The human motor neuron pools receive a dominant slow-varying common synaptic input

The identification of extensive samples of motor units in human muscles reveals diverse effects of neuromodulatory inputs on the rate coding

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. To provide the most comprehensive framework to date of motor unit activity during isometric contractions, we identified the firing activity of extensive samples of motor units in the tibialis anterior (129 ± 44 per participant; n=8) and the vastus lateralis (130 ± 63 per participant; n=8) muscles during isometric contractions of up to 80% of maximal force. From this unique dataset, the rate coding of each motor unit was characterised as the relation between its instantaneous firing rate and the applied force, with the assumption that the linear increase in isometric force reflects a proportional increase in the net synaptic excitatory inputs received by the motoneuron. This relation was characterised with a natural logarithm function that comprised two stages. The initial stage was marked by a steep acceleration of firing rate, which was greater for low- than medium- and high-threshold motor units. The second stage comprised a linear increase in firing rate, which was greater for high- than medium- and low-threshold motor units. Changes in firing rate were largely non-linear during the ramp-up and ramp-down phases of the task, but with significant prolonged firing activity only evident for medium-threshold motor units. Contrary to what is usually assumed, our results demonstrate that the firing rate of each motor unit can follow a large variety of trends with force across the pool. From a neural control perspective, these findings indicate how motor unit pools use gain control to transform inputs with limited bandwidths into an intended muscle force.

Distinct Neural Drives along the Semitendinosus Muscle

INTRODUCTION

Conflicting results have been reported on the functional role of the proximal and distal compartments of the semitendinosus (ST) muscle. This study compared the discharge characteristics of motor units (MU) in the two compartments at three knee joint angles (0°: long length; 45°: intermediate length; and 90°: short length).

METHODS

Twenty men (21.4 ± 2.3 yr) performed steady isometric contractions with the knee flexors at four target forces: 10%, 20%, 40%, and 60% of maximum voluntary contraction. High-density EMG signals were recorded to examine the MU discharge characteristics in the two compartments. Measurements included recruitment threshold, mean discharge rate, coefficient of variation (CoV) for interspike interval, and SD of filtered cumulative spike train (fCST). Additionally, the within- and between-compartment association of the neural drive was calculated.

RESULTS

ANOVA indicated that maximal force, absolute EMG amplitude during the maximum voluntary contractions, and force steadiness (CoV for force) were greater at the longest muscle length than the other two lengths ( P < 0.05). Linear mixed models showed that both recruitment threshold and CoV for interspike interval were similar between compartments ( P > 0.05) at each of the three knee joint angles. However, the mean discharge rate and the variability in neural drive were greater for the proximal than the distal compartment ( P < 0.05). The between-compartment association in neural drive (filtered cumulative spike train) was relatively low.

CONCLUSIONS

There were distinct differences in MU discharge characteristics between the proximal and the distal compartments of ST across its operating range of muscle lengths, and each compartment received a relatively distinct neural drive. These findings emphasize the importance of recognizing differences in neural control of the ST compartments to guide related interventions and to inform rehabilitation strategies.

A Stochastic Dynamic Operator Framework That Improves the Precision of Analysis and Prediction Relative to the Classical Spike-Triggered Average Method, Extending the Toolkit

Here we test the stochastic dynamic operator (SDO) as a new framework for describing physiological signal dynamics relative to spiking or stimulus events. The SDO is a natural extension of existing spike-triggered average (STA) or stimulus-triggered average techniques currently used in neural analysis. It extends the classic STA to cover state-dependent and probabilistic responses where STA may fail. In simulated data, SDO methods were more sensitive and specific than the STA for identifying state-dependent relationships. We have tested SDO analysis for interactions between electrophysiological recordings of spinal interneurons, single motor units, and aggregate muscle electromyograms (EMG) of major muscles in the spinal frog hindlimb. When predicting target signal behavior relative to spiking events, the SDO framework outperformed or matched classical spike-triggered averaging methods. SDO analysis permits more complicated spike-signal relationships to be captured, analyzed, and interpreted visually and intuitively. SDO methods can be applied at different scales of interest where spike-triggered averaging methods are currently employed, and beyond, from single neurons to gross motor behaviors. SDOs may be readily generated and analyzed using the provided SDO Analysis Toolkit We anticipate this method will be broadly useful for describing dynamical signal behavior and uncovering state-dependent relationships of stochastic signals relative to discrete event times.

