Functional Corticomuscular Coupling Based on Bivariate Empirical Mode Decomposition - Multiscale Transfer Entropy

Shengcui Cheng, Xiaoling Chen, P. Xie, Xiaohui Pang, Xiaolin Bai
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Abstract

The functional corticomuscular coupling (FCMC) is a physiological phenomenon to reflect the multilayered characteristics of the information interaction between electroencephalogram (EEG) and electromyographic (EMG) signals. The multilayered characteristics such as local frequency band, complex and multiscale between the brain and muscles are of great significance to understand the cooperative function of the motor-sensory neural network. Though the multiscale transfer entropy (MSTE) method can effectively describe the multiscale and complex characteristics of the coupling signals to some extent, it fails to describe the FCMC on the local frequency band. Therefore, in this study, we combined the bivariate empirical mode decomposition (BEMD) with the MSTE to construct a new model, named bivariate empirical mode decomposition-multiscale transfer entropy (BMTE), to quantify the synchronous coupling between EEG and EMG signals on the local frequency band at different scales. The results show that the FCMC is significant in both EEG→EMG and EMG → EEG directions at betal and beta2 bands during steady-state grip task. Meanwhile, the maximum coupling strength value at beta2 band on different scales alomost occur on the high scales (9–16 scales), and the significant value at betal band was on the lower time scale. Additionally, the coupling strength at gamma band in EEG→ EMG direction is also significant in the higher scale. The results show that the BMTE method can quantitatively describe the local frequency band and multiscale characteristics between the motor cortex and the contralateral muscle in motor control system. This study extends the relative researches on the FCMC.
基于二元经验模态分解-多尺度传递熵的功能皮质-肌肉耦合
功能性皮质肌耦合(FCMC)是一种反映脑电图(EEG)和肌电图(EMG)信号之间多层次信息交互特征的生理现象。脑与肌肉之间的局部频带、复杂性和多尺度等多层特性对理解运动-感觉神经网络的协同功能具有重要意义。虽然多尺度传递熵(MSTE)方法能在一定程度上有效描述耦合信号的多尺度和复杂特性,但无法描述本频段上的FCMC。因此,本研究将二元经验模态分解(BEMD)与多尺度传递熵(MSTE)相结合,构建二元经验模态分解-多尺度传递熵(BMTE)模型,量化不同尺度下局部频段脑电与肌电信号之间的同步耦合。结果表明,在稳态握力任务中,FCMC在EEG→EMG和EMG→EEG方向上均具有显著性。同时,在不同尺度上,β 2波段的最大耦合强度值几乎出现在高尺度(9 ~ 16尺度),β 2波段的显著值出现在低时间尺度上。此外,在高尺度上,脑电→肌电方向γ波段的耦合强度也很显著。结果表明,BMTE方法可以定量描述运动控制系统中运动皮层与对侧肌肉之间的局部频带和多尺度特征。本研究是对FCMC相关研究的延伸。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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