PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

High Gamma-Power Predicts Performance in Sensorimotor-Rhythm Brain-Computer Interfaces
Moritz Grosse-Wentrup and Bernhard Schölkopf
Journal of Neural Engineering Volume 9, Number 046001, 2012.

Abstract

Subjects operating a brain–computer interface (BCI) based on sensorimotor rhythms exhibit large variations in performance over the course of an experimental session. Here, we show that high-frequency γ-oscillations, originating in fronto-parietal networks, predict such variations on a trial-to-trial basis. We interpret this finding as empirical support for an influence of attentional networks on BCI performance via modulation of the sensorimotor rhythm.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Brain Computer Interfaces
ID Code:9620
Deposited By:Moritz Grosse-Wentrup
Deposited On:01 December 2012