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

Grosse-Wentrup, M; Schölkopf, B

doi:10.1088/1741-2560/9/4/046001

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

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Grosse-Wentrup, M
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Schölkopf, B
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

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http://iopscience.iop.org/article/10.1088/1741-2560/9/4/046001/pdf
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引用

Grosse-Wentrup, M., & Schölkopf, B. (2012). High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces. Journal of Neural Engineering, 9(4), 1-8. doi:10.1088/1741-2560/9/4/046001.

引用: https://hdl.handle.net/11858/00-001M-0000-0013-B760-5

要旨

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.