EEG correlates of haptic feedback in a visuomotor tracking task.
Identifieur interne : 001E73 ( Ncbi/Checkpoint ); précédent : 001E72; suivant : 001E74EEG correlates of haptic feedback in a visuomotor tracking task.
Auteurs : Chun-Ling Lin [Taïwan] ; Fu-Zen Shaw ; Kuu-Young Young ; Chin-Teng Lin ; Tzyy-Ping JungSource :
- NeuroImage [ 1095-9572 ] ; 2012.
English descriptors
- KwdEn :
- MESH :
Abstract
This study investigates the temporal brain dynamics associated with haptic feedback in a visuomotor tracking task. Haptic feedback with deviation-related forces was used throughout tracking experiments in which subjects' behavioral responses and electroencephalogram (EEG) data were simultaneously measured. Independent component analysis was employed to decompose the acquired EEG signals into temporally independent time courses arising from distinct brain sources. Clustering analysis was used to extract independent components that were comparable across participants. The resultant independent brain processes were further analyzed via time-frequency analysis (event-related spectral perturbation) and event-related coherence (ERCOH) to contrast brain activity during tracking experiments with or without haptic feedback. Across subjects, in epochs with haptic feedback, components with equivalent dipoles in or near the right motor region exhibited greater alpha band power suppression. Components with equivalent dipoles in or near the left frontal, central, left motor, right motor, and parietal regions exhibited greater beta-band power suppression, while components with equivalent dipoles in or near the left frontal, left motor, and right motor regions showed greater gamma-band power suppression relative to non-haptic conditions. In contrast, the right occipital component cluster exhibited less beta-band power suppression in epochs with haptic feedback compared to non-haptic conditions. The results of ERCOH analysis of the six component clusters showed that there were significant increases in coherence between different brain networks in response to haptic feedback relative to the coherence observed when haptic feedback was not present. The results of this study provide novel insight into the effects of haptic feedback on the brain and may aid the development of new tools to facilitate the learning of motor skills.
DOI: 10.1016/j.neuroimage.2012.02.008
PubMed: 22348883
Affiliations:
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pubmed:22348883Le document en format XML
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<author><name sortKey="Lin, Chun Ling" sort="Lin, Chun Ling" uniqKey="Lin C" first="Chun-Ling" last="Lin">Chun-Ling Lin</name>
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<front><div type="abstract" xml:lang="en">This study investigates the temporal brain dynamics associated with haptic feedback in a visuomotor tracking task. Haptic feedback with deviation-related forces was used throughout tracking experiments in which subjects' behavioral responses and electroencephalogram (EEG) data were simultaneously measured. Independent component analysis was employed to decompose the acquired EEG signals into temporally independent time courses arising from distinct brain sources. Clustering analysis was used to extract independent components that were comparable across participants. The resultant independent brain processes were further analyzed via time-frequency analysis (event-related spectral perturbation) and event-related coherence (ERCOH) to contrast brain activity during tracking experiments with or without haptic feedback. Across subjects, in epochs with haptic feedback, components with equivalent dipoles in or near the right motor region exhibited greater alpha band power suppression. Components with equivalent dipoles in or near the left frontal, central, left motor, right motor, and parietal regions exhibited greater beta-band power suppression, while components with equivalent dipoles in or near the left frontal, left motor, and right motor regions showed greater gamma-band power suppression relative to non-haptic conditions. In contrast, the right occipital component cluster exhibited less beta-band power suppression in epochs with haptic feedback compared to non-haptic conditions. The results of ERCOH analysis of the six component clusters showed that there were significant increases in coherence between different brain networks in response to haptic feedback relative to the coherence observed when haptic feedback was not present. The results of this study provide novel insight into the effects of haptic feedback on the brain and may aid the development of new tools to facilitate the learning of motor skills.</div>
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<name sortKey="Shaw, Fu Zen" sort="Shaw, Fu Zen" uniqKey="Shaw F" first="Fu-Zen" last="Shaw">Fu-Zen Shaw</name>
<name sortKey="Young, Kuu Young" sort="Young, Kuu Young" uniqKey="Young K" first="Kuu-Young" last="Young">Kuu-Young Young</name>
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<country name="Taïwan"><noRegion><name sortKey="Lin, Chun Ling" sort="Lin, Chun Ling" uniqKey="Lin C" first="Chun-Ling" last="Lin">Chun-Ling Lin</name>
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