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

To evaluate the influence ofMotor 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 < .05). Reinforcement of Interhemispheric Connections were observed in both groups (p < .05), with a different between-group behavior with respect to EEG frequency bands (beta/gamma and theta/alpha frequency bands for the BCI and CTRL group, respectively). Increased ipsilesional connectivity correlated with clinical improvement as measured by the Fugl-Mayer scale in the BCI group only (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