9. Brain network modulation following motor imagery BCI-assisted training after stroke

Abstract

To evaluate the influence of Motor Imagery (MI) training assisted via Brain Computer Interface (BCI) on brain network organization in subacute stroke patients. We analyzed EEG-derived brain networks estimated before and after two training strategies (with and without BCI support); correlations between connectivity indices and clinical improvement were performed. Twenty-eight subacute stroke patients were enrolled and assigned to two groups: 14 patients underwent a one-month motor imagery (MI) training supported by a sensorimotor–based BCI (BCI group) while 14 underwent a similar MI training without BCI support (CTRL group). Before and after training we recorded EEG from 61 positions during 5 min of rest. Effective connectivity was computed by means of Partial Directed Coherence. Paired sample t -tests and Pearson’s Correlation were employed to analyze data (significance was defined by p p R = 0.568, p = 0.034). Overall findings indicate that MI training supported via BCI induces a reinforcement of interhemispheric connections related to sensorimotor rhythms; brain connectivity is a promising neurophysiological marker for BCI training efficacy in stroke rehabilitation. This work was partially supported by the European ICT Programme Project FP7-224631 and by the project “Brain Computer Interface-Driven Rehabilitation After Stroke: An Add-On Intervention For Hand Motor Recovery” (RF-2010-2319611) founded by the Italian Ministry of Healthcare.