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  High Gamma-Power Predicts Performance in Brain-Computer Interfacing

Grosse-Wentrup, M., & Schölkopf, B.(2012). High Gamma-Power Predicts Performance in Brain-Computer Interfacing (3). Tübingen, Germany: Max-Planck-Institut für Intelligente Systeme.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-B842-1 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-97D5-4
Genre: Report

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TR-IntSys-003.pdf (Publisher version), 2MB
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Grosse-Wentrup, M1, Author              
Schölkopf, B1, Author              
Affiliations:
1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, DE, ou_1497647              

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 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 in uence of attentional networks on BCI-performance via modulation of the sensorimotor rhythm.

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 Dates: 2012-02
 Publication Status: Published in print
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 Publishing info: Tübingen, Germany : Max-Planck-Institut für Intelligente Systeme
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 Identifiers: Report Nr.: 3
BibTex Citekey: GrosseWentrupS2012
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Title: Technical Report
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Publ. Info: Tübingen, Germany : Max-Planck-Institut für Intelligente Systeme
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1 - 14 Identifier: -