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Delay estimation for cortical-muscular interaction with wavelet coherence time lag.

Authors :
Wang, Ting
Xia, Mingze
Wang, Junhong
Zhilenkov, Anton
Wang, Jian
Xi, Xugang
Li, Lihua
Source :
Journal of Neuroscience Methods. May2024, Vol. 405, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Cortico-muscular coherence (CMC) between the cerebral cortex and muscle activity is an effective tool for studying neural communication in the motor control system. To accurately evaluate the coherence between electroencephalogram (EEG) and electromyogram (EMG) signals, it is necessary to accurately calculate the time delay between physiological signals to ensure signal synchronization. We proposed a new delay estimation method, named wavelet coherence time lag (WCTL) and the significant increase areas (SIA) index as a measure of the specific region enhancement effect of the magnitude squared coherence (MSC) image. The grip strength level had a small effect on the information transmission time from the cortex to the muscles, while the transmission time from the cortex to different muscle channels was different for the same task. A positive correlation was found between the grip strength level and the SIA index on the β band of C3-B and the α and β bands of C3-FDS. Comparison with Existing Method: The WCTL method was found to accurately calculate the delay time even when the number of repeated segments was low in a simple motor control model, and the results were more accurate than the rate of voxels change (RVC) and CMC with time lag (CMCTL) methods. The WCTL is an effective method for detecting the transmission time of information between the cortex and muscles, laying the foundation for future rehabilitation treatment for stroke patients. • A new way to detect time delays between two physiological signals. • Repeated segments was low and accurately calculate. • The grip strength level effect on transmission time from the cortex to the muscles. • The index reflects significant improvements in grip strength levels. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01650270
Volume :
405
Database :
Academic Search Index
Journal :
Journal of Neuroscience Methods
Publication Type :
Academic Journal
Accession number :
176356384
Full Text :
https://doi.org/10.1016/j.jneumeth.2024.110098