Kasahara Kazumi, DaSalla Charles Sayo, Honda Manabu, Hanakawa Takashi
Department of Functional Brain Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo 187-8502, Japan; Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Tokyo 187-8551, Japan.
Department of Functional Brain Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo 187-8502, Japan; Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Tokyo 187-8551, Japan; PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan.
Neuroimage. 2015 Apr 15;110:95-100. doi: 10.1016/j.neuroimage.2015.01.055. Epub 2015 Feb 4.
Brain-computer interfaces (BCIs) offer a potential means to replace or restore lost motor function. However, BCI performance varies considerably between users, the reasons for which are poorly understood. Here we investigated the relationship between sensorimotor rhythm (SMR)-based BCI performance and brain structure. Participants were instructed to control a computer cursor using right- and left-hand motor imagery, which primarily modulated their left- and right-hemispheric SMR powers, respectively. Although most participants were able to control the BCI with success rates significantly above chance level even at the first encounter, they also showed substantial inter-individual variability in BCI success rate. Participants also underwent T1-weighted three-dimensional structural magnetic resonance imaging (MRI). The MRI data were subjected to voxel-based morphometry using BCI success rate as an independent variable. We found that BCI performance correlated with gray matter volume of the supplementary motor area, supplementary somatosensory area, and dorsal premotor cortex. We suggest that SMR-based BCI performance is associated with development of non-primary somatosensory and motor areas. Advancing our understanding of BCI performance in relation to its neuroanatomical correlates may lead to better customization of BCIs based on individual brain structure.
脑机接口（BCIs）为替代或恢复丧失的运动功能提供了一种潜在手段。然而，不同用户之间BCI的性能差异很大，其原因尚不清楚。在此，我们研究了基于感觉运动节律（SMR）的BCI性能与脑结构之间的关系。参与者被要求使用右手和左手运动想象来控制电脑光标，这主要分别调节了他们左、右半球的SMR功率。尽管大多数参与者即使在初次尝试时就能以显著高于随机水平的成功率控制BCI，但他们在BCI成功率上也表现出很大的个体差异。参与者还接受了T1加权三维结构磁共振成像（MRI）。以BCI成功率作为自变量，对MRI数据进行基于体素的形态测量。我们发现BCI性能与辅助运动区、辅助体感区和背侧运动前皮层的灰质体积相关。我们认为基于SMR的BCI性能与非初级体感和运动区的发育有关。加深我们对BCI性能与其神经解剖学相关性的理解，可能会基于个体脑结构更好地定制BCIs。
