Analysis of corticomuscular connectivity during walking using vine copula

Xiebing Chen; Yuliang Ma; Xiaoyun Liu; Wanzeng Kong; Xugang Xi; Xiebing Chen; Yuliang Ma; Xiaoyun Liu; Wanzeng Kong; Xugang Xi

doi:10.3934/mbe.2021218

Mathematical Biosciences and Engineering

2021, Volume 18, Issue 4: 4341-4357. doi: 10.3934/mbe.2021218

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Analysis of corticomuscular connectivity during walking using vine copula

1.
School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
2.
Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 310018, China

Received: 16 January 2021 Accepted: 26 April 2021 Published: 18 May 2021

Corticomuscular connectivity plays an important role in the neural control of human motion. This study recorded electroencephalography (EEG) and surface electromyography (sEMG) signals from subjects performing specific tasks (walking on level ground and on stairs) based on metronome instructions. This study presents a novel method based on vine copula to jointly model EEG and sEMG signals. The advantage of vine copula is its applicability in the construction of dependency structures to describe the connectivity between the cortex and muscles during different movements. A corticomuscular function network was also constructed by analyzing the dependence of each channel sample. The successfully constructed network shows information transmission between different divisions of the cortex, between muscles, and between the cortex and muscles when the body performs lower limb movements. Additionally, it highlights the potential of the vine copula concept used in this study, indicating that significant changes in the corticomuscular network under lower limb movements can be quantified by effective connectivity values.
- corticomuscular connectivity,
- electroencephalography,
- electromyography, vine copula
Citation: Xiebing Chen, Yuliang Ma, Xiaoyun Liu, Wanzeng Kong, Xugang Xi. Analysis of corticomuscular connectivity during walking using vine copula[J]. Mathematical Biosciences and Engineering, 2021, 18(4): 4341-4357. doi: 10.3934/mbe.2021218

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Abstract

Corticomuscular connectivity plays an important role in the neural control of human motion. This study recorded electroencephalography (EEG) and surface electromyography (sEMG) signals from subjects performing specific tasks (walking on level ground and on stairs) based on metronome instructions. This study presents a novel method based on vine copula to jointly model EEG and sEMG signals. The advantage of vine copula is its applicability in the construction of dependency structures to describe the connectivity between the cortex and muscles during different movements. A corticomuscular function network was also constructed by analyzing the dependence of each channel sample. The successfully constructed network shows information transmission between different divisions of the cortex, between muscles, and between the cortex and muscles when the body performs lower limb movements. Additionally, it highlights the potential of the vine copula concept used in this study, indicating that significant changes in the corticomuscular network under lower limb movements can be quantified by effective connectivity values.

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