Coordination amongst quadriceps muscles suggests neural regulation of internal joint stresses, not simplification of task performance

Dissecting muscle synergies in the task space

The muscle synergy is a guiding concept in motor control research that relies on the general notion of muscles 'working together' towards task performance. However, although the synergy concept has provided valuable insights into motor coordination, muscle interactions have not been fully characterised with respect to task performance. Here, we address this research gap by proposing a novel perspective to the muscle synergy that assigns specific functional roles to muscle couplings by characterising their task-relevance. Our novel perspective provides nuance to the muscle synergy concept, demonstrating how muscular interactions can 'work together' in different ways: (1) irrespective of the task at hand but also (2) redundantly or (3) complementarily towards common task-goals. To establish this perspective, we leverage information- and network-theory and dimensionality reduction methods to include discrete and continuous task parameters directly during muscle synergy extraction. Specifically, we introduce co-information as a measure of the task-relevance of muscle interactions and use it to categorise such interactions as task-irrelevant (present across tasks), redundant (shared task information), or synergistic (different task information). To demonstrate these types of interactions in real data, we firstly apply the framework in a simple way, revealing its added functional and physiological relevance with respect to current approaches. We then apply the framework to large-scale datasets and extract generalizable and scale-invariant representations consisting of subnetworks of synchronised muscle couplings and distinct temporal patterns. The representations effectively capture the functional interplay between task end-goals and biomechanical affordances and the concurrent processing of functionally similar and complementary task information. The proposed framework unifies the capabilities of current approaches in capturing distinct motor features while providing novel insights and research opportunities through a nuanced perspective to the muscle synergy.

Muscle redundancy is greatly reduced by the spatiotemporal nature of neuromuscular control

Animals must control numerous muscles to produce forces and movements with their limbs. Current theories of motor optimization and synergistic control are predicated on the assumption that there are multiple highly diverse feasible activations for any motor task ("muscle redundancy"). Here, we demonstrate that the dimensionality of the neuromuscular control problem is greatly reduced when adding the temporal constraints inherent to any sequence of motor commands: the physiological time constants for muscle activation-contraction dynamics. We used a seven-muscle model of a human finger to fully characterize the seven-dimensional polytope of all possible motor commands that can produce fingertip force vector in any direction in 3D, in alignment with the core models of Feasibility Theory. For a given sequence of seven force vectors lasting 300 ms, a novel single-step extended linear program finds the 49-dimensional polytope of all possible motor commands that can produce the sequence of forces. We find that muscle redundancy is severely reduced when the temporal limits on muscle activation-contraction dynamics are added. For example, allowing a generous ± 12% change in muscle activation within 50 ms allows visiting only ∼ 7% of the feasible activation space in the next time step. By considering that every motor command conditions future commands, we find that the motor-control landscape is much more highly structured and spatially constrained than previously recognized. We discuss how this challenges traditional computational and conceptual theories of motor control and neurorehabilitation for which muscle redundancy is a foundational assumption.

Two motor neuron synergies, invariant across ankle joint angles, activate the triceps surae during plantarflexion

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. In part 1, we used simulations to validate these methods. The results suggested that PCA can accurately identify the number of common inputs and their distribution across active motor neurons. Moreover, the results confirmed that cross-correlation can separate pairs of motor neurons that receive common inputs from those that do not receive common inputs. In part 2, 16 individuals performed plantarflexion at three ankle angles while we recorded EMG signals from the gastrocnemius lateralis (GL) and medialis (GM) and the soleus (SOL) with grids of surface electrodes. The PCA revealed two motor neuron synergies. These motor neuron synergies were relatively stable, with no significant differences in the distribution of motor neuron weights across ankle angles (P = 0.62). When the cross-correlation was calculated for pairs of motor units tracked across ankle angles, we observed that only 13.0% of pairs of motor units from GL and GM exhibited significant correlations of their smoothed discharge rates across angles, confirming the low level of common inputs between these muscles. Overall, these results highlight the modularity of movement control at the motor neuron level, suggesting a sensible reduction of computational resources for movement control. KEY POINTS: The CNS might generate movements by activating groups of motor neurons (synergies) with common inputs. We show here that two main sources of common inputs drive the motor neurons innervating the triceps surae muscles during isometric ankle plantarflexions. We report that the distribution of these common inputs is globally invariant despite changing the mechanical constraints of the tasks, i.e. the ankle angle. These results suggest the functional relevance of the modular organization of the CNS to control movements.

