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Fronto-Parietal Gamma-Oscillations are a Cause of Performance Variation in Brain-Computer Interfacing
In recent work, we have provided evidence that fronto-parietal γ-oscillations of the electromagnetic field of the brain modulate the sensorimotor-rhythm. It is unclear, however, what impact this effect may have on explaining and addressing within-subject performance variations of brain-computer interfaces (BCIs). In this paper, we provide evidence that on a group-average classification accuracies in a two-class motor-imagery paradigm differ by up to 22.2% depending on the state of fronto-parietal γ-power. As such, this effect may have a large impact on the design of future BCI-systems. We further investigate whether adapting classification procedures to the current state of γ-power improves classification accuracy, and discuss other approaches to exploiting this effect.
@inproceedings{GrosseWentrup2011, title = {Fronto-Parietal Gamma-Oscillations are a Cause of Performance Variation in Brain-Computer Interfacing}, abstract = {In recent work, we have provided evidence that fronto-parietal γ-oscillations of the electromagnetic field of the brain modulate the sensorimotor-rhythm. It is unclear, however, what impact this effect may have on explaining and addressing within-subject performance variations of brain-computer interfaces (BCIs). In this paper, we provide evidence that on a group-average classification accuracies in a two-class motor-imagery paradigm differ by up to 22.2% depending on the state of fronto-parietal γ-power. As such, this effect may have a large impact on the design of future BCI-systems. We further investigate whether adapting classification procedures to the current state of γ-power improves classification accuracy, and discuss other approaches to exploiting this effect.}, pages = {384-387}, publisher = {IEEE}, address = {Piscataway, NJ, USA}, month = may, year = {2011}, slug = {grossewentrup2011}, author = {Grosse-Wentrup, M.}, month_numeric = {5} }