Empirical Inference
Technical Report
2012
High Gamma-Power Predicts Performance in Brain-Computer Interfacing
PDF
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. |
| Links: | |
| Number (issue): | 3 |
| Year: | 2012 |
| Month: | February |
| Day: | 0 |
| BibTeX Type: | Technical Report (techreport) |
| Digital: | 0 |
| Electronic Archiving: | grant_archive |
| Institution: | Max-Planck-Institut für Intelligente Systeme, Tübingen |
BibTeX
@techreport{GrosseWentrupS2012,
title = {High Gamma-Power Predicts Performance in Brain-Computer Interfacing},
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 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.},
number = {3},
institution = {Max-Planck-Institut für Intelligente Systeme, Tübingen},
month = feb,
year = {2012},
author = {Grosse-Wentrup, M. and Sch{\"o}lkopf, B.},
month_numeric = {2}
}