Correlation networks of spinal motor neurons that innervate lower limb muscles during a multi-joint isometric task

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. In this human study (n = 10), we used a purely data-driven method grounded on graph theory to extract networks of motor neurons based on their correlated activity during an isometric multi-joint task. Specifically, high-density surface electromyography recordings from six lower limb muscles were decomposed into motor neurons spiking activity. We analysed these activities by identifying their common low-frequency components, from which networks of correlated activity to the motor neurons were derived and interpreted as networks of common synaptic inputs. The vast majority of the identified motor neurons shared common inputs with other motor neuron(s). In addition, groups of motor neurons were partly decoupled from their innervated muscle, such that motor neurons innervating the same muscle did not necessarily receive common inputs. Conversely, some motor neurons from different muscles-including distant muscles-received common inputs. The study supports the theory that movements are produced through the control of small numbers of groups of motor neurons via common inputs and that there is a partial mismatch between these groups of motor neurons and muscle anatomy. We provide a new neural framework for a deeper understanding of the structure of common inputs to motor neurons. KEY POINTS: A central and unresolved question is how spinal motor neurons are controlled to generate movement. We decoded the spiking activities of dozens of spinal motor neurons innervating six muscles during a multi-joint task, and we used a purely data-driven method grounded on graph theory to extract networks of motor neurons based on their correlated activity (considered as common input). The vast majority of the identified motor neurons shared common inputs with other motor neuron(s). Groups of motor neurons were partly decoupled from their innervated muscle, such that motor neurons innervating the same muscle did not necessarily receive common inputs. Conversely, some motor neurons from different muscles, including distant muscles, received common inputs. The study supports the theory that movement is produced through the control of groups of motor neurons via common inputs and that there is a partial mismatch between these groups of motor neurons and muscle anatomy.

Neuromuscular control: from a biomechanist's perspective

Understanding neural control of movement necessitates a collaborative approach between many disciplines, including biomechanics, neuroscience, and motor control. Biomechanics grounds us to the laws of physics that our musculoskeletal system must obey. Neuroscience reveals the inner workings of our nervous system that functions to control our body. Motor control investigates the coordinated motor behaviours we display when interacting with our environment. The combined efforts across the many disciplines aimed at understanding human movement has resulted in a rich and rapidly growing body of literature overflowing with theories, models, and experimental paradigms. As a result, gathering knowledge and drawing connections between the overlapping but seemingly disparate fields can be an overwhelming endeavour. This review paper evolved as a need for us to learn of the diverse perspectives underlying current understanding of neuromuscular control. The purpose of our review paper is to integrate ideas from biomechanics, neuroscience, and motor control to better understand how we voluntarily control our muscles. As biomechanists, we approach this paper starting from a biomechanical modelling framework. We first define the theoretical solutions (i.e., muscle activity patterns) that an individual could feasibly use to complete a motor task. The theoretical solutions will be compared to experimental findings and reveal that individuals display structured muscle activity patterns that do not span the entire theoretical solution space. Prevalent neuromuscular control theories will be discussed in length, highlighting optimality, probabilistic principles, and neuromechanical constraints, that may guide individuals to families of muscle activity solutions within what is theoretically possible. Our intention is for this paper to serve as a primer for the neuromuscular control scientific community by introducing and integrating many of the ideas common across disciplines today, as well as inspire future work to improve the representation of neural control in biomechanical models.

Neuromechanical Properties of the Vastus Medialis and Vastus Lateralis in Adolescents With Patellofemoral Pain

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.

Purpose/Hypothesis

The purpose of this study was to determine whether the relative index of torque distribution for the VM and VL differs between adolescents with and without patellofemoral pain. It was hypothesized that, relative to the VL, the VM would contribute less to knee extension torque in adolescents with patellofemoral pain compared with controls.

Study Design

Cross-sectional study; Level of evidence, 3.

Methods

Twenty adolescents with patellofemoral pain and 20 matched control participants were included (38 female; age, 15.3 ± 1.8 years; weight, 58 ± 13 kg; height, 164 ± 8 cm). Muscle volumes and resting moment arms were quantified from magnetic resonance images, and fascicle lengths were obtained from panoramic B-mode ultrasonography. Muscle activation was estimated using surface electromyography during submaximal isometric tasks (wall-squat and seated tasks). Muscle torque was estimated as the product of muscle physiological cross-sectional area (ie, muscle volume/fascicle length), muscle activation (normalized to maximal activation), and moment arm.

Results

Across tasks and force levels, the relative contribution of the VM to the overall medial and lateral vastii torque was 31.0% ± 8.6% for controls and 31.5 ± 7.6% for adolescents with patellofemoral pain (group effect, P > .34).

Conclusion

For the tasks and positions investigated in this study, the authors found no evidence of lower VM torque generation (relative to the VL) in adolescents with patellofemoral pain compared with controls.

