Coherence of the Surface EMG and Common Synaptic Input to Motor Neurons

Coherence between electromyographic (EMG) signals is often used to infer the common synaptic input to populations of motor neurons. This analysis, however, may be limited due to the filtering effect of the motor unit action potential waveforms. This study investigated the ability of surface EMG–EMG...

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Main Authors: Jakob L. Dideriksen, Francesco Negro, Deborah Falla, Signe R. Kristensen, Natalie Mrachacz-Kersting, Dario Farina
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-06-01
Series:Frontiers in Human Neuroscience
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fnhum.2018.00207/full
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spelling doaj-e0a9751c593b4f398dbc827c6c10ff322020-11-25T02:39:17ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612018-06-011210.3389/fnhum.2018.00207329175Coherence of the Surface EMG and Common Synaptic Input to Motor NeuronsJakob L. Dideriksen0Francesco Negro1Deborah Falla2Signe R. Kristensen3Natalie Mrachacz-Kersting4Dario Farina5Center for Sensory-Motor Interaction, Department of Health Science and Technology, Aalborg University, Aalborg, DenmarkDepartment of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, ItalyCentre of Precision Rehabilitation for Spinal Pain, School of Sport, Exercise, and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Birmingham, United KingdomCenter for Sensory-Motor Interaction, Department of Health Science and Technology, Aalborg University, Aalborg, DenmarkCenter for Sensory-Motor Interaction, Department of Health Science and Technology, Aalborg University, Aalborg, DenmarkDepartment of Bioengineering, Imperial College London, London, United KingdomCoherence between electromyographic (EMG) signals is often used to infer the common synaptic input to populations of motor neurons. This analysis, however, may be limited due to the filtering effect of the motor unit action potential waveforms. This study investigated the ability of surface EMG–EMG coherence to predict common synaptic input to motor neurons. Surface and intramuscular EMG were recorded from two locations of the tibialis anterior muscle during steady ankle dorsiflexions at 5 and 10% of the maximal force in 10 healthy individuals. The intramuscular EMG signals were decomposed to identify single motor unit spike trains. For each trial, the strength of the common input in different frequency bands was estimated from the coherence between two cumulative spike trains, generated from sets of single motor unit spike trains (reference measure). These coherence values were compared with those obtained from the coherence between the surface EMG signals (raw, rectified, and high-passed filtered at 250 Hz before rectification) using linear regression. Overall, the high-pass filtering of the EMG prior to rectification did not substantially change the results with respect to rectification only. For both signals, the correlation of EMG coherence with motor unit coherence was strong at 5% MVC (r2 > 0.8; p < 0.01), but only for frequencies > 5 Hz. At 10% MVC, the correlation between EMG and motor unit coherence was only significant for frequencies > 15 Hz (r2 > 0.8; p < 0.01). However, when using raw EMG for coherence analysis, the only significant relation with motor unit coherence was observed for the bandwidth 5–15 Hz (r2 > 0.68; p = 0.04). In all cases, there was no association between motor unit and EMG coherence for frequencies < 5 Hz (r2 ≤ 0.2; p ≥ 0.51). In addition, a substantial error in the best linear fit between motor unit and EMG coherence was always present. In conclusion, high-frequency (>5 Hz) common synaptic inputs to motor neurons can partly be estimated from the rectified surface EMG at low-level steady contractions. The results, however, suggest that this association is weakened with increasing contraction intensity and that input at lower frequencies during steady isometric contractions cannot be detected accurately by surface EMG coherence.https://www.frontiersin.org/article/10.3389/fnhum.2018.00207/fullcoherencemotor controlmotor unitsurface EMGsynaptic input
collection DOAJ
language English
format Article
sources DOAJ
author Jakob L. Dideriksen
Francesco Negro
Deborah Falla
Signe R. Kristensen
Natalie Mrachacz-Kersting
Dario Farina
spellingShingle Jakob L. Dideriksen
Francesco Negro
Deborah Falla
Signe R. Kristensen
Natalie Mrachacz-Kersting
Dario Farina
Coherence of the Surface EMG and Common Synaptic Input to Motor Neurons
Frontiers in Human Neuroscience
coherence
motor control
motor unit
surface EMG
synaptic input
author_facet Jakob L. Dideriksen
Francesco Negro
Deborah Falla
Signe R. Kristensen
Natalie Mrachacz-Kersting
Dario Farina
author_sort Jakob L. Dideriksen
title Coherence of the Surface EMG and Common Synaptic Input to Motor Neurons
title_short Coherence of the Surface EMG and Common Synaptic Input to Motor Neurons
title_full Coherence of the Surface EMG and Common Synaptic Input to Motor Neurons
title_fullStr Coherence of the Surface EMG and Common Synaptic Input to Motor Neurons
title_full_unstemmed Coherence of the Surface EMG and Common Synaptic Input to Motor Neurons
title_sort coherence of the surface emg and common synaptic input to motor neurons
publisher Frontiers Media S.A.
series Frontiers in Human Neuroscience
issn 1662-5161
publishDate 2018-06-01
description Coherence between electromyographic (EMG) signals is often used to infer the common synaptic input to populations of motor neurons. This analysis, however, may be limited due to the filtering effect of the motor unit action potential waveforms. This study investigated the ability of surface EMG–EMG coherence to predict common synaptic input to motor neurons. Surface and intramuscular EMG were recorded from two locations of the tibialis anterior muscle during steady ankle dorsiflexions at 5 and 10% of the maximal force in 10 healthy individuals. The intramuscular EMG signals were decomposed to identify single motor unit spike trains. For each trial, the strength of the common input in different frequency bands was estimated from the coherence between two cumulative spike trains, generated from sets of single motor unit spike trains (reference measure). These coherence values were compared with those obtained from the coherence between the surface EMG signals (raw, rectified, and high-passed filtered at 250 Hz before rectification) using linear regression. Overall, the high-pass filtering of the EMG prior to rectification did not substantially change the results with respect to rectification only. For both signals, the correlation of EMG coherence with motor unit coherence was strong at 5% MVC (r2 > 0.8; p < 0.01), but only for frequencies > 5 Hz. At 10% MVC, the correlation between EMG and motor unit coherence was only significant for frequencies > 15 Hz (r2 > 0.8; p < 0.01). However, when using raw EMG for coherence analysis, the only significant relation with motor unit coherence was observed for the bandwidth 5–15 Hz (r2 > 0.68; p = 0.04). In all cases, there was no association between motor unit and EMG coherence for frequencies < 5 Hz (r2 ≤ 0.2; p ≥ 0.51). In addition, a substantial error in the best linear fit between motor unit and EMG coherence was always present. In conclusion, high-frequency (>5 Hz) common synaptic inputs to motor neurons can partly be estimated from the rectified surface EMG at low-level steady contractions. The results, however, suggest that this association is weakened with increasing contraction intensity and that input at lower frequencies during steady isometric contractions cannot be detected accurately by surface EMG coherence.
topic coherence
motor control
motor unit
surface EMG
synaptic input
url https://www.frontiersin.org/article/10.3389/fnhum.2018.00207/full
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AT deborahfalla coherenceofthesurfaceemgandcommonsynapticinputtomotorneurons
AT signerkristensen coherenceofthesurfaceemgandcommonsynapticinputtomotorneurons
AT nataliemrachaczkersting coherenceofthesurfaceemgandcommonsynapticinputtomotorneurons
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