Human motor cortical activity recorded with Micro-ECoG electrodes, during individual finger movements

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dc.contributor.authorWang, W.
dc.contributor.authorDegenhart, A. D.
dc.contributor.authorCollinger, J. L.
dc.contributor.authorVinjamuri, Ramana
dc.contributor.authorSudre, G. P.
dc.contributor.authorAdelson, P. D.
dc.contributor.authorHolder, D. L.
dc.contributor.authorLeuthardt, E. C.
dc.contributor.authorMoran, D. W.
dc.contributor.authorBoninger, M. L.
dc.contributor.authorSchwartz, A. B.
dc.contributor.authorCrammond, D. J.
dc.contributor.authorTyler-Kabara, E. C.
dc.contributor.authorWeber, D. J.
dc.date.accessioned2021-05-19T18:36:04Z
dc.date.available2021-05-19T18:36:04Z
dc.date.issued2009-11-13
dc.description2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Societyen_US
dc.description.abstractIn this study human motor cortical activity was recorded with a customized micro-ECoG grid during individual finger movements. The quality of the recorded neural signals was characterized in the frequency domain from three different perspectives: (1) coherence between neural signals recorded from different electrodes, (2) modulation of neural signals by finger movement, and (3) accuracy of finger movement decoding. It was found that, for the high frequency band (60-120 Hz), coherence between neighboring micro-ECoG electrodes was 0.3. In addition, the high frequency band showed significant modulation by finger movement both temporally and spatially, and a classification accuracy of 73% (chance level: 20%) was achieved for individual finger movement using neural signals recorded from the micro-ECoG grid. These results suggest that the micro-ECoG grid presented here offers sufficient spatial and temporal resolution for the development of minimally-invasive brain-computer interface applications.en_US
dc.description.sponsorshipThis work was supported by the National Science Foundation under Cooperative Agreement EEC-0540865, Grant Number 5 UL1 RR024153 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH) and NIH Roadmap for Medical Research, and a special grant from the Office of the Senior Vice Chancellor for the Health Sciences at University of Pittsburgh. This papers contents are solely the responsibility of the authors and do not necessarily represent the official view of NCRR or NIH. Information on NCRR is available at http://www.ncrr.nih.gov/. Information on Re-engineering the Clinical Research Enterprise can be obtained from http://nihroadmap.nih.gov/clinicalresearch/overview-translational.asp. Additional funding support was provided by NIH grants from the NIBIB (1R01EB007749) and NINDS (1R21NS056136) and grant W81XWH-07-1-0716 from the US Army Medical Research and Material Command. We would like to thank the participant who kindly made it possible for us to perform this study. We would also like to thank the clinical staff of the epilepsy monitoring unit at the Childrens Hospital of Pittsburgh. We would also like to acknowledge Ms. Patricia Lordeon and Mr. Clinton Young for their engineering and technical support. We thank Dr. Gerwin Schalk for helpful discussions regarding ECoG recording and BCI2000 software.en_US
dc.description.urihttps://ieeexplore.ieee.org/document/5333704en_US
dc.format.extent9 pagesen_US
dc.genreconference papers and proceedings postprintsen_US
dc.identifierdoi:10.13016/m28yyc-snyw
dc.identifier.citationWang, W.; Degenhart, A. D.; Collinger, J. L.; Vinjamuri, R.; Sudre, G. P.; Adelson, P. D.; Holder, D. L.; Leuthardt, E. C.; Moran, D. W.; Boninger, M. L.; Schwartz, A. B.; Crammond, D. J.; Tyler-Kabara, E. C.; Weber, D. J.; Human motor cortical activity recorded with Micro-ECoG electrodes, during individual finger movements; 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (2009); https://ieeexplore.ieee.org/document/5333704en_US
dc.identifier.urihttps://doi.org/10.1109/IEMBS.2009.5333704
dc.identifier.urihttp://hdl.handle.net/11603/21569
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rights© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.titleHuman motor cortical activity recorded with Micro-ECoG electrodes, during individual finger movementsen_US
dc.typeTexten_US

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