The Forces Generated by Agonist Muscles during Isometric Contractions Arise from Motor Unit Synergies

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. On average, 75% of the motor units for the thenar muscles and first dorsal interosseus were strongly correlated with the module for the muscle in which they resided. In contrast, we found a continuous distribution of motor unit modes spanning the two vastii muscle modules. The proportion of the muscle-specific motor unit modes was 60% for vastus medialis and 45% for vastus lateralis. The other motor units were either correlated with both muscle modules (shared inputs) or belonged to the module for the other muscle (15% for vastus lateralis). Moreover, coherence of the discharge rates between motor unit pools was explained by the presence of shared synaptic inputs. In simulations with 480 integrate-and-fire neurons, we demonstrate that factor analysis identifies the motor unit modes with high levels of accuracy. Our results indicate that correlated discharge rates of motor units that comprise motor unit modes arise from at least two independent sources of common input among the motor neurons innervating synergistic muscles.SIGNIFICANCE STATEMENT It has been suggested that the nervous system controls synergistic muscles by projecting common synaptic inputs to the engaged motor neurons. In our study, we reduced the dimensionality of the output produced by pools of synergistic motor neurons innervating the hand and thigh muscles during isometric contractions. We found two neural modules, each representing a different common input, that were each specific for one of the muscles. In the vastii muscles, we found a continuous distribution of motor unit modes spanning the two synergistic muscles. Some of the motor units from the homonymous vastii muscle were controlled by the dominant neural module of the other synergistic muscle. In contrast, we found two distinct neural modules for the hand muscles.

Inhibition of knee joint sensory afferents alters covariation across strides between quadriceps muscles during locomotion

Sport-related injuries to articular structures often alter the sensory information conveyed by joint structures to the nervous system. However, the role of joint sensory afferents in motor control is still unclear. Here, we evaluate the role of knee joint sensory afferents in the control of quadriceps muscles, hypothesizing that such sensory information modulates control strategies that limit patellofemoreal joint loading. We compared locomotor kinematics and muscle activity before and after inhibition of knee sensory afferents by injection of lidocaine into the knee capsule of rats. We evaluated whether this inhibition reduced the strength of correlation between the activity of vastus medialis (VM) and vastus lateralis (VL) both across strides and within each stride, coordination patterns that limit net mediolateral patellofemoral forces. We also evaluated whether this inhibition altered correlations among the other quadriceps muscle activity, the time-profiles of individual EMG envelopes, or movement kinematics. Neither the EMG envelopes nor limb kinematics was affected by the inhibition of knee sensory afferents. This perturbation also did not affect the correlations between VM and VL, suggesting that the regulation of patellofemoral joint loading is mediated by different mechanisms. However, inhibition of knee sensory afferents caused a significant reduction in the correlation between vastus intermedius (VI) and both VM and VL across, but not within, strides. Knee joint sensory afferents may therefore modulate the coordination between the vasti muscles but only at coarse time scales. Injuries compromising joint afferents might result in altered muscle coordination, potentially leading to persistent internal joint stresses and strains.NEW & NOTEWORTHY Sensory afferents originating from knee joint receptors provide the nervous system with information about the internal state of the joint. In this study, we show that these sensory signals are used to modulate the covariations among the activity of a subset of vasti muscles across strides of locomotion. Sport-related injuries that damage joint receptors may therefore compromise these mechanisms of muscle coordination, potentially leading to persistent internal joint stresses and strains.

Mechanical disturbances applied by motorized ankle foot orthosis to adapt ankle muscles activation—A validation study

Background: Reduced function of ankle muscles usually leads to impaired gait. Motorized ankle foot orthoses (MAFOs) have shown potential to improve neuromuscular control and increase volitional engagement of ankle muscles. In this study, we hypothesize that specific disturbances (adaptive resistance-based perturbations to the planned trajectory) applied by a MAFO can be used to adapt the activity of ankle muscles. The first goal of this exploratory study was to test and validate two different ankle disturbances based on plantarflexion and dorsiflexion resistance while training in standing still position. The second goal was to assess neuromuscular adaptation to these approaches, namely, in terms of individual muscle activation and co-activation of antagonists.

Methods: Two ankle disturbances were tested in ten healthy subjects. For each subject, the dominant ankle followed a target trajectory while the contralateral leg was standing still: a) dorsiflexion torque during the first part of the trajectory (Stance Correlate disturbance—StC), and b) plantarflexion torque during the second part of the trajectory (Swing Correlate disturbance—SwC). Electromyography was recorded from the tibialis anterior (TAnt) and gastrocnemius medialis (GMed) during MAFO and treadmill (baseline) trials.

Results: GMed (plantarflexor muscle) activation decreased in all subjects during the application of StC, indicating that dorsiflexion torque did not enhance GMed activity. On the other hand, TAnt (dorsiflexor muscle) activation increased when SwC was applied, indicating that plantarflexion torque succeeded in enhancing TAnt activation. For each disturbance paradigm, there was no antagonist muscle co-activation accompanying agonist muscle activity changes.

Conclusion: We successfully tested novel ankle disturbance approaches that can be explored as potential resistance strategies in MAFO training. Results from SwC training warrant further investigation to promote specific motor recovery and learning of dorsiflexion in neural-impaired patients. This training can potentially be beneficial during intermediate phases of rehabilitation prior to overground exoskeleton-assisted walking. Decreased activation of GMed during StC might be attributed to the unloaded body weight in the ipsilateral side, which typically decreases activation of anti-gravity muscles. Neural adaptation to StC needs to be studied thoroughly in different postures in futures studies.

