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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