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High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces
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.
@article{GrosseWentrupS2012_2, title = {High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces}, journal = {Journal of Neural Engineering}, 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.}, volume = {9}, number = {4}, pages = {046001}, month = may, year = {2012}, slug = {grossewentrups2012_2}, author = {Grosse-Wentrup, M. and Sch{\"o}lkopf, B.}, month_numeric = {5} }