脑-运动单元功能耦合估计方法

郑杨; 强威; 张四聪

doi:10.7652/xjtuxb202412011

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脑-运动单元功能耦合估计方法

—————————————————————— | 更新时间：2025-07-28

- 脑-运动单元功能耦合估计方法
- Estimation Method of Cortico-Motor Unit Coherence
- 西安交通大学学报 2024年58卷第12期页码：111-118
- 作者机构：
  
  1. 西安交通大学机械工程学院,西安,710049
  2. 西安交通大学精密微纳制造技术全国重点实验室,西安,710049
- 作者简介：
  
  : 2024-03-20。作者简介: 郑杨(1987—),男,副教授,博士生导师。基金项目: 科技创新2030资助项目(2022ZD0209800)
- 基金信息：
  
  : 2024-03-20。作者简介: 郑杨(1987—),男,副教授,博士生导师。基金项目: 科技创新2030资助项目(2022ZD0209800);陕西省重点研发计划资助项目(2022ZDLSF04-10);陕西省秦创原引用高层次创新创业人才资助项目(QCYRCXM-2022-34)。
- DOI：10.7652/xjtuxb202412011
  中图分类号： R318.04
- 网络首发：2024-12-10，
  
  纸质出版：2024
- 稿件说明：
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郑杨, 强威, 张四聪. 脑-运动单元功能耦合估计方法[J]. 西安交通大学学报, 2024,58(12):111-118.

ZHENG Yang, QIANG Wei, ZHANG Sicong. Estimation Method of Cortico-Motor Unit Coherence[J]. 2024, 58(12): 111-118.
郑杨, 强威, 张四聪. 脑-运动单元功能耦合估计方法[J]. 西安交通大学学报, 2024,58(12):111-118. DOI： 10.7652/xjtuxb202412011.

ZHENG Yang, QIANG Wei, ZHANG Sicong. Estimation Method of Cortico-Motor Unit Coherence[J]. 2024, 58(12): 111-118. DOI： 10.7652/xjtuxb202412011.

摘要

针对现有脑肌功能耦合(CMC)估计方法仅能反映皮层活动与运动单元(MU)复合放电活动间耦合状态、无法反映皮层和各MU独立耦合作用的问题

提出了一种脑与MU之间独立交互作用的估计方法

并初步验证了脑-运动单元功能耦合(CMUC)作用的存在。首先

采用肌电分解技术获得各MU独立活动

即运动单元动作电位序列; 然后

利用头皮表面拉普拉斯技术

获得头皮电流密度以表征皮层活动

并通过估计运动单元动作电位序列和头皮电流密度的频域相干性获得CMUC; 最后

通过手指伸展实验对所提方法的有效性加以验证。实验结果表明:当被试者伸展手指时

指伸肌的MU和对侧运动皮层存在显著的β、γ频带耦合交互作用

且耦合强度显著高于其他皮层区域。这一结论与已有的CMC研究结论相一致

能够表明所提CMUC估计方法的有效性

同时也证明了脑和MU独立耦合交互作用的存在性。提出的CMUC估计方法可为进一步深入研究生理及病理条件下肌肉的神经控制机制提供有力指导。

Abstract

Existing methods for estimating corticomuscular coherence(CMC)can only reflect the coherence between cortical activity and the compound firing activity of motor units(MUs)

without addressing the issue of independent coherence interactions between the cortex and individual MUs. In response to this

a method for estimating the independent interactions between the cortex and MUs is proposed

and the existence of cortico-motor unit coherence(CMUC)is preliminarily verified. Initially

electromyography decomposition techniques were used to obtain the independent activities of each MU

i.e.

the motor unit action potential train(MUAPT). Subsequently

scalp current density(SCD)is derived using the scalp surface Laplacian to characterize cortical activity

and CMUC is determined by estimating the frequency-domain coherence between MUAPT and SCD. Finally

the effectiveness of the proposed method is validated through finger extension experiments. The experimental results reveal that when subjects extend their fingers

the MUs of the finger extensor muscle and the contralateral motor cortex exhibited significant coherence interactions in the β and γ frequency bands. This coherence strength is notably higher than in other cortical regions. These findings align with previous research conclusions on CMC

demonstrating the effectiveness of the proposed CMUC estimation method and confirming the existence of independent coherence interactions between the cortex and MUs. The introduction of the CMUC estimation method can serve as a powerful tool for further investigating the neural control mechanisms of muscles under physiological and pathological conditions.

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references

LEMON R N. Descending pathways in motor control [J]. Annual Review of Neuroscience, 2008, 31: 195-218.

ROSENBERG J R, AMJAD A M, BREEZE P, et al. The Fourier approach to the identification of functional coupling between neuronal spike trains [J]. Progress in Biophysics and Molecular Biology, 1989, 53(1): 1-31.

KILNER J M, BAKER S N, SALENIUS S, et al. Human cortical muscle coherence is directly related to specific motor parameters [J]. Journal of Neuroscience, 2000, 20(23): 8838-8845.

BAKER S N, OLIVIER E, LEMON R N. Coherent oscillations in monkey motor cortex and hand muscle EMG show task-dependent modulation [J]. The Journal of Physiology, 1997, 501(1): 225-241.

ZHENG Yang, GAO Lin, WANG Gang, et al. The influence of unilateral contraction of hand muscles on the contralateral corticomuscular coherence during bimanual motor tasks [J]. Neuropsychologia, 2016, 85: 199-207.

