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Can the occipital alpha-phase speed up visual detection through a real-time EEG-based brain–computer interface (BCI)?
European Journal of Neuroscience ( IF 2.7 ) Pub Date : 2020-08-03 , DOI: 10.1111/ejn.14931
Irene Vigué-Guix 1 , Luis Morís Fernández 1, 2 , Mireia Torralba Cuello 1 , Manuela Ruzzoli 3 , Salvador Soto-Faraco 1, 4
Affiliation  

Electrical brain oscillations reflect fluctuations in neural excitability. Fluctuations in the alpha band (α, 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 α-phase from extra-cranial EEG and behavioural responses to visual stimuli in humans. The latest studies have used offline approaches to confirm α-gated cyclic patterns. However, a particularly relevant implication is the possibility to use this principle online, whereby stimuli are time-locked to specific α-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 α-phase via an EEG closed-loop brain–computer interface (BCI). According to the theory, we predicted a modulation of reaction times (RTs) along the α-cycle. Our BCI system achieved reliable trial-to-trial phase locking of stimuli to the phase of individual occipito-parietal α-oscillations. Yet, the behavioural results did not support a consistent relation between RTs and the phase of the α-cycle neither at group nor at single participant levels. We must conclude that although the α-phase might play a role in perceptual decisions from a theoretical perspective, its impact on EEG-based BCI application appears negligible.

中文翻译:

枕骨 α 相能否通过基于实时 EEG 的脑机接口 (BCI) 加速视觉检测?

脑电振荡反映了神经兴奋性的波动。枕顶叶皮层 α 波段(α,8-12 Hz)的波动被认为可以调节感觉反应,导致视觉感知的周期性变化。受这一理论的启发,过去和最近的一些研究已经解决了颅外脑电图的 α 期与人类对视觉刺激的行为反应之间的关系。最新研究使用离线方法来确认 α 门控循环模式。然而,一个特别相关的含义是可以在线使用这个原则从而刺激被时间锁定到特定的α阶段,从而导致可预测的性能结果。在这里,我们旨在为这种实时神经技术提供概念证明。参与者对通过脑电图闭环脑机接口 (BCI) 实时估计 α 阶段呈现的视觉目标执行了快速响应任务。根据该理论,我们预测了沿 α 循环的反应时间 (RT) 的调节。我们的 BCI 系统实现了对单个枕顶叶 α 振荡相位的刺激的可靠试验锁相。然而,行为结果不支持 RT 与 α 循环阶段之间的一致关系,无论是在组还是在单个参与者水平。
更新日期:2020-08-03
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