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High Gamma-Power Predicts Performance in Brain-Computer Interfacing

2012

Technical Report

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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.

Author(s): Grosse-Wentrup, M. and Schölkopf, B.
Number (issue): 3
Year: 2012
Month: February
Day: 0

Department(s): Empirical Inference
Bibtex Type: Technical Report (techreport)

Institution: Max-Planck-Institut für Intelligente Systeme, Tübingen

Digital: 0

Links: PDF

BibTex

@techreport{GrosseWentrupS2012,
  title = {High Gamma-Power Predicts Performance in Brain-Computer Interfacing},
  author = {Grosse-Wentrup, M. and Sch{\"o}lkopf, B.},
  number = {3},
  institution = {Max-Planck-Institut für Intelligente Systeme, Tübingen},
  month = feb,
  year = {2012},
  month_numeric = {2}
}