Literature DB >> 19964229

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

W Wang1, A D Degenhart, J L Collinger, R Vinjamuri, G P Sudre, P D Adelson, D L Holder, E C Leuthardt, D W Moran, M L Boninger, A B Schwartz, D J Crammond, E C Tyler-Kabara, D J Weber.   

Abstract

In 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.

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Year:  2009        PMID: 19964229      PMCID: PMC3142578          DOI: 10.1109/IEMBS.2009.5333704

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  11 in total

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4.  Decoding individuated finger movements using volume-constrained neuronal ensembles in the M1 hand area.

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  38 in total

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5.  Decoding three-dimensional reaching movements using electrocorticographic signals in humans.

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7.  Neural Interactions Underlying Visuomotor Associations in the Human Brain.

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9.  Collaborative approach in the development of high-performance brain-computer interfaces for a neuroprosthetic arm: translation from animal models to human control.

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Review 10.  Neural interface technology for rehabilitation: exploiting and promoting neuroplasticity.

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