Empirical Inference

High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces

2012

Article

ei

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.

Author(s): Grosse-Wentrup, M. and Schölkopf, B.
Journal: Journal of Neural Engineering
Volume: 9
Number (issue): 4
Pages: 046001
Year: 2012
Month: May
Day: 0
Department(s): Empirical Inference
Bibtex Type: Article (article)
Digital: 0
DOI: 10.1088/1741-2560/9/4/046001
Links: Web

BibTex 

@article{GrosseWentrupS2012_2,
  title = {High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces},
  author = {Grosse-Wentrup, M. and Sch{\"o}lkopf, B.},
  journal = {Journal of Neural Engineering},
  volume = {9},
  number = {4},
  pages = {046001},
  month = may,
  year = {2012},
  doi = {10.1088/1741-2560/9/4/046001},
  month_numeric = {5}
}