2026-10-14T07:46:15Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34007925 2026-09-28T04:23:08Z category_363 portal_316 item_type_3 month_year_09_2026

Supplementary file 1_Electrophysiological signature of stroke recovery: investigating EEG biomarkers for prognostic insights.pdf Majid Khalili-Ardali (23254850) Vivek Sharma (1565158) Tarandeep Singh Mandahar (25119204) Francisco Páscoa dos Santos (16510676) Paul Tiesinga (4001927) Nick Ramsey (4392091) Neurology and Neuromuscular Diseases EEG lesion metastability microstates stroke synchrony Introduction<p>Stroke is a leading cause of long-term disability, often resulting in persistent motor impairments that reflect disruptions in large-scale brain networks. An integrated framework capturing spatiotemporal EEG dynamics would help clarify how these networks change during recovery.</p>Methods<p>We analysed resting-state EEG from stroke patients at 1 week (Session 1) and three months (Session 2) post-stroke to investigate electrophysiological biomarkers of motor recovery, indexed by change in the Fugl-Meyer scale (ΔFM). We quantified relative alpha-band power, microstate metrics (mean duration, complexity, and transition probabilities), and measures of metastability and synchrony derived from the Kuramoto Order Parameter.</p>Results:s<p>Change in relative alpha power emerged as the strongest single correlate of motor improvement, accounting for the largest proportion of variance among the EEG measures examined. Metastability and synchrony did not individually reach statistical significance but showed moderate positive correlations with ΔFM, particularly in the alpha and theta bands, and added 26% explained variance in ΔFM when combined with alpha power. Microstate parameters did not explain additional variance once alpha power and network-level dynamics were accounted for. A hierarchical model combining alpha power, metastability/synchrony, and microstates explained over 78% of the variance in ΔFM.</p>Discussion<p>These findings indicate that stroke recovery involves restoring balanced alpha oscillations and flexible large-scale brain coordination. Larger samples and more frequent longitudinal assessments are required to confirm the prognostic utility of integrated EEG biomarkers for guiding personalised stroke rehabilitation strategies.</p> 2026-09-28T04:23:08Z Dataset Dataset 10.3389/fstro.2026.1894659.s001 https://figshare.com/articles/dataset/Supplementary_file_1_Electrophysiological_signature_of_stroke_recovery_investigating_EEG_biomarkers_for_prognostic_insights_pdf/34007925 CC BY 4.0