Tolerable degree of muscle sacrifice when harvesting a vastus lateralis or myocutaneous anterolateral thigh flap

The myocutaneous anterolateral thigh (ALT) and vastus lateralis (VL) flaps include a large muscle mass and a sufficient vascular pedicle, and they have been used for decades to reconstruct traumatic and acquired defects of the head and neck and extremities. In spite of these benefits, musculoskeletal dysfunction was reported in nearly 1 out of 20 patients at follow-up. It is unclear whether the recently proposed muscle-sparing flap-raising approach could preserve VL muscle function and whether patients at increased risk could benefit from such an approach. Therefore, we performed a predictive dynamic gait simulation based on a biological motion model with gradual weakening of the VL during a self-selected and fast walking speed to determine the compensable degree of VL muscle reduction. Muscle force, joint angle, and joint moment were measured. Our study showed that VL muscle reduction could be compensated up to a certain degree, which could explain the observed incidence of musculoskeletal dysfunction. In elderly or fragile patients, the VL muscle should not be reduced by 50% or more, which could be achieved by muscle-sparing flap-raising of the superficial partition only. In young or athletic patients, a VL muscle reduction of 10%, which corresponds to a muscle cuff, has no relevant effect. Yet, a reduction of more than 30% leads to relevant weakening of the quadriceps. Therefore, in this patient population with the need for a large portion of muscle, alternative flaps should be considered. This study can serve as the first basis for further investigations of human locomotion after flap-raising.

Motor control strategies differ between monoarticular and biarticular quadriceps muscles during bipedal squats

The interplay between biarticular and monoarticular muscles of the knee and hip joints during bipedal squats (SQ_BP ) requires adequate central-nervous control mechanisms to enable smooth and dynamic movements. Here, we investigated motor control between M. vastus medialis (VM), M. vastus lateralis (VL), and M. rectus femoris (RF) in 12 healthy male recreational athletes during SQ_BP with three load levels (50%, 62.5% & 75% of 3-repetition maximum) following a standardized strength training protocol (3 sets of 10 repetitions). To quantify differences in motor control mechanisms in both time and frequency domains, we analyzed (1) muscle covariation via correlation analyses, as well as (2) common neural input via intermuscular coherence (IMC) between RF, VM, and VL. Our results revealed significantly higher gamma IMC between VM-VL compared to RF-VL and RF-VM for both legs. Correlation analyses demonstrated significantly higher correlation coefficients during ascent periods compared to descent periods across all analyzed muscle pairs. However, no load-dependent modulation of motor control could be observed. Our study provides novel evidence that motor control during SQ_BP is characterized by differences in common input between biarticular and monoarticular muscles. Additionally, muscle activation patterns show higher similarity during ascent compared to descent periods. Future research should aim to validate and extend our observations as insights into the underlying control mechanisms offer the possibility for practical implications to optimize training concepts in elite sports and rehabilitation.

Estimating muscle activation from EMG using deep learning-based dynamical systems models

OBJECTIVE

To study the neural control of movement, it is often necessary to estimate how muscles are activated across a variety of behavioral conditions. One approach is to try extracting the underlying neural command signal to muscles by applying latent variable modeling methods to electromyographic (EMG) recordings. However, estimating the latent command signal that underlies muscle activation is challenging due to its complex relation with recorded EMG signals. Common approaches estimate each muscle activation independently or require manual tuning of model hyperparameters to preserve behaviorally-relevant features.

APPROACH

Here, we adapted AutoLFADS, a large-scale, unsupervised deep learning approach originally designed to de-noise cortical spiking data, to estimate muscle activation from multi-muscle EMG signals. AutoLFADS uses recurrent neural networks (RNNs) to model the spatial and temporal regularities that underlie multi-muscle activation.

MAIN RESULTS

We first tested AutoLFADS on muscle activity from the rat hindlimb during locomotion and found that it dynamically adjusts its frequency response characteristics across different phases of behavior. The model produced single-trial estimates of muscle activation that improved prediction of joint kinematics as compared to low-pass or Bayesian filtering. We also applied AutoLFADS to monkey forearm muscle activity recorded during an isometric wrist force task. AutoLFADS uncovered previously uncharacterized high-frequency oscillations in the EMG that enhanced the correlation with measured force. The AutoLFADS-inferred estimates of muscle activation were also more closely correlated with simultaneously-recorded motor cortical activity than were other tested approaches.

SIGNIFICANCE

This method leverages dynamical systems modeling and artificial neural networks to provide estimates of muscle activation for multiple muscles. Ultimately, the approach can be used for further studies of multi-muscle coordination and its control by upstream brain areas.

The repeatability of neuromuscular activation strategies recorded in recreationally active individuals during cycling

Purpose

The human neuro-motor system can select different intermuscular coordination patterns to complete any given task, such as pedalling a bicycle. This study assessed whether intermuscular coordination patterns are used consistently across visit days and cadence conditions in recreationally active individuals.

