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The aim of the study is to quantify individual changes in scalp connectivity patterns associated to the affected hand movement in stroke patients after a 1-month training based on BCIsupported motor imagery to improve upper limb motor recovery. To perform the statistical evaluation between preand post-training conditions at the single subject level, a resampling approach was applied to EEG datasets acquired from 12 stroke patients during the execution of a motor task with the stroke affected hand before and after the rehabilitative intervention. Significant patterns of the network reinforced after the training were extracted and a significant correlation was found between indices related to the reinforced pattern and the clinical outcome indicated by clinical scales.

Bci-Assisted Training for upper limb motor Rehabilitation: estimation of effects on Individual brain connectivity and motor Functions