Novel Insights Into Biarticular Muscle Actions Gained From High-Density Electromyogram

Watanabe, Kohei; Vieira, Taian; Gallina, Alessio; Kouzaki, Motoki; Moritani, Toshio

doi:10.1249/jes.0000000000000254

Cited by 26 publications

(22 citation statements)

References 87 publications

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“…Some realistic aspects of the MN neurophysiology are also maintained. For example, the range of MN surface areas [0.15; 0.36]𝑚𝑚 2 and input resistances [0.5; 4.1]𝑀Ω obtained from the 𝑆(𝑗) distribution falls into the classic range of MN properties for cats [21,42], which is consistent with the distribution of rheobase values used in…”

Section: Application To Mn-driven Modellingsupporting

confidence: 73%

“…During voluntary muscle contractions, pools of spinal alpha-motoneurons (MNs) convert the synaptic input they receive into a neural command that drives the contractile activity of the innervated muscle fibres, determining limb motion. Identifying the recruitment and firing dynamics of MNs is fundamental for understanding the neural strategies controlling human voluntary motion, with applications in sport sciences (Felici & Del Vecchio, 2020; Watanabe, K. et al, 2021; Maeda et al, 2021), and neurological and musculoskeletal rehabilitation (Jordanić et al, 2016; Fang et al, 2020; Pilkar et al, 2020; Kisiel-Sajewicz et al, 2020; Nishikawa et al, 2021). Determining the MN-specific contributions to the MN population activity also allows more realistic control of neuromuscular models (Callahan et al, 2013; Potvin & Fuglevand, 2017; Kim & Kim, 2018; Carriou et al, 2019), investigation of muscle neuromechanics (Waasdorp et al, 2021; Martinez-Valdes et al, 2021), prediction of limb motion from MN-specific behaviour (Chen et al, 2020), or improvement in human-machine interfacing and neuroprosthetics (Farina et al, 2017; Farina et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…For all four datasets, the 𝑟2 and 𝑛𝑅𝑀𝑆𝐸 values obtained for the comparison of the time-histories of the normalized experimental force trace against the effective neural drive (1) 𝑒𝑁𝐷 𝑁 𝑟 and (2) 𝑒𝑁𝐷 𝑁 computed from the spike trains of(1) the 𝑁 𝑟 identified MNs and (2) the 𝑁 virtual MNs. The results for 𝐻𝑇𝐴 50(1) were obtained with the standard approach, while those for 𝐻𝑇𝐴 50(2) were obtained with a revisited 𝐼𝑃(𝑗) distribution (see text).…”

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confidence: 99%

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Estimation of the firing behaviour of a complete motoneuron pool by combining electromyography signal decomposition and realistic motoneuron modelling

Caillet

Phillips

Farina

et al. 2022

Preprint

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Our understanding of the firing behaviour of motoneuron (MN) pools during human voluntary muscle contractions is currently limited to electrophysiological findings from animal experiments extrapolated to humans, mathematical models of MN pools not validated for human data, and experimental results obtained from EMG decomposition. These approaches are limited in accuracy or provide information on only small partitions of the MN population. Here, we propose a method based on the combination of high-density EMG (HDEMG) data and realistic modelling for predicting the behaviour of entire pools of motoneurons in humans. The method builds on a physiologically realistic model of a MN pool which predicts, from the experimental spike trains of a smaller number of individual MNs identified from decomposed HDEMG signals, the unknown recruitment and firing activity of the remaining unidentified MNs in the complete MN pool. The MN pool model is described as a cohort of leaky fire- and-integrate (LIF) models of MNs scaled by a physiologically realistic distribution of MN electrophysiological properties and driven by a spinal synaptic input, both derived from decomposed HDEMG data. The MN spike trains and effective neural drive to muscle, predicted with this method, have been successfully validated experimentally. Representative applications of the method are also presented for the prediction of activity-dependant changes in MN intrinsic properties and in MN-driven neuromuscular modelling. The proposed approach provides a validated tool for neuroscientists, experimentalists, and modelers to infer the firing activity of MNs that cannot be observed experimentally, investigate the neurophysiology of human MN pools, support future experimental investigations, and advance neuromuscular modelling for investigating the neural strategies controlling human voluntary contractions.Author SummaryOur experimental understanding of the firing behaviour of motoneuron (MN) pools during human voluntary muscle contractions is currently limited to the observation of small samples of active MNs obtained from EMG decomposition. EMG decomposition therefore provides an important but incomplete description of the role of individual MNs in the firing activity of the complete MN pool, which limits our understanding of the neural strategies of the whole MN pool and of how the firing activity of each MN contributes to the neural drive to muscle. Here, we combine decomposed high-density EMG (HDEMG) data and a physiologically realistic model of MN population to predict the unknown recruitment and firing activity of the remaining unidentified MNs in the complete MN pool. In brief, an experimental estimation of the synaptic current is input to a cohort of MN models, which are calibrated using the available decomposed HDEMG data, and predict the MN spike trains fired by the entire MN population. This novel approach is experimentally validated and applied to muscle force prediction from neuromuscular modelling, and to investigate neurophysiological properties of the human MN population during voluntary contractions.