Methods

Seven participants completed a cycling exercise protocol across 2 days, consisting of pedalling at 150 Watts at cadences of 60, 80 and 100 rpm. Whilst cycling, surface electromyography was continuously recorded from ten leg muscles. For each participant, muscle coordination patterns were established using principal component (PC) analysis and the amount that each pattern was used was quantified by the PC loading scores. A sample entropy derived measure of the persistence of the loading scores across consecutive pedal cycles, entropic half-life (EnHL), was calculated. The median loading scores and EnHLs of the first three PCs were then compared across cadence conditions and visit days.

Results

No significant differences were found in the median loading scores across cadence conditions or visits, nor were there any significant differences in the EnHLs across visits. However, the EnHLs were significantly longer when participants were cycling at 60 rpm compared to 100 rpm.

Conclusion

These findings are based on a small sample size, but do suggest that, within individual participants, a consistent neuromuscular control strategy is used during cycling on different days. However, the underlying structure of muscle coordination is more persistent when pedalling at slower cadences with large differences between individuals.

A network information theoretic framework to characterise muscle synergies in space and time

Objective Current approaches to muscle synergy extraction rely on linear dimensionality reduction algorithms that make specific assumptions on the underlying signals. However, to capture nonlinear time varying, large-scale but also muscle-specific interactions, a more generalised approach is required. Approach Here we developed a novel framework for muscle synergy extraction that relaxes model assumptions by using a combination of information- and network theory and dimensionality reduction. We first quantify informational dynamics between muscles, time-samples or muscle-time pairings using a novel mutual information formulation. We then model these pairwise interactions as multiplex networks and identify modules representing the network architecture. We employ this modularity criterion as the input parameter for dimensionality reduction, which verifiably extracts the identified modules, and also to characterise salient structures within each module. Main results This novel framework captures spatial, temporal and spatiotemporal interactions across two benchmark datasets of reaching movements, producing distinct spatial groupings and both tonic and phasic temporal patterns. Readily interpretable muscle synergies spanning multiple spatial and temporal scales were identified, demonstrating significant task dependence, ability to capture trial-to-trial fluctuations and concordance across participants. Furthermore, our framework identifies submodular structures that represent the distributed networks of co-occurring signal interactions across scales. Significance The capabilities of this framework are illustrated through the concomitant continuity with previous research and novelty of the insights gained. Several previous limitations are circumvented including the extraction of functionally meaningful and multiplexed pairwise muscle couplings under relaxed model assumptions. The extracted synergies provide a holistic view of the movement while important details of task performance are readily interpretable. The identified muscle groupings transcend biomechanical constraints and the temporal patterns reveal characteristics of fundamental motor control mechanisms. We conclude that this framework opens new opportunities for muscle synergy research and can constitute a bridge between existing models and recent network-theoretic endeavours.

Less common synaptic input between muscles from the same group allows for more flexible coordination strategies during a fatiguing task

This study aimed to determine whether neural drive is redistributed between muscles during a fatiguing isometric contraction, and if so, whether the initial level of common synaptic input between these muscles constrains this redistribution. We studied two muscle groups: triceps surae (14 participants) and quadriceps (15 participants). Participants performed a series of submaximal isometric contractions and a torque-matched contraction maintained until task failure. We used high-density surface electromyography to identify the behavior of 1874 motor units from the soleus, gastrocnemius medialis (GM), gastrocnemius lateralis(GL), rectus femoris, vastus lateralis (VL), and vastus medialis(VM). We assessed the level of common drive between muscles in absence of fatigue using a coherence analysis. We also assessed the redistribution of neural drive between muscles during the fatiguing contraction through the correlation between their cumulative spike trains (index of neural drive). The level of common drive between VL and VM was significantly higher than that observed for the other muscle pairs, including GL-GM. The level of common drive increased during the fatiguing contraction, but the differences between muscle pairs persisted. We also observed a strong positive correlation of neural drive between VL and VM during the fatiguing contraction (r=0.82). This was not observed for the other muscle pairs, including GL-GM, which exhibited differential changes in neural drive. These results suggest that less common synaptic input between muscles allows for more flexible coordination strategies during a fatiguing task, i.e., differential changes in neural drive across muscles. The role of this flexibility on performance remains to be elucidated.

The effect of limb position on a static knee extension task can be explained with a simple spinal cord circuit model

The influence of proprioceptive feedback on muscle activity during isometric tasks is the subject of conflicting studies. We performed an isometric knee extension task experiment based on two common clinical tests for mobility and flexibility. The task was carried out at four preset angles of the knee, and we recorded from five muscles for two different hip positions. We applied muscle synergy analysis using nonnegative matrix factorization on surface electromyograph recordings to identify patterns in the data that changed with internal knee angle, suggesting a link between proprioception and muscle activity. We hypothesized that such patterns arise from the way proprioceptive and cortical signals are integrated in neural circuits of the spinal cord. Using the MIIND neural simulation platform, we developed a computational model based on current understanding of spinal circuits with an adjustable afferent input. The model produces the same synergy trends as observed in the data, driven by changes in the afferent input. To match the activation patterns from each knee angle and position of the experiment, the model predicts the need for three distinct inputs: two to control a nonlinear bias toward the extensors and against the flexors, and a further input to control additional inhibition of rectus femoris. The results show that proprioception may be involved in modulating muscle synergies encoded in cortical or spinal neural circuits.NEW & NOTEWORTHY The role of sensory feedback in motor control when limbs are held in a fixed position is disputed. We performed a novel experiment involving fixed position tasks based on two common clinical tests. We identified patterns of muscle activity during the tasks that changed with different leg positions and then inferred how sensory feedback might influence the observations. We developed a computational model that required three distinct inputs to reproduce the activity patterns observed experimentally. The model provides a neural explanation for how the activity patterns can be changed by sensory feedback.

