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High Gamma-Power Predicts Performance in Brain-Computer Interfacing
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 nding as empirical support for an in uence of attentional networks on BCI-performance via modulation of the sensorimotor rhythm.
@techreport{GrosseWentrupS2012, title = {High Gamma-Power Predicts Performance in Brain-Computer Interfacing}, 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 nding as empirical support for an in uence of attentional networks on BCI-performance via modulation of the sensorimotor rhythm.}, number = {3}, institution = {Max-Planck-Institut für Intelligente Systeme, Tübingen}, month = feb, year = {2012}, slug = {grossewentrups2012}, author = {Grosse-Wentrup, M. and Sch{\"o}lkopf, B.}, month_numeric = {2} }