Investigating Neural Representation of Finger-Movement Directions Using Electroencephalography Independent Components

M. Tellache, H. Kambara, Y. Koike, M. Miyakoshi, N. Yoshimura
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Abstract

There are few EEG studies on finger movement directions because ocular artifacts also convey directional information, which makes it hard to separate the contribution of EEG from that of the ocular artifacts. To overcome this issue, we designed an experiment in which EEG’s temporal dynamics and spatial information are evaluated together to improve the performance of brain-computer interface (BCI) for classifying finger movement directions. Six volunteers participated in the study. We examined their EEG using decoding analyses. Independent components (ICs) that represented brain-source signals successfully classified the directions of the finger movements with higher rates than chance level. The weight analyses of the classifiers revealed that maximal performance of the classification was recorded at the latencies prior to the onset of finger movements. The weight analyses also revealed the relevant cortical areas including the right lingual, left posterior cingulate, left inferior temporal gyrus, and right precuneus, which indicated the involvement of the visuospatial processing. We concluded that combining spatial distribution and temporal dynamics of the scalp EEG may improve BCI performance.
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利用脑电图独立分量研究手指运动方向的神经表征
由于眼伪影也传递方向信息,因此对手指运动方向的EEG研究很少,很难将EEG的贡献与眼伪影的贡献区分开来。为了克服这一问题,我们设计了一种同时评估EEG时间动态和空间信息的实验,以提高脑机接口(BCI)在手指运动方向分类中的性能。6名志愿者参加了这项研究。我们用解码分析检查了他们的脑电图。代表脑源信号的独立分量(ic)以高于随机水平的速率成功地对手指运动方向进行了分类。分类器的权重分析显示,在手指运动开始前的潜伏期记录了最大的分类性能。重量分析还揭示了右侧舌区、左侧后扣带区、左侧颞下回区和右侧楔前叶区等相关皮质区域,提示了视觉空间加工的参与。我们认为,结合头皮脑电的空间分布和时间动态可以改善脑机接口的性能。
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