ArticleFrontiers in stroke2026
Electrophysiological signature of stroke recovery: investigating EEG biomarkers for prognostic insights.
Article in Frontiers in stroke, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: 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. Methods: 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 (Δ Resultss: 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 Δ Discussion: 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.
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