Control of Mammalian Locomotion by Somatosensory Feedback

When animals walk overground, mechanical stimuli activate various receptors located in muscles, joints, and skin. Afferents from these mechanoreceptors project to neuronal networks controlling locomotion in the spinal cord and brain. The dynamic interactions between the control systems at different levels of the neuraxis ensure that locomotion adjusts to its environment and meets task demands. In this article, we describe and discuss the essential contribution of somatosensory feedback to locomotion. We start with a discussion of how biomechanical properties of the body affect somatosensory feedback. We follow with the different types of mechanoreceptors and somatosensory afferents and their activity during locomotion. We then describe central projections to locomotor networks and the modulation of somatosensory feedback during locomotion and its mechanisms. We then discuss experimental approaches and animal models used to investigate the control of locomotion by somatosensory feedback before providing an overview of the different functional roles of somatosensory feedback for locomotion. Lastly, we briefly describe the role of somatosensory feedback in the recovery of locomotion after neurological injury. We highlight the fact that somatosensory feedback is an essential component of a highly integrated system for locomotor control. © 2021 American Physiological Society. Compr Physiol 11:1-71, 2021.

Evidence for constancy in the modularity of trunk muscle activity preceding reaching: implications for the role of preparatory postural activity

Postural muscle activity precedes voluntary movements of the upper limbs. The traditional view of this activity is that it anticipates perturbations to balance caused by the movement of a limb. However, findings from reach-based paradigms have shown that postural adjustments can initiate center of mass displacement for mobility rather than minimize its displacement for stability. Within this context, altering reaching distance beyond the base of support would place increasing constraints on equilibrium during stance. If the underlying composition of anticipatory postural activity is linked to stability, coordination between muscles (i.e., motor modules) may evolve differently as equilibrium constraints increase. We analyzed the composition of motor modules in functional trunk muscles as participants performed multidirectional reaching movements to targets within and beyond the arm's length. Bilateral trunk and reaching arm muscle activity were recorded. Despite different trunk requirements necessary for successful movement, and the changing biomechanical (i.e., postural) constraints that accompany alterations in reach distance, nonnegative matrix factorization identified functional motor modules derived from preparatory trunk muscle activity that shared common features. Relative similarity in modular weightings (i.e., composition) and spatial activation profiles that reflect movement goals across tasks necessitating differing levels of trunk involvement provides evidence that preparatory postural adjustments are linked to the same task priorities (i.e., movement generation rather than stability).NEW & NOTEWORTHY Reaching within and beyond arm's length places different task constraints upon the required trunk motion necessary for successful movement execution. The identification of constant modular features, including functional muscle weightings and spatial tuning, lend support to the notion that preparatory postural adjustments of the trunk are tied to the same task priorities driving mobility, regardless of the future postural constraints.

Forward and backward walking share the same motor modules and locomotor adaptation strategies

Forward and backward walking are remarkably similar motor behaviors to the extent that backward walking has been described as a time-reversed version of forward walking. However, because they display different muscle activity patterns, it has been questioned if forward and backward walking share common control strategies. To investigate this point, we used a split-belt treadmill experimental paradigm designed to elicit healthy individuals' motor adaptation by changing the speed of one of the treadmill belts, while keeping the speed of the other belt constant. We applied this experimental paradigm to both forward and backward walking. We analyzed several adaptation parameters including step symmetry, stability, and energy expenditure as well as the characteristics of the synergies of lower-limb muscles. We found that forward and backward walking share the same muscle synergy modules. We showed that these modules are marked by similar patterns of adaptation driven by stability and energy consumption minimization criteria, both relying on modulating the temporal activation of the muscle synergies. Our results provide evidence that forward and backward walking are governed by the same control and adaptation mechanisms.

Temporal control of muscle synergies is linked with alpha-band neural drive

KEY POINTS

It is theorized that the nervous system controls groups of muscles together as functional units, or 'synergies', resulting in correlated electromyographic (EMG) signals among muscles. However, such correlation does not necessarily imply group-level neural control. Oscillatory synchronization (coherence) among EMG signals implies neural coupling, but it is not clear how this relates to control of muscle synergies. EMG was recorded from seven arm muscles of 10 adult participants rotating an upper limb ergometer, and EMG-EMG coherence, EMG amplitude correlations and their relationship with each other were characterized. A novel method to derive multi-muscle synergies from EMG-EMG coherence is presented and these are compared with classically defined synergies. Coherent alpha-band (8-16 Hz) drive was strongest among muscles whose gross activity levels are well correlated within a given task. The cross-muscle distribution and temporal modulation of coherent alpha-band drive suggests a possible role in the neural coordination/monitoring of synergies.

