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  High Gamma-Power Predicts Performance in Brain-Computer Interfacing. MPI-IS-TR-003

Grosse-Wentrup, M., & Schoelkopf, B.(2012). High Gamma-Power Predicts Performance in Brain-Computer Interfacing. MPI-IS-TR-003 (MPI-IS-TR-003). Tübingen: Max-Planck-Institut für Intelligente Systeme.

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 Creators:
Grosse-Wentrup, Moritz1, Author              
Schoelkopf, Bernhard1, Author              
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1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              

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Free keywords: MPI für Intelligente Systeme; Abt. Schölkopf; BCI, gamma, EEG, sensorimotor-rhythm. MPI-IS-TR-003
 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 gamma-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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Language(s): eng - English
 Dates: 2012-02-072012-02-07
 Publication Status: Published in print
 Pages: -
 Publishing info: Tübingen : Max-Planck-Institut für Intelligente Systeme
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 Rev. Type: -
 Identifiers: eDoc: 578949
URI: http://mlin.kyb.tuebingen.mpg.de/mpi-is-tr-003.pdf
Other: MPI-IS-TR-003
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Title: Technical Report
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