Publications by authors named "Francois Hug"

Movements are performed by motoneurons transforming synaptic inputs into an activation signal that controls muscle force. The control signal emerges from interactions between ionotropic and neuromodulatory inputs to motoneurons. Critically, these interactions vary across motoneuron pools and differ between muscles.

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Skeletal muscles change shape when they contract. Current insights into the effects of shape change on muscle function have primarily come from experiments on isolated muscles operating at maximal activation levels. However, when muscles contract and change shape, the forces they apply onto surrounding muscles will also change.

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Decoding the activity of individual neural cells during natural behaviours allows neuroscientists to study how the nervous system generates and controls movements. Contrary to other neural cells, the activity of spinal motor neurons can be determined non-invasively (or minimally invasively) from the decomposition of electromyographic (EMG) signals into motor unit firing activities. For some interfacing and neuro-feedback investigations, EMG decomposition needs to be performed in real time.

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Article Synopsis
  • Skeletal muscles are vital for movement, and understanding how to estimate the forces they produce is essential in fields like biomechanics, robotics, and rehabilitation.
  • Direct measurement of muscle force in humans is invasive, so non-invasive methods like electromyography (EMG) are used for estimation, and a matrix developed by CEDE provides guidelines on EMG applications.
  • The matrix suggests EMG methods for identifying muscle force during isometric and dynamic contractions, while emphasizing the importance of considering various factors to improve accuracy in estimating muscle forces, fostering interdisciplinary discussions to enhance muscle modeling techniques.
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The implementation of low-dimensional movement control by the central nervous system has been debated for decades. In this study, we investigated the dimensionality of the control signals received by spinal motor neurons when controlling either the ankle or knee joint torque. We first identified the low-dimensional latent factors underlying motor unit activity during torque-matched isometric contractions in male participants.

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Purpose: To assess the effect of a remote handgrip contraction during wide-pulse high-frequency (WPHF) neuromuscular electrical stimulation (NMES) on the magnitude of extra torque, progressive increase in torque during stimulation, and estimates of the persistent inward current (PIC) contribution to motoneuron firing in the plantar flexors.

Methods: Ten participants performed triangular shaped contractions to 20% of maximal plantar flexion torque before and after WPHF NMES with and without a handgrip contraction, and control conditions. Extra torque, the relative difference between the initial and final torque during stimulation, and sustained electromyographic (EMG) activity were assessed.

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We introduce the open-source software MUedit and we describe its use for identifying the discharge timing of motor units from all types of electromyographic (EMG) signals recorded with multi-channel systems. MUedit performs EMG decomposition using a blind-source separation approach. Following this, users can display the estimated motor unit pulse trains and inspect the accuracy of the automatic detection of discharge times.

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The diversity in electromyography (EMG) techniques and their reporting present significant challenges across multiple disciplines in research and clinical practice, where EMG is commonly used. To address these challenges and augment the reproducibility and interpretation of studies using EMG, the Consensus for Experimental Design in Electromyography (CEDE) project has developed a checklist (CEDE-Check) to assist researchers to thoroughly report their EMG methodologies. Development involved a multi-stage Delphi process with seventeen EMG experts from various disciplines.

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The distribution of activation among muscles from the same anatomical group can be affected by the mechanical constraints of the task, such as limb orientation. For example, the distribution of activation between the gastrocnemius medialis (GM) and lateralis (GL) muscles during submaximal plantarflexion depends on the orientation of the foot in the horizontal plane. The neural mechanisms behind these modulations are not known.

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Persistent inward currents (PICs) increase the intrinsic excitability of α-motoneurons. The main objective of this study was to compare estimates of α-motoneuronal PICs between inactive, chronic resistance-trained, and chronic endurance-trained young individuals. We also aimed to investigate whether there is a relationship in the estimates of α-motoneuronal PIC magnitude between muscles.

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Background: Using a machine learning algorithm, individuals can be accurately identified from their muscle activation patterns during gait, leading to the concept of individual muscle activation signatures.

Research Question: Are muscle activation signatures robust across different walking speeds?

Methods: We used an open dataset containing electromyographic (EMG) signals from 8 lower limb muscles in 50 asymptomatic adults walking at 5 speeds (extremely slow, very slow, slow, spontaneous, and fast). A machine learning approach classified the EMG profiles based on similar (intra-speed classification) or different (inter-speed classification) walking speeds as training and testing conditions.

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Recent studies have suggested that the nervous system generates movements by controlling groups of motor neurons (synergies) that do not always align with muscle anatomy. In this study, we determined whether these synergies are robust across tasks with different mechanical constraints. We identified motor neuron synergies using principal component analysis (PCA) and cross-correlations between smoothed discharge rates of motor neurons.

