Can the occipital alpha-phase speed up visual detection through a real-time EEG-based brain-computer interface (BCI)?

Electrical brain oscillations reflect fluctuations in neural excitability. Fluctuations in the alpha band (alpha, 8-12 Hz) in the occipito-parietal cortex are thought to regulate sensory responses, leading to cyclic variations in visual perception. Inspired by this theory, some past and recent studies have addressed the relationship between alpha-phase from extra-cranial EEG and behavioural responses to visual stimuli in humans. The latest studies have used offline approaches to confirm alpha-gated cyclic patterns. However, a particularly relevant implication is the possibility to use this principle online, whereby stimuli are time-locked to specific alpha-phases leading to predictable outcomes in performance. Here, we aimed at providing a proof of concept for such real-time neurotechnology. Participants performed a speeded response task to visual targets that were presented upon a real-time estimation of the alpha-phase via an EEG closed-loop brain-computer interface (BCI). According to the theory, we predicted a modulation of reaction times (RTs) along the alpha-cycle. Our BCI system achieved reliable trial-to-trial phase locking of stimuli to the phase of individual occipito-parietal alpha-oscillations. Yet, the behavioural results did not support a consistent relation between RTs and the phase of the alpha-cycle neither at group nor at single participant levels. We must conclude that although the alpha-phase might play a role in perceptual decisions from a theoretical perspective, its impact on EEG-based BCI application appears negligible.

Automated summary

This study aimed to validate the impact of real-time estimation of alpha-phase in an EEG closed-loop brain-computer interface on behavioral responses. However, the results showed no consistent relationship between reaction times and alpha-phase, both at the group and individual participant levels.