{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T07:43:46Z","timestamp":1766994226425,"version":"3.48.0"},"reference-count":38,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T00:00:00Z","timestamp":1765756800000},"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. Hum. Neurosci."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Stroke ranks as the second leading cause of death and disability worldwide, with the resulting upper-limb spasticity severely impairing patients\u2019 motor function and quality of life. However, existing clinical assessment scales exhibit a degree of subjectivity, and research into the neurophysiological mechanisms underlying spasticity remains insufficient. Brain network analysis offers a novel perspective for investigating the neural mechanisms associated with spasticity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Eight patients with upper limb spasticity due to stroke (MAS grades 1\u20132) and eight healthy controls were enrolled. Multi-channel EEG signals were recorded during different upper limb movements (fist clenching, elbow flexion, wrist flexion). Functional brain networks were constructed using the weighted phase delay index, and further calculations were performed on relevant brain network characteristics, including node degree, global efficiency, local efficiency, clustering coefficient, and small-world properties.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Research findings indicate that functional connectivity in spasticity patients is significantly lower than in healthy subjects, particularly in the alpha and beta frequency bands, with weaker cross-regional synchrony in frontal, central, and temporal lobe regions. Graph theory analysis further reveals that compared to healthy controls, spasticity patients exhibit significantly reduced global efficiency, local efficiency, and clustering coefficient, while small-world properties remain relatively preserved. Node degree analysis revealed abnormal compensatory activation in temporal and parietal regions, whereas healthy participants exhibited higher node degrees in central and frontal areas. These findings suggest that spasticity is associated with impaired local and global network integration, accompanied by inefficient compensatory mechanisms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>This study provides new evidence that post-stroke upper limb spasticity is not only a peripheral muscle phenomenon but also reflects disturbances in cortical network dynamics. Brain network metrics, particularly global and local efficiency, may serve as objective biomarkers to quantify spasticity severity and guide personalized rehabilitation interventions, offering a promising direction for developing precision rehabilitation strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fnhum.2025.1713235","type":"journal-article","created":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T06:29:58Z","timestamp":1765780198000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Functional brain network analysis in patients with upper-limb spasticity after stroke"],"prefix":"10.3389","volume":"19","author":[{"given":"Fangwen","family":"Gao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Man","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xubo","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lijie","family":"Gou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kuihua","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinyu","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,12,15]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"102229","DOI":"10.1016\/j.bspc.2020.102229","article-title":"An EEG-based methodology for the estimation of functional brain connectivity networks: application to the analysis of newborn EEG seizure","volume":"63","author":"Abbas","year":"2021","journal-title":"Biomed. 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Res."},{"key":"ref4","doi-asserted-by":"publisher","first-page":"666","DOI":"10.3390\/healthcare11050666","article-title":"Brain analysis with a complex network approach in stroke patients based on electroencephalography: a systematic review and Meta-analysis","volume":"11","author":"Asadi","year":"2023","journal-title":"Healthcare"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"655886","DOI":"10.3389\/fnsys.2021.655886","article-title":"Understanding the role of sensorimotor Beta oscillations","volume":"15","author":"Barone","year":"2021","journal-title":"Front. Syst. Neurosci."},{"key":"ref6","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1007\/s13760-022-02102-z","article-title":"Cortical connectivity in stroke using signals from resting-state EEG: a review of current literature","volume":"123","author":"Bistriceanu","year":"2023","journal-title":"Acta Neurol. Belg."},{"key":"ref7","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1016\/j.neuroimage.2013.06.039","article-title":"Multiscale topological properties of functional brain networks during motor imagery after stroke","volume":"83","author":"De Vico Fallani","year":"2013","journal-title":"NeuroImage"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"1577393","DOI":"10.3389\/fneur.2025.1577393","article-title":"Resting-state EEG associated with clinical measures to predict upper limb motor recovery of subacute stroke","volume":"16","author":"Ding","year":"2025","journal-title":"Front. Neurol."},{"key":"ref9","doi-asserted-by":"publisher","first-page":"3303","DOI":"10.1007\/s11517-023-02905-z","article-title":"Effect of tDCS on corticomuscular coupling and the brain functional network of stroke patients","volume":"61","author":"Fan","year":"2023","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref10","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1016\/S1474-4422(21)00252-0","article-title":"Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the global burden of disease study 2019","volume":"20","author":"Feigin","year":"2021","journal-title":"Lancet Neurol."},{"key":"ref11","doi-asserted-by":"publisher","first-page":"8894","DOI":"10.1038\/s41598-019-45289-7","article-title":"EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions","volume":"9","author":"Imperatori","year":"2019","journal-title":"Sci. Rep."