Reaction Time Predicts Brain–Computer Interface Aptitude

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