English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Sensorimotor functional connectivity: A neurophysiological factor related to BCI performance

Vidaurre, C., Haufe, S., Jorajuría, T., Müller, K.-R., & Nikulin, V. V. (2020). Sensorimotor functional connectivity: A neurophysiological factor related to BCI performance. Frontiers in Neuroscience, 14: 575081. doi:10.3389/fnins.2020.575081.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/21.11116/0000-0007-A9B2-1 Version Permalink: http://hdl.handle.net/21.11116/0000-0007-A9B3-0
Genre: Journal Article

Files

show Files
hide Files
:
Vidaurre_2020.pdf (Publisher version), 3MB
Name:
Vidaurre_2020.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Vidaurre, Carmen1, Author
Haufe, Stefan2, 3, Author
Jorajuría, Tania1, Author
Müller, Klaus-Robert4, 5, 6, 7, Author
Nikulin, Vadim V.8, 9, Author              
Affiliations:
1Statistics, Informatics and Mathematics Department, Public University of Navarre, Spain, ou_persistent22              
2Berlin Center for Advanced Neuroimaging (BCAN), Charité University Medicine Berlin, Germany, ou_persistent22              
3Bernstein Center for Computational Neuroscience, Berlin, Germany, ou_persistent22              
4Department of Machine Learning, TU Berlin, Germany, ou_persistent22              
5Center for Artificial Intelligence, Korea University, Seoul, Republic of Korea, ou_persistent22              
6Max Planck Institute for Informatics, Saarbrücken, Germany, ou_persistent22              
7Google Research, Brain Team, Berlin, Germany, ou_persistent22              
8Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
9Centre for Cognition and Decision Making, National Research University Higher School of Economics, Moscow, Russia, ou_persistent22              

Content

show
hide
Free keywords: Connectivity; Sensorimotor signals; BCI performance; μ-band; BCI efficiency; Pre-stimulus
 Abstract: Brain-Computer Interfaces (BCIs) are systems that allow users to control devices using brain activity alone. However, the ability of participants to command BCIs varies from subject to subject. About 20% of potential users of sensorimotor BCIs do not gain reliable control of the system. The inefficiency to decode user's intentions requires the identification of neurophysiological factors determining “good” and “poor” BCI performers. One of the important neurophysiological aspects in BCI research is that the neuronal oscillations, used to control these systems, show a rich repertoire of spatial sensorimotor interactions. Considering this, we hypothesized that neuronal connectivity in sensorimotor areas would define BCI performance. Analyses for this study were performed on a large dataset of 80 inexperienced participants. They took part in a calibration and an online feedback session recorded on the same day. Undirected functional connectivity was computed over sensorimotor areas by means of the imaginary part of coherency. The results show that post- as well as pre-stimulus connectivity in the calibration recording is significantly correlated to online feedback performance in μ and feedback frequency bands. Importantly, the significance of the correlation between connectivity and BCI feedback accuracy was not due to the signal-to-noise ratio of the oscillations in the corresponding post and pre-stimulus intervals. Thus, this study demonstrates that BCI performance is not only dependent on the amplitude of sensorimotor oscillations as shown previously, but that it also relates to sensorimotor connectivity measured during the preceding training session. The presence of such connectivity between motor and somatosensory systems is likely to facilitate motor imagery, which in turn is associated with the generation of a more pronounced modulation of sensorimotor oscillations (manifested in ERD/ERS) required for the adequate BCI performance. We also discuss strategies for the up-regulation of such connectivity in order to enhance BCI performance.

Details

show
hide
Language(s): eng - English
 Dates: 2020-06-222020-11-162020-12-18
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.3389/fnins.2020.575081
Other: eCollection 2020
PMID: 33390877
PMC: PMC7775663
 Degree: -

Event

show

Legal Case

show

Project information

show hide
Project name : -
Grant ID : RyC-2014-15671
Funding program : -
Funding organization : MINECO
Project name : -
Grant ID : 758985
Funding program : Horizon 2020
Funding organization : European Research Council (ERC)
Project name : Institute for Information & Communications Technology Promotion
Grant ID : 2017-0-00451
Funding program : -
Funding organization : Korea government
Project name : -
Grant ID : 01IS14013A-E, 01GQ1115, 01GQ0850, 01IS18025A, and 01IS18037A
Funding program : -
Funding organization : German Ministry for Education and Research (BMBF)
Project name : -
Grant ID : EXC 2046/1
Funding program : (390685689)
Funding organization : German ResearchFoundation (DFG)

Source 1

show
hide
Title: Frontiers in Neuroscience
  Other : Front Neurosci
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Lausanne, Switzerland : Frontiers Research Foundation
Pages: - Volume / Issue: 14 Sequence Number: 575081 Start / End Page: - Identifier: ISSN: 1662-4548
ISSN: 1662-453X
CoNE: https://pure.mpg.de/cone/journals/resource/1662-4548