Using occipital ⍺-bursts to modulate behaviour in real-time

Abstract

ABSTRACTSpontaneous oscillatory neural activity can influence the processing of incoming sensory input and subsequent behavioural reactions. Spontaneous oscillatory activity mostly appears in stochastic bursts, but typical trial-averaged approaches fail to capture this. We aimed at relating oscillatory bursts in the alpha band (8-13 Hz) to behaviour directly, via an EEG-based brain-computer interface (BCI) that allowed for burst-triggered stimulus presentation in real-time in a visual detection task. According to alpha theories, we hypothesised that targets presented during alpha-bursts should lead to slower responses and higher miss rates, whereas targets presented in the absence of bursts should lead to faster responses and higher false alarm rates. Our findings support the role of bursts in alpha-oscillations in visual perception and exemplify how real-time BCI systems can be used as a test bench for brain-behavioural theories.