Towards improvement of MI-BCI performance of subjects with BCI deficiency

The subjects´ performance in using a brain-computer interface (BCI) system controlled by motor imagery (MI) varies considerably. Poor subjects´ performance, known as BCI deficiency, can be due to the subjects´ inability to modulate their sensorimotor rhythms (SMRs). In this work, we investigated the feasibility of improving the BCI performance through neurofeedback (NF) training of the resting state alpha rhythm (8-13 Hz). Thirteen healthy subjects were recruited and randomly assigned to the experimental or the control group. The experimental group participated in a MI-BCI session, followed by 12 NF sessions, and a final MI-BCI sessions. The control group performed a MI-BCI session followed by a final MI-BCI session. The results showed that the performances of the experimental group after 12 sessions of NF significantly improved upon the initial MI-BCI performance (p=0.02) but not the control group (p=0.14). Moreover, the resting state alpha of the experimental group significantly improved after 12 sessions of NF (p=0.04). In conclusion, the proposed approach is promising to address BCI deficiency.