郑杨, 王刚, 徐进, 等. 大脑皮层-肌肉交互作用与注意力关系的实验研究 [J]. 西安交通大学学报, 2014, 48(6): 134-138.

ZHENG Yang, WANG Gang, XU Jin, et al. Experimental research on relationship between attention and cortex-muscle interaction [J]. Journal of Xi'an Jiaotong University, 2014, 48(6): 134-138.

JOHNSON A N, WHEATON L A, SHINOHARA M. Attenuation of corticomuscular coherence with additional motor or non-motor task [J]. Clinical Neurophysiology, 2011, 122(2): 356-363.

KRISTEVA-FEIGE R, FRITSCH C, TIMMER J, et al. Effects of attention and precision of exerted force on beta range EEG-EMG synchronization during a maintained motor contraction task [J]. Clinical Neurophysiology, 2002, 113(1): 124-131.

JOHNSON A N, SHINOHARA M. Corticomuscular coherence with and without additional task in the elderly [J]. Journal of Applied Physiology, 2012, 112(6): 970-981.

KRAUTH R, SCHWERTNER J, VOGT S, et al. Cortico-muscular coherence is reduced acutely post-stroke and increases bilaterally during motor recovery: a pilot study [J]. Frontiers in Neurology, 2019, 10: 126.

ZHENG Yang, PENG Yu, XU Guanghua, et al. Using corticomuscular coherence to reflect function recovery of paretic upper limb after stroke: a case study [J]. Frontiers in Neurology, 2018, 8: 728.

CHEN Xiaoling, XIE Ping, ZHANG Yuanyuan, et al. Abnormal functional corticomuscular coupling after stroke [J]. NeuroImage: Clinical, 2018, 19: 147-159.

CHIANG J, WANG Z J, MCKEOWN M J. A multiblock PLS model of cortico-cortical and corticomuscular interactions in Parkinson's disease [J]. NeuroImage, 2012, 63(3): 1498-1509.

BERNHARD C G, BOHM E. Cortical representation and functional significance of the corticomotoneuronal system [J]. American Medical Association Archives of Neurology Psychiatry, 1954, 72(4): 473-502.

谢平, 陈迎亚, 张园园, 等. 基于Gabor小波和格兰杰因果的脑-肌电同步性分析 [J]. 中国生物医学工程学报, 2017, 36(1): 28-38.

XIE Ping, CHEN Yingya, ZHANG Yuanyuan, et al. EEG-EMG synchronization analysis based on Gabor wavelet transform-granger causality [J]. Chinese Journal of Biomedical Engineering, 2017, 36(1): 28-38.

谢平, 杨芳梅, 李欣欣, 等. 基于变分模态分解-传递熵的脑肌电信号耦合分析 [J]. 物理学报, 2016, 65(11): 118701.

XIE Ping, YANG Fangmei, LI Xinxin, et al. Functional coupling analyses of electroencephalogram and electromyogram based on variational mode decomposition-transfer entropy [J]. Acta Physica Sinica, 2016, 65(11): 118701.

CHEN Xiaoling, ZHANG Yuanyuan, CHENG Shengcui, et al. Transfer spectral entropy and application to functional corticomuscular coupling [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2019, 27(5): 1092-1102.[18] DE LUCA C J, ADAM A, WOTIZ R, et al. Decomposition of surface EMG signals [J]. Journal of Neurophysiology, 2006, 96(3): 1646-1657.

DAI Chenyun, HU Xiaogang. Independent component analysis based algorithms for high-density electromyogram decomposition: experimental evaluation of upper extremity muscles [J]. Computers in Biology and Medicine, 2019, 108: 42-48.

HYVÄRINEN A, OJA E. Independent component analysis: algorithms and applications [J]. Neural Networks, 2000, 13(4/5): 411-430.

NEGRO F, MUCELI S, CASTRONOVO A M, et al. Multi-channel intramuscular and surface EMG decomposition by convolutive blind source separation [J]. Journal of Neural Engineering, 2016, 13(2): 026027.

ARTHUR D, VASSILVITSKII S. K-means++: the advantages of careful seeding [C]//Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms. New Orleans, USA: Society for Industrial and Applied Mathematics, 2007: 1027-1035.

李怡欣, 郑杨. 用于运动单元活动追踪的动作电位卷积神经网络分类方法仿真研究 [J]. 西安交通大学学报, 2023, 57(6): 10-17.

LI Yixin, ZHENG Yang. Simulation study on CNN-Based motor unit action potential classification method for activity tracking of motor unit [J]. Journal of Xi'an Jiaotong University, 2023, 57(6): 10-17.

HU Xiaogang, RYMER W Z, SURESH N L. Motor unit pool organization examined via spike-triggered averaging of the surface electromyogram [J]. Journal of Neurophysiology, 2013, 110(5): 1205-1220.

CHEN Maoqi, ZHOU Ping. A novel framework based on FastICA for high density surface EMG decomposition [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2016, 24(1): 117-127.

PERRIN F, BERTRAND O, PERNIER J. Scalp current density mapping: value and estimation from potential data [J]. IEEE Transactions on Biomedical Engineering, 1987, 34(4): 283-288.

CHEN S, ENTAKLI J, BONNARD M, et al. Functional corticospinal projections from human supplementary motor area revealed by corticomuscular coherence during precise grip force control [J]. PLOS One, 2013, 8(3): e60291.

BROWN P, SALENIUS S, ROTHWELL J C, et al. Cortical correlate of the piper rhythm in humans [J]. Journal of Neurophysiology, 1998, 80(6): 2911-2917.

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