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Neurofeedback Training of Alpha Relative Power Improves the Performance of Motor Imagery Brain-Computer Interface

Authors :
Qing Zhou
Ruidong Cheng
Lin Yao
Xiangming Ye
Kedi Xu
Source :
Frontiers in Human Neuroscience, Vol 16 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

Significant variation in performance in motor imagery (MI) tasks impedes their wide adoption for brain-computer interface (BCI) applications. Previous researchers have found that resting-state alpha-band power is positively correlated with MI-BCI performance. In this study, we designed a neurofeedback training (NFT) protocol based on the up-regulation of the alpha band relative power (RP) to investigate its effect on MI-BCI performance. The principal finding of this study is that alpha NFT could successfully help subjects increase alpha-rhythm power and improve their MI-BCI performance. An individual difference was also found in this study in that subjects who increased alpha power more had a better performance improvement. Additionally, the functional connectivity (FC) of the frontal-parietal (FP) network was found to be enhanced after alpha NFT. However, the enhancement failed to reach a significant level after multiple comparisons correction. These findings contribute to a better understanding of the neurophysiological mechanism of cognitive control through alpha regulation.

Details

Language :
English
ISSN :
16625161
Volume :
16
Database :
Directory of Open Access Journals
Journal :
Frontiers in Human Neuroscience
Publication Type :
Academic Journal
Accession number :
edsdoj.f566425b4f7464e90a7b605e6be1a7c
Document Type :
article
Full Text :
https://doi.org/10.3389/fnhum.2022.831995