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Section: Application To Mn-driven Modellingsupporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Estimation of the firing behaviour of a complete motoneuron pool by combining electromyography signal decomposition and realistic motoneuron modelling

Caillet

Phillips

Farina

et al. 2022

Preprint

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“…Furthermore, since surface EMGs were collected with a single pair of electrodes positioned at a given point of interest in the skin, we cannot exclude that excitation of deep fibers in the target muscles was not properly sampled ( Vigotsky et al, 2018 ) ( Watanabe et al, 2021 ) ( Vigotsky et al, 2022 ), leading to type II error ( Vieira and Botter, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Not all Forms of Muscle Hypertonia Worsen With Fatigue: A Pilot Study in Para Swimmers

et al. 2022

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In hypertonic muscles of patients with upper motor neuron syndrome (UMNS), investigation with surface electromyography (EMG) with the muscle in a shortened position and during passive muscle stretch allows to identify two patterns underlying hypertonia: spasticity and spastic dystonia. We recently observed in Para swimmers that the effect of fatigue on hypertonia can be different from subject to subject. Our goal was, therefore, to understand whether this divergent behavior may depend on the specific EMG pattern underlying hypertonia. We investigated eight UMNS Para swimmers (five men, mean age 23.25 ± 3.28 years), affected by cerebral palsy, who presented muscle hypertonia of knee flexors and extensors. Muscle tone was rated using the Modified Ashworth Scale (MAS). EMG patterns were investigated in rectus femoris (RF) and biceps femoris (BF) before and after two fatiguing motor tasks of increasing intensity. Before the fatiguing tasks, two subjects (#2 and 7) had spasticity and one subject (#5) had spastic dystonia in both RF and BF. Two subjects (#3 and 4) showed spasticity in RF and spastic dystonia in BF, whereas one subject (#1) had spasticity in RF and no EMG activity in BF. The remaining two subjects (#6 and 8) had spastic dystonia in RF and no EMG activity in BF. In all the 16 examined muscles, these EMG patterns persisted after the fatiguing tasks. Spastic dystonia increased (p < 0.05), while spasticity did not change (p > 0.05). MAS scores increased only in the muscles affected by spastic dystonia. Among the phenomena possibly underlying hypertonia, only spastic dystonia is fatigue-dependent. Technical staff and medical classifiers should be aware of this specificity, because, in athletes with spastic dystonia, intense and prolonged motor activity could negatively affect competitive performance, creating a situation of unfairness among Para athletes belonging to the same sports class.

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Effect of ankle weight loading and walking speed on metabolic and neuromuscular responses and lower limb kinematics during treadmill walking

2023

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Novel Insights Into Biarticular Muscle Actions Gained From High-Density Electromyogram

Abstract: Human biarticular muscles are regionally activated for different functional roles, and this should be considered when recording surface electromyography.

Cited by 26 publications

References 87 publications

Estimation of the firing behaviour of a complete motoneuron pool by combining electromyography signal decomposition and realistic motoneuron modelling

Estimation of the firing behaviour of a complete motoneuron pool by combining electromyography signal decomposition and realistic motoneuron modelling

Not all Forms of Muscle Hypertonia Worsen With Fatigue: A Pilot Study in Para Swimmers

Effect of ankle weight loading and walking speed on metabolic and neuromuscular responses and lower limb kinematics during treadmill walking

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