ABSTRACT

During movement, groups of muscles may be controlled together by the nervous system as an adaptable functional entity, or 'synergy'. The rules governing when (or if) this occurs during voluntary behaviour in humans are not well understood, at least in part because synergies are usually defined by correlated patterns of muscle activity without regard for the underlying structure of their neural control. In this study, we investigated the extent to which comodulation of muscle output (i.e. correlation of electromyographic (EMG) amplitudes) implies that muscles share intermuscular neural input (assessed via EMG-EMG coherence analysis). We first examined this relationship among pairs of upper limb muscles engaged in an arm cycling task. We then applied a novel multidimensional EMG-EMG coherence analysis allowing synergies to be characterized on the basis of shared neural drive. We found that alpha-band coherence (8-16 Hz) is related to the degree to which overall muscle activity levels correlate over time. The extension of this coherence analysis to describe the cross-muscle distribution and temporal modulation of alpha-band drive revealed a close match to the temporal and structural features of traditionally defined muscle synergies. Interestingly, the coherence-derived neural drive was inversely associated with, and preceded, changes in EMG amplitudes by ∼200 ms. Our novel characterization of how alpha-band neural drive is dynamically distributed among muscles is a fundamental step forward in understanding the neural origins and correlates of muscle synergies.

Perceptual-motor styles

Even for a stereotyped task, sensorimotor behavior is generally variable due to noise, redundancy, adaptability, learning or plasticity. The sources and significance of different kinds of behavioral variability have attracted considerable attention in recent years. However, the idea that part of this variability depends on unique individual strategies has been explored to a lesser extent. In particular, the notion of style recurs infrequently in the literature on sensorimotor behavior. In general use, style refers to a distinctive manner or custom of behaving oneself or of doing something, especially one that is typical of a person, group of people, place, context, or period. The application of the term to the domain of perceptual and motor phenomenology opens new perspectives on the nature of behavioral variability, perspectives that are complementary to those typically considered in the studies of sensorimotor variability. In particular, the concept of style may help toward the development of personalised physiology and medicine by providing markers of individual behaviour and response to different stimuli or treatments. Here, we cover some potential applications of the concept of perceptual-motor style to different areas of neuroscience, both in the healthy and the diseased. We prefer to be as general as possible in the types of applications we consider, even at the expense of running the risk of encompassing loosely related studies, given the relative novelty of the introduction of the term perceptual-motor style in neurosciences.

Approaches to revealing the neural basis of muscle synergies: a review and a critique

The central nervous system (CNS) may produce coordinated motor outputs via the combination of motor modules representable as muscle synergies. Identification of muscle synergies has hitherto relied on applying factorization algorithms to multimuscle electromyographic data (EMGs) recorded during motor behaviors. Recent studies have attempted to validate the neural basis of the muscle synergies identified by independently retrieving the muscle synergies through CNS manipulations and analytic techniques such as spike-triggered averaging of EMGs. Experimental data have demonstrated the pivotal role of the spinal premotor interneurons in the synergies' organization and the presence of motor cortical loci whose stimulations offer access to the synergies, but whether the motor cortex is also involved in organizing the synergies has remained unsettled. We argue that one difficulty inherent in current approaches to probing the synergies' neural basis is that the EMG generative model based on linear combination of synergies and the decomposition algorithms used for synergy identification are not grounded on enough prior knowledge from neurophysiology. Progress may be facilitated by constraining or updating the model and algorithms with knowledge derived directly from CNS manipulations or recordings. An investigative framework based on evaluating the relevance of neurophysiologically constrained models of muscle synergies to natural motor behaviors will allow a more sophisticated understanding of motor modularity, which will help the community move forward from the current debate on the neural versus nonneural origin of muscle synergies.

The Effects of Mechanical Scale on Neural Control and the Regulation of Joint Stability

Recent work has demonstrated how the size of an animal can affect neural control strategies, showing that passive viscoelastic limb properties have a significant role in determining limb movements in small animals but are less important in large animals. We extend that work to consider effects of mechanical scaling on the maintenance of joint integrity; i.e., the prevention of aberrant contact forces within joints that might lead to joint dislocation or cartilage degradation. We first performed a literature review to evaluate how properties of ligaments responsible for joint integrity scale with animal size. Although we found that the cross-sectional area of the anterior cruciate ligament generally scaled with animal size, as expected, the effects of scale on the ligament’s mechanical properties were less clear, suggesting potential adaptations in passive contributions to the maintenance of joint integrity across species. We then analyzed how the neural control of joint stability is altered by body scale. We show how neural control strategies change across mechanical scales, how this scaling is affected by passive muscle properties and the cost function used to specify muscle activations, and the consequences of scaling on internal joint contact forces. This work provides insights into how scale affects the regulation of joint integrity by both passive and active processes and provides directions for studies examining how this regulation might be accomplished by neural systems.

