Leeuwis Nikki, Yoon Sue, Alimardani Maryam
Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, Netherlands.
Front Hum Neurosci. 2021 Oct 15;15:732946. doi: 10.3389/fnhum.2021.732946. eCollection 2021.
Motor Imagery BCI systems have a high rate of users that are not capable of modulating their brain activity accurately enough to communicate with the system. Several studies have identified psychological, cognitive, and neurophysiological measures that might explain this MI-BCI inefficiency. Traditional research had focused on mu suppression in the sensorimotor area in order to classify imagery, but this does not reflect the true dynamics that underlie motor imagery. Functional connectivity reflects the interaction between brain regions during the MI task and resting-state network and is a promising tool in improving MI-BCI classification. In this study, 54 novice MI-BCI users were split into two groups based on their accuracy and their functional connectivity was compared in three network scales (Global, Large and Local scale) during the resting-state, left vs. right-hand motor imagery task, and the transition between the two phases. Our comparison of High and Low BCI performers showed that in the alpha band, functional connectivity in the right hemisphere was increased in High compared to Low aptitude MI-BCI users during motor imagery. These findings contribute to the existing literature that indeed connectivity might be a valuable feature in MI-BCI classification and in solving the MI-BCI inefficiency problem.
运动想象脑机接口（MI-BCI）系统存在大量用户，他们无法精确调节自身大脑活动以与系统进行通信。多项研究已经确定了一些心理、认知和神经生理学指标，这些指标可能解释了MI-BCI效率低下的原因。传统研究聚焦于感觉运动区的μ波抑制以对想象进行分类，但这并未反映出运动想象背后的真实动态。功能连接反映了MI任务和静息态网络期间大脑区域之间的相互作用，是改善MI-BCI分类的一种很有前景的工具。在本研究中，54名MI-BCI新手用户根据其准确率被分为两组，并在静息态、左手与右手运动想象任务以及两个阶段之间的转换过程中，在三个网络尺度（全局、大尺度和局部尺度）上比较了他们的功能连接。我们对高、低BCI表现者的比较表明，在α波段，与低能力MI-BCI用户相比，高能力用户在运动想象期间右半球的功能连接增强。这些发现为现有文献提供了补充，即连接性确实可能是MI-BCI分类以及解决MI-BCI效率低下问题的一个有价值的特征。
