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Neural Eng."],"published-print":{"date-parts":[[2026,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective<\/jats:italic>\n                    . Central vertigo (CV) lacks objective electrophysiological measures for severity assessment and rehabilitation monitoring. We aimed to characterize multiscale resting-state EEG alterations and identify clinically interpretable candidate features in stroke-related CV.\n                    <jats:italic>Approach<\/jats:italic>\n                    . Resting-state EEG was analyzed in 50 patients with stroke-related CV (31 moderate, 19 severe) and 31 age-matched healthy controls. The framework integrated relative spectral power, cross-frequency coupling, PLV-based sensor-level phase synchrony, graph metrics, machine-learning feature ranking, and associations with balance confidence and dizziness severity.\n                    <jats:italic>Main results<\/jats:italic>\n                    . Severe CV showed widespread relative delta-power reductions of 28.7%\u201329.4% versus controls. Post hoc analysis showed lower global absolute delta power in severe CV than controls (Tukey\n                    <jats:italic>p<\/jats:italic>\n                    = 0.0227; rank-based false-discovery-rate (FDR)\n                    <jats:italic>q<\/jats:italic>\n                    = 0.0459), although the absolute-power effect was less spatially extensive. Both patient groups showed reduced delta\u2013theta and delta\u2013beta amplitude\u2013amplitude coupling (AAC), enhanced delta\u2013alpha PPC, and theta-band increases in PLV-derived node degree, clustering, and global efficiency; local efficiency increased only in SV. Delta\u2013beta AAC ranked highest across machine-learning methods and correlated moderately with balance confidence (\n                    <jats:italic>\u03c1<\/jats:italic>\n                    = 0.470,\n                    <jats:italic>p<\/jats:italic>\n                    = 0.001) and dizziness severity (\n                    <jats:italic>\u03c1<\/jats:italic>\n                    = \u2212 0.472,\n                    <jats:italic>p<\/jats:italic>\n                    = 0.001). Zero-lag-robust measures showed the same theta ordering but were nonsignificant after FDR correction and did not establish volume-conduction-independent topology, supporting cautious PLV interpretation.\n                    <jats:italic>Significance<\/jats:italic>\n                    . Stroke-related CV involves coordinated alterations across oscillatory, cross-frequency, and sensor-level network measures. This interpretable framework identifies candidate EEG features for objective characterization that require external and longitudinal validation before clinical use.\n                  <\/jats:p>","DOI":"10.1088\/1741-2552\/ae98b9","type":"journal-article","created":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T22:52:54Z","timestamp":1786575174000},"page":"046059","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A multi-feature resting-state EEG framework for candidate EEG feature discovery in central vertigo"],"prefix":"10.1088","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-5438-142X","authenticated-orcid":true,"given":"Jiedong","family":"Nan","sequence":"first","affiliation":[{"name":"Tianjin University"},{"name":"Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Yang","sequence":"additional","affiliation":[{"name":"Huanhu Hospital Tianjin University"},{"name":"Tianjin Key Laboratory of Cerebral Vascular and Neurodegenerative Diseases"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoran","family":"Jiang","sequence":"additional","affiliation":[{"name":"Tianjin University"},{"name":"Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunyang","family":"Hong","sequence":"additional","affiliation":[{"name":"Tianjin University"},{"name":"Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3066-0345","authenticated-orcid":true,"given":"Jinghan","family":"Yang","sequence":"additional","affiliation":[{"name":"Tianjin University"},{"name":"Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3959-7898","authenticated-orcid":true,"given":"Yanru","family":"Bai","sequence":"additional","affiliation":[{"name":"Tianjin University"},{"name":"Xinjiang Hetian College"},{"name":"Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jialing","family":"Wu","sequence":"additional","affiliation":[{"name":"Huanhu Hospital Tianjin University"},{"name":"Tianjin Key Laboratory of Cerebral Vascular and Neurodegenerative Diseases"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9240-3020","authenticated-orcid":true,"given":"Guangjian","family":"Ni","sequence":"additional","affiliation":[{"name":"Tianjin University"},{"name":"Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,8,24]]},"reference":[{"key":"jneae98b9bib1","doi-asserted-by":"publisher","first-page":"e17","DOI":"10.1371\/journal.pcbi.0030017","type":"journal-article","article-title":"Efficiency and cost of economical brain functional networks","volume":"3","author":"Achard","year":"2007","journal-title":"PLoS Comput. 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