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  High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces

Grosse-Wentrup, M., & Schölkopf, B. (2012). High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces. Journal of Neural Engineering, 9(4): 046001. doi:10.1088/1741-2560/9/4/046001.

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Grosse-Wentrup, M1, Author           
Schölkopf, B.1, Author           
Affiliations:
1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              

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Free keywords: Abt. Schölkopf
 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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 Dates: 2012-05
 Publication Status: Issued
 Pages: 8
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1088/1741-2560/9/4/046001
BibTex Citekey: GrosseWentrupS2012_2
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Title: Journal of Neural Engineering
Source Genre: Journal
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Pages: - Volume / Issue: 9 (4) Sequence Number: 046001 Start / End Page: - Identifier: -