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Neuroanatomical correlates of brain–computer interface performance
by
Honda, Manabu
, DaSalla, Charles Sayo
, Kasahara, Kazumi
, Hanakawa, Takashi
in
BCI performance
/ Brain
/ Brain - anatomy & histology
/ Brain Mapping
/ Brain-Computer Interfaces
/ Brain–computer interface
/ Correlation
/ Cortical Synchronization
/ Customizing
/ Data Interpretation, Statistical
/ Electroencephalography
/ Emulation
/ Event-related desynchronization
/ 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
/ Motor Cortex - physiology
/ Motor imagery
/ Motors
/ Perceptions
/ Software
/ Studies
/ Success
/ Three dimensional
/ Voxel-based morphometry
/ Young Adult
2015
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Neuroanatomical correlates of brain–computer interface performance
by
Honda, Manabu
, DaSalla, Charles Sayo
, Kasahara, Kazumi
, Hanakawa, Takashi
in
BCI performance
/ Brain
/ Brain - anatomy & histology
/ Brain Mapping
/ Brain-Computer Interfaces
/ Brain–computer interface
/ Correlation
/ Cortical Synchronization
/ Customizing
/ Data Interpretation, Statistical
/ Electroencephalography
/ Emulation
/ Event-related desynchronization
/ 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
/ Motor Cortex - physiology
/ Motor imagery
/ Motors
/ Perceptions
/ Software
/ Studies
/ Success
/ Three dimensional
/ Voxel-based morphometry
/ Young Adult
2015
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Neuroanatomical correlates of brain–computer interface performance
by
Honda, Manabu
, DaSalla, Charles Sayo
, Kasahara, Kazumi
, Hanakawa, Takashi
in
BCI performance
/ Brain
/ Brain - anatomy & histology
/ Brain Mapping
/ Brain-Computer Interfaces
/ Brain–computer interface
/ Correlation
/ Cortical Synchronization
/ Customizing
/ Data Interpretation, Statistical
/ Electroencephalography
/ Emulation
/ Event-related desynchronization
/ 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
/ Motor Cortex - physiology
/ Motor imagery
/ Motors
/ Perceptions
/ Software
/ Studies
/ Success
/ Three dimensional
/ Voxel-based morphometry
/ Young Adult
2015
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Neuroanatomical correlates of brain–computer interface performance
Journal Article
Neuroanatomical correlates of brain–computer interface performance
2015
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Overview
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.
•Brain–computer interface (BCI) success rate varies between users.•We investigated the relationship between BCI success rate and brain structure.•BCI performance correlated with gray matter volume of somatosensory and motor areas.
Publisher
Elsevier Inc,Elsevier Limited
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