during executive cognition in humans","volume":"112","author":"Braun","year":"2015","journal-title":"Proc. Natl. Acad. Sci."},{"key":"ref8","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1016\/j.tics.2010.04.004","article-title":"Large-scale brain networks in cognition: emerging methods and principles","volume":"14","author":"Bressler","year":"2010","journal-title":"Trends Cogn. Sci."},{"key":"ref9","doi-asserted-by":"publisher","first-page":"2271","DOI":"10.1016\/j.neuroimage.2012.02.070","article-title":"Why use a connectivity-based approach to study stroke and recovery of function?","volume":"62","author":"Carter","year":"2012","journal-title":"NeuroImage"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"1467","DOI":"10.1016\/j.neunet.2004.07.002","article-title":"Fast exact leave-one-out cross-validation of sparse least-squares support vector machines","volume":"17","author":"Cawley","year":"2004","journal-title":"Neural Netw."},{"key":"ref11","doi-asserted-by":"publisher","first-page":"852","DOI":"10.1002\/hbm.21475","article-title":"Dynamic changes of Ica-derived eeg functional connectivity in the resting state","volume":"34","author":"Chen","year":"2013","journal-title":"Hum. Brain Mapp."},{"key":"ref12","doi-asserted-by":"publisher","first-page":"2023","DOI":"10.1002\/ar.20965","article-title":"Evaluation of the brain network organization from eeg signals: a preliminary evidence in stroke patient","volume":"292","author":"De Vico","year":"2009","journal-title":"Anat. Rec."},{"key":"ref13","doi-asserted-by":"publisher","first-page":"968","DOI":"10.1016\/j.neuroimage.2006.01.021","article-title":"An automated labeling system for subdividing the human cerebral cortex on mri scans into gyral based regions of interest","volume":"31","author":"Desikan","year":"2006","journal-title":"NeuroImage"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1177\/1550059419875916","article-title":"Quantitative and qualitative eeg as a prediction tool for outcome and complications in acute stroke patients","volume":"51","author":"Doerrfuss","year":"2019","journal-title":"Clin. EEG Neurosci."},{"key":"ref15","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1016\/S0166-2236(00)01633-7","article-title":"Common regions of the human frontal lobe recruited by diverse cognitive demands","volume":"23","author":"Duncan","year":"2000","journal-title":"Trends Neurosci."},{"key":"ref16","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.clinph.2012.07.003","article-title":"Eeg in ischaemic stroke: quantitative eeg can uniquely inform (sub-)acute prognoses and clinical management","volume":"124","author":"Finnigan","year":"2013","journal-title":"Clin. Neurophysiol."},{"key":"ref17","doi-asserted-by":"publisher","first-page":"2237","DOI":"10.1056\/NEJMra1706158","article-title":"Mapping symptoms to brain networks with the human connectome","volume":"379","author":"Fox","year":"2018","journal-title":"N. Engl. J. Med."},{"key":"ref18","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1023\/A:1024190429920","article-title":"Frontal lobe and cognitive development","volume":"31","author":"Fuster","year":"2002","journal-title":"J. Neurocytol."},{"key":"ref19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2022\/5666229","article-title":"Eeg-based spectral dynamic in characterization of poststroke patients with cognitive impairment for early detection of vascular dementia","volume":"2022","author":"Hadiyoso","year":"2022","journal-title":"J. Healthc. Eng."},{"key":"ref20","doi-asserted-by":"publisher","first-page":"713","DOI":"10.1007\/s13246-014-0308-3","article-title":"Eeg based brain source localization comparison of sloreta and eloreta","volume":"37","author":"Jatoi","year":"2014","journal-title":"Australas. Phys. Eng. Sci. 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Geriatr Med Res."},{"key":"ref24","doi-asserted-by":"publisher","first-page":"297","DOI":"10.5853\/jos.2021.02376","article-title":"Post-stroke cognitive impairment: pathophysiological insights into brain disconnectome from advanced neuroimaging analysis techniques","volume":"23","author":"Lim","year":"2021","journal-title":"J. Stroke"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2017\/8362741","article-title":"Complex brain network analysis and its applications to brain disorders: a survey","volume":"2017","author":"Liu","year":"2017","journal-title":"Complexity"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"e2257","DOI":"10.1212\/WNL.0000000000008612","article-title":"Profile of and risk factors for poststroke cognitive impairment in diverse ethnoregional groups","volume":"93","author":"Lo","year":"2019","journal-title":"Neurology"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"2553","DOI":"10.1109\/TBME.2015.2481482","article-title":"Real-time neuroimaging and cognitive monitoring using wearable dry eeg","volume":"62","author":"Mullen","year":"2015","journal-title":"I.E.E.E. Trans. Biomed. 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Neurophysiol."},{"key":"ref38","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.cortex.2017.12.019","article-title":"Re-emergence of modular brain networks in stroke recovery","volume":"101","author":"Siegel","year":"2018","journal-title":"Cortex"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"1228","DOI":"10.1016\/S1474-4422(10)70247-7","article-title":"Prediction of recovery of motor function after stroke","volume":"9","author":"Stinear","year":"2010","journal-title":"Lancet Neurol."},{"key":"ref40","doi-asserted-by":"publisher","first-page":"8659","DOI":"10.1016\/j.eswa.2010.06.065","article-title":"Eeg signal classification using pca, Ica, lda and support vector machines","volume":"37","author":"Subasi","year":"2010","journal-title":"Expert Syst. Appl."},{"key":"ref41","doi-asserted-by":"publisher","first-page":"822","DOI":"10.1016\/S1474-4422(13)70124-8","article-title":"Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration","volume":"12","author":"Wardlaw","year":"2013","journal-title":"Lancet Neurol."},{"key":"ref42","doi-asserted-by":"publisher","first-page":"981","DOI":"10.1177\/1747493020984552","article-title":"Post-stroke cognitive impairment on the mini-mental state examination primarily relates to left middle cerebral artery infarcts","volume":"16","author":"Weaver","year":"","journal-title":"Int. J. Stroke"},{"key":"ref43","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1016\/S1474-4422(21)00060-0","article-title":"Strategic infarct locations for post-stroke cognitive impairment: a pooled analysis of individual patient data from 12 acute ischaemic stroke cohorts","volume":"20","author":"Weaver","year":"","journal-title":"Lancet Neurol."},{"key":"ref44","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1258\/0007142001903120","article-title":"The impact of stroke","volume":"56","author":"Wolfe","year":"2000","journal-title":"Br. Med. Bull."},{"key":"ref45","doi-asserted-by":"publisher","first-page":"776","DOI":"10.3389\/fnins.2019.00776","article-title":"Altered topology of the structural brain network in patients with post-stroke depression","volume":"13","author":"Xu","year":"2019","journal-title":"Front. 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