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Background: An alteration in the force distribution among quadriceps heads is one possible underlying mechanism of patellofemoral pain. However, this hypothesis cannot be directly tested as there are currently no noninvasive experimental techniques to measure individual muscle force or torque in vivo in humans. In this study, the authors considered a combination of biomechanical and muscle activation measures, which enabled us to estimate the mechanical impact of the vastus medialis (VM) and vastus lateralis (VL) on the patella.

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We aimed to determine whether the neural control of the biarticular gastrocnemius medialis (GM) and lateralis (GL) muscles is joint-specific, that is, whether their control differs between isolated knee flexion and ankle plantar flexion tasks. Twenty-one male participants performed isometric knee flexion and ankle plantar flexion tasks while we recorded high-density surface electromyography (HDsEMG). First, we estimated the distribution of activation both within- and between muscles using two complementary approaches: surface EMG amplitude and motor unit activity identified from HDsEMG decomposition.

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Skeletal muscle is the engine that powers what is arguably the most essential and defining feature of human and animal life-locomotion. Muscles function to change length and produce force to enable movement, posture, and balance. Despite this seemingly simple role, skeletal muscle displays a variety of phenomena that still remain poorly understood.

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Skeletal muscles bulge when they contract. These three-dimensional shape changes, coupled with fiber rotation, influence a muscle's mechanical performance by uncoupling fiber velocity from muscle belly velocity (i.e.

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Purpose: Redundancy of the musculoskeletal system implies multiple strategies are theoretically available to coordinate back extensor muscles. This study investigated whether coordination between back muscles during a tightly constrained isometric trunk extension task varies within and between individuals, and whether this changes following brief exposure to activation feedback of a muscle.

Methods: Nine healthy participants performed three blocks of two repetitions of ramped isometric trunk extension in side-lying against resistance from 0-30% of maximum voluntary contraction over 30 s (force feedback).

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The purpose of our study was to identify the low-dimensional latent components, defined hereafter as motor unit modes, underlying the discharge rates of the motor units in two knee extensors (vastus medialis and lateralis, eight men) and two hand muscles (first dorsal interossei and thenars, seven men and one woman) during submaximal isometric contractions. Factor analysis identified two independent motor unit modes that captured most of the covariance of the motor unit discharge rates. We found divergent distributions of the motor unit modes for the hand and vastii muscles.

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The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials generated by an alpha motor neuron and those received by the innervated muscle fibers. Such a powerful assessment has been conventionally performed with invasive electrodes (i.e.

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High-density electromyography (HD-EMG) decomposition algorithms are used to identify individual motor unit (MU) spike trains, which collectively constitute the neural code of movements, to predict motor intent. This approach has advanced from offline to online decomposition, from isometric to dynamic contractions, leading to a wide range of neural-machine interface applications. However, current online methods need offline retraining when applied to the same muscle on a different day or to a different person, which limits their applications in a real-time neural-machine interface.

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The human soleus muscle is anatomically divided into four separate anatomical compartments. The functional role of this compartmentalization remains unclear. Here, we tested the hypothesis that the common synaptic input to motor units between the medial and lateral posterior compartments is less than within each compartment.

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Understanding how movement is controlled by the CNS remains a major challenge, with ongoing debate about basic features underlying this control. In current established views, the concepts of motor neuron recruitment order, common synaptic input to motor neurons and muscle synergies are usually addressed separately and therefore seen as independent features of motor control. In this review, we analyse the body of literature in a broader perspective and we identify a unified approach to explain apparently divergent observations at different scales of motor control.

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Objective: Previous studies have demonstrated promising results in estimating the neural drive to muscles, the net output of all motoneurons that innervate the muscle, using high-density electromyography (HD-EMG) for the purpose of interfacing with assistive technologies. Despite the high estimation accuracy, current methods based on neural networks need to be trained with specific motor unit action potential (MUAP) shapes updated for each condition (i.e.

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Whether the neural control of manual behaviors differs between the dominant and nondominant hand is poorly understood. This study aimed to determine whether the level of common synaptic input to motor neurons innervating the same or different muscles differs between the dominant and the nondominant hand. Seventeen participants performed two motor tasks with distinct mechanical requirements: an isometric pinch and an isometric rotation of a pinched dial.

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Movements are reportedly controlled through the combination of synergies that generate specific motor outputs by imposing an activation pattern on a group of muscles. To date, the smallest unit of analysis of these synergies has been the muscle through the measurement of its activation. However, the muscle is not the lowest neural level of movement control.

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