EEG-Based Brain Network Analysis of Chronic Stroke Patients After BCI Rehabilitation Training - Zhan, Gege; Chen, Shugeng; Ji, Yanyun; Xu, Ying; Song, Zuoting; Wang, Junkongshuai; Niu, Lan; Bin, Jianxiong; Kang, Xiaoyang; Jia, Jie (Frontiers in Human Neuroscience, 2022)
Traditional rehabilitation strategies become difficult in the chronic phase stage of stroke prognosis. Brain-computer interface (BCI) combined with external devices may improve motor function in chronic stroke patients, but it is lacking of comprehensive assessments of neurological changes regarding functional rehabilitation. This study aimed to comprehensively and quantitatively investigate the changes in brain activity induced by BCI-FES training in chronic stroke patients. We analyzed the EEG of two groups of chronic stroke patients, one group received functional electrical stimulation (FES) rehabilitation training (FES group), and the other group received BCI combined with FES training (BCI-FES group). We constructed functional networks in both groups of patients based on direct directed transfer function (dDTF) and assessed changes of brain activity using graph theory analysis. The results of this study can be summarized as follows: (i) After rehabilitation training, the Fugl-Meyer assessment scale (FMA) score was significantly improved in the BCI-FES group (p<0.05), and there was no significant difference in the FES group. (ii) Both the global and local graph theory measures of the brain network of chronic stroke patients in the BCI-FES group were improved after rehabilitation training. (iii) The node strength in the contralesional hemisphere and central region of patients in the BCI-FES group was significantly higher than that in the FES group after the intervention (p<0.05). And a significant increase in the node strength of C4 in the contralesional sensorimotor cortex region could be observed in the BCI-FES group (p<0.05). These results suggest that BCI-FES rehabilitation training can induce clinically significant improvements in motor function of chronic stroke patients. It can improve the functional integration and functional separation of brain networks and boosts compensatory activity in the contralesional hemisphere to a certain extent. The findings of our study may provide new insights into understanding the plastic changes of brain activity in chronic stroke patients induced by BCI-FES rehabilitation training.