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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), 8 pages. doi:10.1088/1741-2560/9/4/046001.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-B760-5 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-B761-3
Genre: Journal Article

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Grosse-Wentrup, M1, Author           
Schölkopf, B1, Author           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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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 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
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 Identifiers: URI: http://iopscience.iop.org/1741-2552/9/4/046001
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: - Start / End Page: 8 pages Identifier: -