Corticomuscular Coherence Based on Wavelet Transform During Imagination, Execution and Stimulation Tasks

Xu, Rui; He, Feng; Qiu, Shuang; Chen, Long; Liu, Shuang; Zhao, Xinyi; Qi, Hongzhi; Zhang, Lixin; Wan, Baikun; Ming, Dong

doi:10.1166/jmihi.2015.1397

Cited by 3 publications

(4 citation statements)

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“…Coherence similarities between cortical activities occurred during the imaginary neuromuscular activities [3,25,26]. Nevertheless, there was very low coherence in the MI and OL tasks, except for some subjects in the OL task.…”

Section: Eeg-emg Functional Coupling Analysis Using Linear Coherencementioning

confidence: 99%

Electroencephalogram-Electromyogram Functional Coupling and Delay Time Change Based on Motor Task Performance

Tun

Sanuki

Iramina

2021

Sensors

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Synchronous correlation brain and muscle oscillations during motor task execution is termed as functional coupling. Functional coupling between two signals appears with a delay time which can be used to infer the directionality of information flow. Functional coupling of brain and muscle depends on the type of muscle contraction and motor task performance. Although there have been many studies of functional coupling with types of muscle contraction and force level, there has been a lack of investigation with various motor task performances. Motor task types play an essential role that can reflect the amount of functional interaction. Thus, we examined functional coupling under four different motor tasks: real movement, intention, motor imagery and movement observation tasks. We explored interaction of two signals with linear and nonlinear information flow. The aim of this study is to investigate the synchronization between brain and muscle signals in terms of functional coupling and delay time. The results proved that brain–muscle functional coupling and delay time change according to motor tasks. Quick synchronization of localized cortical activity and motor unit firing causes good functional coupling and this can lead to short delay time to oscillate between signals. Signals can flow with bidirectionality between efferent and afferent pathways.

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Section: Eeg-emg Functional Coupling Analysis Using Linear Coherencementioning

confidence: 99%

Electroencephalogram-Electromyogram Functional Coupling and Delay Time Change Based on Motor Task Performance

Tun

Sanuki

Iramina

2021

Sensors

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“…Equation (1) and equation (2) offer a basic and intuitive technique to display the synchronous values. On this basis, wavelet-based coherence is proposed to enhance the relative level of the motor cortex and muscle and observes the coherence in time-frequency domain which estimates the signal spectral characteristics according to the function of time ( Xu et al, 2015 ). To overcome the problems of non-stationary signals like sEMG signal, wavelet analysis is a rational method to analyze signals with fast-changing spectra ( Lachaux et al, 2002 ).…”

Section: Cmc Definition and Formulaementioning

confidence: 99%

Corticomuscular Coherence and Its Applications: A Review

Liu

Sheng

Liu

2019

Front. Hum. Neurosci.

110

100

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Corticomuscular coherence (CMC) is an index utilized to indicate coherence between brain motor cortex and associated body muscles, conventionally. As an index of functional connections between the cortex and muscles, CMC research is the focus of neurophysiology in recent years. Although CMC has been extensively studied in healthy subjects and sports disorders, the purpose of its applications is still ambiguous, and the magnitude of CMC varies among individuals. Here, we aim to investigate factors that modulate the variation of CMC amplitude and compare significant CMC between these factors to find a well-developed research prospect. In the present review, we discuss the mechanism of CMC and propose a general definition of CMC. Factors affecting CMC are also summarized as follows: experimental design, band frequencies and force levels, age correlation, and difference between healthy controls and patients. In addition, we provide a detailed overview of the current CMC applications for various motor disorders. Further recognition of the factors affecting CMC amplitude can clarify the physiological mechanism and is beneficial to the implementation of CMC clinical methods.

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“…The next concern with correlation is that coherence can occur in the beta band during static movement and in the gamma band during dynamic performance [3], [10]. Some published papers concluded coherence which occurred during movement execution and motor imagery might contain overlapping neural networks in perirolandic cortical areas [3], [11]. Coherence can be detected during motor imagery condition [11].…”

Section: Introducionmentioning

confidence: 99%

“…Some published papers concluded coherence which occurred during movement execution and motor imagery might contain overlapping neural networks in perirolandic cortical areas [3], [11]. Coherence can be detected during motor imagery condition [11]. However, there were controversial topics related to coherence in motor imagery conditions.…”

Section: Introducionmentioning

confidence: 99%

EEG-EMG Correlation Analysis with Linear and Nonlinear Coupling Methods Across Four Motor Tasks

Tun

Sanuki

Iramina

2021

2021 43rd Annual International Conference of the IEEE Engineering in Medicine &Amp; Biology Society (EMBC)

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Correlation between brain and muscle signal is referred to as functional coupling. The amount of correlation between two signals greatly depends on the motor task performance. In this study, we designed the experimental paradigm with four types of motor tasks such as real hand grasping movement (RM), movement intention (Inten), motor imagery (MI) and only looking at virtual hand in three dimensional head mounted display (OL). We aimed to investigate EEG-EMG correlation with linear and nonlinear coupling methods. The results proved that high correlation could be occurred in RM and Inten tasks rather than MI and OL tasks in both linear and nonlinear methods. High coherence occurred in beta and gamma bands of RM and Inten tasks whereas no coherence was detected in MI and OL tasks. In terms of nonlinear correlation, the high mutual information was detected in RM and Inten tasks. There was slight mutual information in MI and OL tasks. The results showed that the coherence in the contralateral brain cortex was higher than in the ipsilateral motor cortex during motor tasks. Furthermore, the amount of EEG-EMG functional coupling changed according to the motor task executed.

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Corticomuscular Coherence Based on Wavelet Transform During Imagination, Execution and Stimulation Tasks

Cited by 3 publications

References 0 publications

Electroencephalogram-Electromyogram Functional Coupling and Delay Time Change Based on Motor Task Performance

Electroencephalogram-Electromyogram Functional Coupling and Delay Time Change Based on Motor Task Performance

Corticomuscular Coherence and Its Applications: A Review

EEG-EMG Correlation Analysis with Linear and Nonlinear Coupling Methods Across Four Motor Tasks

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