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Fig. 3 | Journal of NeuroEngineering and Rehabilitation

Fig. 3

From: Topographical measures of functional connectivity as biomarkers for post-stroke motor recovery

Fig. 3

Data processing pipeline. EEG artifacts were rejected by visual inspection and high-pass filtering, and trial windows corresponding to reaching movements were extracted based on kinematic data. A wavelet filter bank was then applied to separate 6.25–12.5 Hz, 12.5–25 Hz, and 25–50 Hz bands. Functional connectivity between each pair of electrodes was calculated using tGMA, and the resulting dependence matrices were binarized using a sparsity threshold. Several graph metrics were applied in order to produce potential biomarkers, which were then analyzed for statistical relationships with the FMUE functional measure

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