Neuroanatomical correlates of brain-computer interface performance

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 a...

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Bibliographic Details
Published in:NeuroImage (Orlando, Fla.) Fla.), 2015-04, Vol.110, p.95-100
Main Authors: Kasahara, Kazumi, DaSalla, Charles Sayo, Honda, Manabu, Hanakawa, Takashi
Format: Article
Language:English
Subjects:
Brain
Brain - anatomy & histology
Brain Mapping
Brain-Computer Interfaces
Correlation
Cortical Synchronization
Customizing
Data Interpretation, Statistical
Electroencephalography
Emulation
Experiments
Feedback
Female
Gray Matter - anatomy & histology
Gray Matter - physiology
Human-computer interface
Humans
Image Processing, Computer-Assisted
Imagination
Magnetic Resonance Imaging
Male
Mathematical analysis
Motor ability
Motor Cortex - physiology
Motors
Perceptions
Software
Studies
Success
Three dimensional
Young Adult
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Summary: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.
ISSN:1053-8119
1095-9572
DOI:10.1016/j.neuroimage.2015.01.055