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Abstract:
When a subject operates a non-invasive brain-computer interface (BCI), the system correctly infers the subject's intention in some trials, yet fails to make the right decision in other trials. As the algorithm used to decode brain signals is typically fixed, the reason for this variation in performance has to be found in the subject's brain states. In this talk, I argue that distributed gamma-range oscillations play a major role in determining BCI-performance. In particular, I present empirical evidence that gamma-range oscillations modulate the sensorimotor-rhythm [1], and may be used to predict BCI-performance on a trial-to-trial basis [2]. I further present preliminary evidence that feedback of fronto-parietal gamma-range oscillations may be used to induce a state-of-mind beneficial for operating a BCI [3].
