Functional Connectivity Biomarkers Based on Resting-State EEG for Stroke Recovery

Closed eye resting-state EEG measurement was performed for healthy volunteers and stroke patients. Functional connectivity graphs were created using the debiased weighted Phase Lag Index as an association measure. Thresholded graphs of the delta, theta, alpha, and beta frequency bands were used for comparing connectivity measures between patients and control group as well as between the start and end of the stroke rehabilitation interval. Differences were found in the graph degree, clustering coefficient, global and local efficiency, which correlate with brain plasticity changes during stroke recovery and might be used as biomarkers to quantify stroke severity and outcome of recovery.