Reaction Time Predicts Brain-Computer Interface Aptitude

There is evidence that 15-30% of the general population cannot effectively operate brain-computer interfaces (BCIs). Thus the BCI performance predictors are critically required to pre-screen participants. Current neurophysiological and psychological tests either require complicated equipment or suffer from subjectivity. Thus, a simple and objective BCI performance predictor is desirable. Neurofeedback (NFB) training involves performing a cognitive task (motor imagery) instructed via sensory stimuli and re-adjusted through ongoing real-time feedback. A simple reaction time (SRT) test reflects the time required for a subject to respond to a defined stimulus. Thus, we postulated that individuals with shorter reaction times operate a BCI with rapidly updated feedback better than individuals with longer reaction times. Furthermore, we investigated how changing the feedback update interval (FUI), i.e., modification of the feedback provision frequency, affects the correlation between the SRT and BCI performance. Ten participants attended four NFB sessions with FUIs of 16, 24, 48, and 96 ms in a randomized order. We found that: 1) SRT is correlated with the BCI performance with FUIs of 16 and 96 ms; 2) good and poor performers elicit stronger ERDs and control BCIs more effectively (i.e., produced larger information transfer rates) with 16 and 96 ms FUIs, respectively. Our findings suggest that SRT may be used as a simple and objective surrogate for BCI aptitude with FUIs of 16 and 96 ms. It also implies that the FUI customization according to participants SRT measure may enhance the BCI performance.

Investigating the impact of feedback update interval on the efficacy of restorative brain-computer interfaces

Restorative brain-computer interfaces (BCIs) have been proposed to enhance stroke rehabilitation. Restorative BCIs are able to close the sensorimotor loop by rewarding motor imagery (MI) with sensory feedback. Despite the promising results from early studies, reaching clinically significant outcomes in a timely fashion is yet to be achieved. This lack of efficacy may be due to suboptimal feedback provision. To the best of our knowledge, the optimal feedback update interval (FUI) during MI remains unexplored. There is evidence that sensory feedback disinhibits the motor cortex. Thus, in this study, we explore how shorter than usual FUIs affect behavioural and neurophysiological measures following BCI training for stroke patients using a single-case proof-of-principle study design. The action research arm test was used as the primary behavioural measure and showed a clinically significant increase (36%) over the course of training. The neurophysiological measures including motor evoked potentials and maximum voluntary contraction showed distinctive changes in early and late phases of BCI training. Thus, this preliminary study may pave the way for running larger studies to further investigate the effect of FUI magnitude on the efficacy of restorative BCIs. It may also elucidate the role of early and late phases of motor learning along the course of BCI training.