Empirical Inference
Article
2012
High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces
Web
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. |
| Links: | |
| Journal: | Journal of Neural Engineering |
| Volume: | 9 |
| Number (issue): | 4 |
| Pages: | 046001 |
| Year: | 2012 |
| Month: | May |
| Day: | 0 |
| BibTeX Type: | Article (article) |
| DOI: | 10.1088/1741-2560/9/4/046001 |
| Digital: | 0 |
| Electronic Archiving: | grant_archive |
BibTeX
@article{GrosseWentrupS2012_2,
title = {High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces},
journal = {Journal of Neural Engineering},
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 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.},
volume = {9},
number = {4},
pages = {046001},
month = may,
year = {2012},
author = {Grosse-Wentrup, M. and Sch{\"o}lkopf, B.},
doi = {10.1088/1741-2560/9/4/046001},
month_numeric = {5}
}