},{"key":"ref12","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1148\/radiol.2016160422","article-title":"Decreased network efficiency in benign epilepsy with Centrotemporal spikes","volume":"283","author":"Ji","year":"2017","journal-title":"Radiology"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"1303","DOI":"10.1212\/WNL.30.12.1303","article-title":"The control of muscle tone, reflexes, and movement: Robert Wartenberg lecture","volume":"30","author":"Lance","year":"1980","journal-title":"Neurology"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1186\/s13098-024-01484-9","article-title":"Network efficiency of functional brain connectomes altered in type 2 diabetes patients with and without mild cognitive impairment","volume":"16","author":"Li","year":"2024","journal-title":"Diabetol. Metab. Syndr."},{"key":"ref15","doi-asserted-by":"publisher","first-page":"1143955","DOI":"10.3389\/fneur.2023.1143955","article-title":"Brain network characteristics between subacute and chronic stroke survivors in active, imagery, passive movement task: a pilot study","volume":"14","author":"Lin","year":"2023","journal-title":"Front. Neurol."},{"key":"ref16","doi-asserted-by":"publisher","first-page":"46","DOI":"10.3389\/fpsyt.2018.00046","article-title":"Enhanced network efficiency of functional brain networks in primary insomnia patients","volume":"9","author":"Ma","year":"2018","journal-title":"Front. Psych."},{"key":"ref17","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1007\/s10548-022-00915-y","article-title":"Relation between EEG measures and upper limb motor recovery in stroke patients: a scoping review","volume":"35","author":"Milani","year":"2022","journal-title":"Brain Topogr."},{"key":"ref18","doi-asserted-by":"publisher","first-page":"5404","DOI":"10.1191\/026921599677595404","article-title":"A review of the properties and limitations of the Ashworth and modified Ashworth scales as measures of spasticity","volume":"13","author":"Pandyan","year":"1999","journal-title":"Clin. Rehabil."},{"key":"ref19","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1016\/j.neuroimage.2019.05.026","article-title":"ICLabel: an automated electroencephalographic independent component classifier, dataset, and website","volume":"198","author":"Pion-Tonachini","year":"2019","journal-title":"NeuroImage"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1186\/s12883-021-02319-0","article-title":"Mapping causal circuit dynamics in stroke using simultaneous electroencephalography and transcranial magnetic stimulation","volume":"21","author":"Rolle","year":"2021","journal-title":"BMC Neurol."},{"key":"ref21","doi-asserted-by":"publisher","first-page":"115","DOI":"10.3389\/fphy.2019.00115","article-title":"Characterization of visuomotor\/imaginary movements in EEG: an information theory and complex network approach","volume":"7","author":"Rosso","year":"2019","journal-title":"Front. 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Bull."},{"key":"ref24","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1186\/s12868-016-0283-6","article-title":"25th annual computational neuroscience meeting: CNS-2016","volume":"17","author":"Sharpee","year":"2016","journal-title":"BMC Neurosci."},{"key":"ref25","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1089\/brain.2021.0070","article-title":"Altered functional networks of alpha and low-Beta bands during upper limb movement and association with motor impairment in chronic stroke","volume":"13","author":"Shim","year":"2023","journal-title":"Brain Connect."},{"key":"ref26","doi-asserted-by":"publisher","first-page":"e02097","DOI":"10.1002\/brb3.2097","article-title":"Electroencephalography resting-state networks in people with stroke","volume":"11","author":"Snyder","year":"2021","journal-title":"Brain Behav."},{"key":"ref27","doi-asserted-by":"publisher","first-page":"149261","DOI":"10.1016\/j.brainres.2024.149261","article-title":"Analysis of brain network differences in the active, motor imagery, and passive stoke rehabilitation paradigms based on the task-state EEG","volume":"1846","author":"Su","year":"2025","journal-title":"Brain Res."},{"key":"ref28","doi-asserted-by":"publisher","first-page":"940845","DOI":"10.3389\/fnhum.2022.940845","article-title":"Oscillatory beta\/alpha band modulations: a potential biomarker of functional language and motor recovery in chronic stroke?","volume":"16","author":"Ulanov","year":"2022","journal-title":"Front. 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Neurosci."},{"key":"ref32","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1007\/s00702-007-0833-2","article-title":"Spasticity treatment with botulinum toxins","volume":"115","author":"Ward","year":"2008","journal-title":"J. Neural Transm."},{"key":"ref33","doi-asserted-by":"publisher","first-page":"2476","DOI":"10.1093\/brain\/awg245","article-title":"Neural correlates of motor recovery after stroke: a longitudinal fMRI study","volume":"126","author":"Ward","year":"2003","journal-title":"Brain"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1038\/30918","article-title":"Collective dynamics of \u2018small-world\u2019networks","volume":"393","author":"Watts","year":"1998","journal-title":"Nature"},{"key":"ref35","doi-asserted-by":"publisher","first-page":"S13","DOI":"10.1212\/WNL.0b013e3182762448","article-title":"Toward an epidemiology of poststroke spasticity","volume":"80","author":"Wissel","year":"2013","journal-title":"Neurology"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"513","DOI":"10.2174\/1567205018666211001110824","article-title":"Functional connectivity alterations based on the weighted phase lag index: an exploratory electroencephalography study on Alzheimer's disease","volume":"18","author":"Yan","year":"2021","journal-title":"Curr. Alzheimer Res."},{"key":"ref37","doi-asserted-by":"publisher","first-page":"103636","DOI":"10.1016\/j.nicl.2024.103636","article-title":"Neuroimaging of motor recovery after ischemic stroke - functional reorganization of motor network","volume":"43","author":"Yu","year":"2024","journal-title":"Neuroimage Clin."},{"key":"ref38","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1186\/s40779-023-00502-7","article-title":"The applied principles of EEG analysis methods in neuroscience and clinical neurology","volume":"10","author":"Zhang","year":"2023","journal-title":"Mil. Med. 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