Effects of gravity and kinematic constraints on muscle synergies in arm cycling

Arm cycling is a bimanual motor task used in medical rehabilitation and in sports training. Understanding how muscle coordination changes across different biomechanical constraints in arm cycling is a step toward improved rehabilitation approaches. This exploratory study aims to get new insights on motor control during arm cycling. To achieve our main goal, we used the muscle synergies analysis to test three hypotheses: 1) body position with respect to gravity (sitting and supine) has an effect on muscle synergies; 2) the movement size (crank length) has an effect on the synergistic behavior; 3) the bimanual cranking mode (asynchronous and synchronous) requires different synergistic control. Thirteen able-bodied volunteers performed arm cranking on a custom-made device with unconnected cranks, which allowed testing three different conditions: body position (sitting vs. supine), crank length (10 cm vs. 15 cm), and cranking mode (synchronous vs. asynchronous). For each of the eight possible combinations, subjects cycled for 30 s while electromyography of eight muscles (four from each arm) were recorded: biceps brachii, triceps brachii, anterior deltoid, and posterior deltoid. Muscle synergies in this eight-dimensional muscle space were extracted by nonnegative matrix factorization. Four synergies accounted for over 90% of muscle activation variances in all conditions. Results showed that synergies were affected by body position and cranking mode but practically unaffected by movement size. These results suggest that the central nervous system may employ different motor control strategies in response to external constraints such as cranking mode and body position during arm cycling.NEW & NOTEWORTHY Recent studies analyzed muscle synergies in lower limb cycling. Here, we examine upper limb cycling and specifically the effect of body position with respect to gravity, movement size, and cranking mode on muscle coordination during arm cranking tasks. We show that altered body position and cranking mode affects modular organization of muscle activities. To our knowledge, this is the first study assessing motor control through muscle synergies framework during upper limb cycling with different constraints.

Individual differences in the neural strategies to control the lateral and medial head of the quadriceps during a mechanically constrained task

We observed that the distribution of the strength of neural drive between the vastus lateralis and vastus medialis during a single-joint isometric task varied across participants. Also, we observed that the proportion of neural drive that was shared within and between these muscles also varied across participants. These results provide evidence that the neural strategies to control the vastus lateralis and vastus medialis muscles widely vary across individuals, even during a mechanically constrained task.

Influence of low back pain and its remission on motor abundance in a low-load lifting task

Having an abundance of motor solutions during movement may be advantageous for the health of musculoskeletal tissues, given greater load distribution between tissues. The aim of the present study was to understand whether motor abundance differs between people with and without low back pain (LBP) during a low-load lifting task. Motion capture with electromyography (EMG) assessment of 15 muscles was performed on 48 participants [healthy control (con) = 16, remission LBP (rLBP) = 16, current LBP (cLBP) = 16], during lifting. Non-negative matrix factorization and uncontrolled manifold analysis were performed to decompose inter-repetition variability in the temporal activity of muscle modes into goal equivalent (GEV) and non-goal equivalent (NGEV) variabilities in the control of the pelvis and trunk linear displacements. Motor abundance occurs when the ratio of GEV to NGEV exceeds zero. There were significant group differences in the temporal activity of muscle modes, such that both cLBP and rLBP individuals demonstrated greater activity of muscle modes that reflected lumbopelvic coactivation during the lifting phase compared to controls. For motor abundance, there were no significant differences between groups. Individuals with LBP, including those in remission, had similar overall motor abundance, but use different activation profiles of muscle modes than asymptomatic people during lifting.

Coordination amongst quadriceps muscles suggests neural regulation of internal joint stresses, not simplification of task performance

Many studies have demonstrated covariation between muscle activations during behavior, suggesting that muscles are not controlled independently. According to one common proposal, this covariation reflects simplification of task performance by the nervous system so that muscles with similar contributions to task variables are controlled together. Alternatively, this covariation might reflect regulation of low-level aspects of movements that are common across tasks, such as stresses within joints. We examined these issues by analyzing covariation patterns in quadriceps muscle activity during locomotion in rats. The three monoarticular quadriceps muscles (vastus medialis [VM], vastus lateralis [VL], and vastus intermedius [VI]) produce knee extension and so have identical contributions to task performance; the biarticular rectus femoris (RF) produces an additional hip flexion. Consistent with the proposal that muscle covariation is related to similarity of muscle actions on task variables, we found that the covariation between VM and VL was stronger than their covariations with RF. However, covariation between VM and VL was also stronger than their covariations with VI. Since all vastii have identical actions on task variables, this finding suggests that covariation between muscle activity is not solely driven by simplification of overt task performance. Instead, the preferentially strong covariation between VM and VL is consistent with the control of internal joint stresses: Since VM and VL produce opposing mediolateral forces on the patella, the high positive correlation between their activation minimizes the net mediolateral patellar force. These results provide important insights into the interpretation of muscle covariations and their role in movement control.