Directed causality of the human electrocorticogram during dexterous movement.

Heather L. Benz, Maxwell Collard, Charalampos Tsimpouris, Soumyadipta Acharya, Nathan E Crone, Nitish V Thakor, Anastasios Bezerianos

Research output: Contribution to journalArticle

Abstract

While significant strides have been made in designing brain-machine interfaces for use in humans, efforts to decode truly dexterous movements in real time have been hindered by difficulty extracting detailed movement-related information from the most practical human neural interface, the electrocorticogram (ECoG). We explore a potentially rich, largely untapped source of movement-related information in the form of cortical connectivity computed with time-varying dynamic Bayesian networks (TV-DBN). We discover that measures of connectivity between ECoG electrodes derived from the local motor potential vary with dexterous movement in 65% of movement-related electrode pairs tested, and measures of connectivity derived from spectral features vary with dexterous movement in 76%. Due to the large number of features generated with connectivity methods, the TV-DBN a promising tool for dexterous decoding.

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Bayesian networks
Causality
Electrodes
Brain-Computer Interfaces
Decoding
Brain

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

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title = "Directed causality of the human electrocorticogram during dexterous movement.",
abstract = "While significant strides have been made in designing brain-machine interfaces for use in humans, efforts to decode truly dexterous movements in real time have been hindered by difficulty extracting detailed movement-related information from the most practical human neural interface, the electrocorticogram (ECoG). We explore a potentially rich, largely untapped source of movement-related information in the form of cortical connectivity computed with time-varying dynamic Bayesian networks (TV-DBN). We discover that measures of connectivity between ECoG electrodes derived from the local motor potential vary with dexterous movement in 65{\%} of movement-related electrode pairs tested, and measures of connectivity derived from spectral features vary with dexterous movement in 76{\%}. Due to the large number of features generated with connectivity methods, the TV-DBN a promising tool for dexterous decoding.",
author = "Benz, {Heather L.} and Maxwell Collard and Charalampos Tsimpouris and Soumyadipta Acharya and Crone, {Nathan E} and Thakor, {Nitish V} and Anastasios Bezerianos",
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AU - Benz, Heather L.

AU - Collard, Maxwell

AU - Tsimpouris, Charalampos

AU - Acharya, Soumyadipta

AU - Crone, Nathan E

AU - Thakor, Nitish V

AU - Bezerianos, Anastasios

PY - 2012

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