English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

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

Grosse-Wentrup, M., & Schölkopf, B. (2012). High gamma-power predicts performance in sensorimotor-rhythm brain-computer interfaces. Journal of Neural Engineering, 9(4), 1-8. doi:10.1088/1741-2560/9/4/046001.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-B760-5 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-1A07-B
Genre: Journal Article

Files

show Files

Locators

show
hide
Description:
-

Creators

show
hide
 Creators:
Grosse-Wentrup, M1, Author              
Schölkopf, B1, Author              
Affiliations:
1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, DE, ou_1497647              

Content

show
hide
Free keywords: -
 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.

Details

show
hide
Language(s):
 Dates: 2012-05
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1088/1741-2560/9/4/046001
BibTex Citekey: GrosseWentrupS2012_2
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Journal of Neural Engineering
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 9 (4) Sequence Number: - Start / End Page: 1 - 8 Identifier: -