TY - GEN
T1 - Brain biomarkers of motor adaptation using phase synchronization
AU - Gentili, Rodolphe J.
AU - Bradberry, Trent J.
AU - Hatfield, Bradley D.
AU - Contreras-Vidal, José L.
PY - 2009
Y1 - 2009
N2 - A growing number of brain monitoring tools for medical and biomedical applications such as surgery have been developed. Although many assistive technologies (e.g., brain computer interface (BCI) systems) aiming to restore cognitive-motor deficits are under development, no functional neural indicator or brain biomarker able to track the cortical dynamics of the brain when interacting with new tools and/or novel environments in ecological situations are available. Therefore this study aimed to investigate potential biomarkers reflecting the dynamic cognitive-motor states of subjects who had to learn a new tool. These biomarkers were derived from phase synchronization measures of electroencephalographic (EEG) signals (coherence, phase locking value (PLV)). The findings indicate a linear decrease of phase synchronization for both movement planning and execution as subjects adapt during tool learning. These changes were correlated with enhanced kinematics as the task progressed. These non-invasive biomarkers may play a role in bioengineering applications and particularly in BCI systems, allowing the establishment of co-adaptation/ cooperation between the user's brain and the decoding algorithm to design adaptive neuroprostheses.
AB - A growing number of brain monitoring tools for medical and biomedical applications such as surgery have been developed. Although many assistive technologies (e.g., brain computer interface (BCI) systems) aiming to restore cognitive-motor deficits are under development, no functional neural indicator or brain biomarker able to track the cortical dynamics of the brain when interacting with new tools and/or novel environments in ecological situations are available. Therefore this study aimed to investigate potential biomarkers reflecting the dynamic cognitive-motor states of subjects who had to learn a new tool. These biomarkers were derived from phase synchronization measures of electroencephalographic (EEG) signals (coherence, phase locking value (PLV)). The findings indicate a linear decrease of phase synchronization for both movement planning and execution as subjects adapt during tool learning. These changes were correlated with enhanced kinematics as the task progressed. These non-invasive biomarkers may play a role in bioengineering applications and particularly in BCI systems, allowing the establishment of co-adaptation/ cooperation between the user's brain and the decoding algorithm to design adaptive neuroprostheses.
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U2 - 10.1109/IEMBS.2009.5334743
DO - 10.1109/IEMBS.2009.5334743
M3 - Conference contribution
C2 - 19965060
AN - SCOPUS:77950974288
SN - 9781424432967
T3 - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
SP - 5930
EP - 5933
BT - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Y2 - 2 September 2009 through 6 September 2009
ER -