利用多通道脑电图和肌电图信号对精确抓握任务下的皮质肌肉功能耦合进行全球同步分析

IF 3.1 3区 工程技术 Q2 NEUROSCIENCES Cognitive Neurodynamics Pub Date : 2024-08-06 DOI:10.1007/s11571-024-10157-2
Xiaoling Chen, Tingting Shen, Yingying Hao, Jinyuan Zhang, Ping Xie
{"title":"利用多通道脑电图和肌电图信号对精确抓握任务下的皮质肌肉功能耦合进行全球同步分析","authors":"Xiaoling Chen, Tingting Shen, Yingying Hao, Jinyuan Zhang, Ping Xie","doi":"10.1007/s11571-024-10157-2","DOIUrl":null,"url":null,"abstract":"<p>Functional corticomuscular coupling (FCMC), a phenomenon describing the information interaction between the cortex and muscles, plays an important role in assessing hand movements. However, related studies mainly focused on specific actions by one-to-one mapping between the brain and muscles, ignoring the global synchronization across the motor system. Little research has been done on the FCMC difference between the brain and different muscle groups in terms of precise grip tasks. This study combined the maximum information coefficient (MIC) and the S estimation method and constructed a multivariate global synchronization index (MGSI) to measure the FCMC by analyzing the multichannel electroencephalogram (EEG) and electromyogram (EMG) during precise grip tasks. Both signals were collected from 12 healthy subjects while performing different weight object tasks. Our results on Hilbert-Huang spectral entropy (HHSE) of signals showed differences in task stages in both<i> β</i> (13–30 Hz) and <i>γ</i> (31–45 Hz) bands. The weight difference was reflected in the HHSE of channel CP5 and muscles at both ends of the upper limb. The one-to-one mapping with MIC between EEG and the muscle pair AD-FDI showed larger MIC values than the muscle pair B-CED; the same trend was seen on the MGSI values. However, the difference in weight of static tasks was not significant. Both MGSI values and the connect ratio of EEG were related to HHSE values. This work investigated the changes in the cortex and muscles during precise grip tasks from different perspectives, contributing to a better understanding of human motor control.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"29 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Global synchronization of functional corticomuscular coupling under precise grip tasks using multichannel EEG and EMG signals\",\"authors\":\"Xiaoling Chen, Tingting Shen, Yingying Hao, Jinyuan Zhang, Ping Xie\",\"doi\":\"10.1007/s11571-024-10157-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Functional corticomuscular coupling (FCMC), a phenomenon describing the information interaction between the cortex and muscles, plays an important role in assessing hand movements. However, related studies mainly focused on specific actions by one-to-one mapping between the brain and muscles, ignoring the global synchronization across the motor system. Little research has been done on the FCMC difference between the brain and different muscle groups in terms of precise grip tasks. This study combined the maximum information coefficient (MIC) and the S estimation method and constructed a multivariate global synchronization index (MGSI) to measure the FCMC by analyzing the multichannel electroencephalogram (EEG) and electromyogram (EMG) during precise grip tasks. Both signals were collected from 12 healthy subjects while performing different weight object tasks. Our results on Hilbert-Huang spectral entropy (HHSE) of signals showed differences in task stages in both<i> β</i> (13–30 Hz) and <i>γ</i> (31–45 Hz) bands. The weight difference was reflected in the HHSE of channel CP5 and muscles at both ends of the upper limb. The one-to-one mapping with MIC between EEG and the muscle pair AD-FDI showed larger MIC values than the muscle pair B-CED; the same trend was seen on the MGSI values. However, the difference in weight of static tasks was not significant. Both MGSI values and the connect ratio of EEG were related to HHSE values. This work investigated the changes in the cortex and muscles during precise grip tasks from different perspectives, contributing to a better understanding of human motor control.</p>\",\"PeriodicalId\":10500,\"journal\":{\"name\":\"Cognitive Neurodynamics\",\"volume\":\"29 1\",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-08-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Neurodynamics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s11571-024-10157-2\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Neurodynamics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s11571-024-10157-2","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

功能性皮质肌肉耦合(FCMC)是一种描述大脑皮层与肌肉之间信息交互的现象,在评估手部运动中发挥着重要作用。然而,相关研究主要通过大脑和肌肉之间一对一的映射来关注特定动作,而忽略了整个运动系统的全局同步性。在精确握力任务方面,有关大脑与不同肌肉群之间的 FCMC 差异的研究还很少。本研究结合最大信息系数(MIC)和 S 估计法,通过分析精确抓握任务中的多通道脑电图(EEG)和肌电图(EMG),构建了多变量全局同步指数(MGSI)来测量 FCMC。这两个信号都是在 12 名健康受试者执行不同重量物体任务时采集的。我们对信号的希尔伯特-黄频谱熵(HHSE)的研究结果表明,在任务阶段,β(13-30 Hz)和γ(31-45 Hz)频段的信号存在差异。重量差异反映在 CP5 频道和上肢两端肌肉的 HHSE 上。EEG 与肌肉对 AD-FDI 之间的一对一 MIC 映射显示,MIC 值大于肌肉对 B-CED;MGSI 值也有同样的趋势。然而,静态任务的权重差异并不显著。MGSI 值和脑电图的连接比都与 HHSE 值有关。这项工作从不同角度研究了精确抓握任务过程中大脑皮层和肌肉的变化,有助于更好地理解人类的运动控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Global synchronization of functional corticomuscular coupling under precise grip tasks using multichannel EEG and EMG signals

Functional corticomuscular coupling (FCMC), a phenomenon describing the information interaction between the cortex and muscles, plays an important role in assessing hand movements. However, related studies mainly focused on specific actions by one-to-one mapping between the brain and muscles, ignoring the global synchronization across the motor system. Little research has been done on the FCMC difference between the brain and different muscle groups in terms of precise grip tasks. This study combined the maximum information coefficient (MIC) and the S estimation method and constructed a multivariate global synchronization index (MGSI) to measure the FCMC by analyzing the multichannel electroencephalogram (EEG) and electromyogram (EMG) during precise grip tasks. Both signals were collected from 12 healthy subjects while performing different weight object tasks. Our results on Hilbert-Huang spectral entropy (HHSE) of signals showed differences in task stages in both β (13–30 Hz) and γ (31–45 Hz) bands. The weight difference was reflected in the HHSE of channel CP5 and muscles at both ends of the upper limb. The one-to-one mapping with MIC between EEG and the muscle pair AD-FDI showed larger MIC values than the muscle pair B-CED; the same trend was seen on the MGSI values. However, the difference in weight of static tasks was not significant. Both MGSI values and the connect ratio of EEG were related to HHSE values. This work investigated the changes in the cortex and muscles during precise grip tasks from different perspectives, contributing to a better understanding of human motor control.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Cognitive Neurodynamics
Cognitive Neurodynamics 医学-神经科学
CiteScore
6.90
自引率
18.90%
发文量
140
审稿时长
12 months
期刊介绍: Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models. The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome. The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged. 1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics. 2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages. 3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.
期刊最新文献
A memristor-based circuit design of avoidance learning with time delay and its application Perceptual information processing in table tennis players: based on top-down hierarchical predictive coding EEG-based deception detection using weighted dual perspective visibility graph analysis The dynamical behavior effects of different numbers of discrete memristive synaptic coupled neurons Advancements in automated diagnosis of autism spectrum disorder through deep learning and resting-state functional mri biomarkers: a systematic review
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1