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Abstract #4640

Anatomical structure correlated with control performance for an electroencephalography-based brain-computer interface: A voxel-based morphometry study

Kazumi Kasahara 1,2 , Charles Sayo DaSalla 2 , Manabu Honda 1,2 , and Takashi Hanakawa 2,3

1 Department of Functional Brain Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodairashi, Tokyo, Japan, 2 Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Kodairashi, Tokyo, Japan, 3 PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama, Japan

Brain-computer interfaces (BCIs) have been widely studied for their potential to replace lost functions in the form of neuroprostheses. However, BCI performance varies considerably among individuals, and the factors affecting BCI performance are poorly understood. Therefore, we investigated the relationship between performance of an electroencephalographic (EEG) mu rhythm-based BCI (EEG-BCI) and brain structure. We found correlations between EEG-BCI performance and gray matter volume of Area 5, the dorsal premotor cortex, and supplementary motor area. These findings demonstrate the need to develop BCIs better suited to individual performance variability and may also provide insight into the methods for doing so.

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