Alpha band oscillations in common synaptic input are explanatory of the complexity of isometric knee extensor muscle torque signals

We investigated whether the strength of oscillations in common synaptic input was explanatory of knee extensor (KE) torque signal complexity during fresh and fatigued submaximal isometric contractions, in adults aged from 18 to 90 years. The discharge times of motor units were derived from the vastus lateralis muscle of 60 participants using high-density surface EMG, during 20 s isometric KE contractions at 20% of maximal voluntary contraction, performed before and after a fatiguing repeated isometric KE contraction protocol at 60% of maximal voluntary contraction. Within-muscle coherence Z-scores were estimated using frequency-domain coherence analysis, and muscle torque complexity was assessed using multiscale entropy analysis and detrended fluctuation analysis. Alpha band (5-15 Hz) coherence was found to predict 23.1% and 31.4% of the variance in the complexity index under 28-scales (CI-28) and detrended fluctuation analysis α complexity metrics, respectively, during the fresh contractions. Delta, alpha and low beta band coherence were significantly increased due to fatigue. Fatigue-related changes in alpha coherence were significantly predictive of the fatigue-related changes in CI-28 and detrended fluctuation analysis α. The fatigue-related increase in sample entropy from scales 11 to 28 of the multiscale entropy analysis curves was significantly predicted by the increase in the alpha band coherence. Age was not a contributory factor to the fatigue-related changes in within-muscle coherence and torque signal complexity. These findings indicate that the strength of alpha band oscillations in common synaptic input can explain, in part, isometric KE torque signal complexity and the fatigue-related changes in torque signal complexity.

Neuroplastic alterations in common synaptic inputs and synergistic motor unit clusters controlling the vastii muscles of individuals with ACL reconstruction

This cross-sectional study aims to elucidate the neural mechanisms underlying the control of knee extension forces in individuals with anterior cruciate ligament reconstruction (ACLR). Eleven soccer players with ACLR and nine control players performed unilateral isometric knee extensions at 10% and 30% of their maximum voluntary force (MVF). Simultaneous recordings of high-density surface electromyography (HDEMG) and force output were conducted for each lower limb, and HDEMG data from the vastus lateralis (VL) and vastus medialis (VM) muscles were decomposed into individual motor unit spike trains. Force steadiness was estimated using the coefficient of variation of force. An intramuscular coherence analysis was adopted to estimate the common synaptic input (CSI) converging to each muscle. A factor analysis was applied to investigate the neural strategies underlying the control of synergistic motor neuron clusters, referred to as motor unit modes. Force steadiness was similar between lower limbs. However, motor neurons innervating the VL on the reconstructed side received a lower proportion of CSI at low-frequency bandwidths (<5 Hz) compared with the unaffected lower limbs (P < 0.01). Furthermore, the reconstructed side demonstrated a higher proportion of motor units associated with the neural input common to the synergistic muscle, as compared with the unaffected lower limbs (P < 0.01). These findings indicate that the VL muscle of reconstructed lower limbs contribute marginally to force steadiness and that a plastic rearrangement in synergistic clusters of motor units involved in the control of knee extension forces is evident following ACLR.NEW & NOTEWORTHY Chronic quadriceps dysfunction is common after anterior cruciate ligament reconstruction (ACLR). We investigated voluntary force control strategies by estimating common inputs to motor neurons innervating the vastii muscles. Our results showed attenuated common inputs to the vastus lateralis and plastic rearrangements in functional clusters of motor neurons modulating knee extension forces in the reconstructed limb. These findings suggest neuroplastic adjustments following ACLR that may occur to fine-tune the control of quadriceps forces.

Explaining the influence of practice on the grooved pegboard times of older adults: role of force steadiness

The purpose was to identify the variables that can explain the variance in the grooved pegboard times of older adults categorized as either fast or slow performers. Participants (n = 28; 60-83 years) completed two experimental sessions, before and after 6 practice sessions of the grooved pegboard test. The 2 groups were identified based on average pegboard times during the practice sessions. Average pegboard time during practice was 73 ± 11 s for the fast group and 85 ± 13 s for the slow group. Explanatory variables for the pegboard times before and after practice were the durations of 4 peg-manipulation phases and 12 measures of force steadiness (coefficient of variation [CV] for force) during isometric contractions with the index finger abductor and wrist extensor muscles. Time to complete the grooved pegboard test after practice decreased by 25 ± 11% for the fast group and by 28 ± 10% for the slow group. Multiple regression models explained more of the variance in the pegboard times for the fast group before practice (Adjusted R2 = 0.85) than after practice (R2 = 0.51), whereas the variance explained for the slow group was similar before (Adjusted R2 = 0.67) and after (Adjusted R2 = 0.64) practice. The explanatory variables differed between before and after practice for the fast group but only slightly for the slow group. These findings indicate that performance-based stratification of older adults can identify unique adjustments in motor function that are independent of chronological age.

Onion skin is not a universal firing pattern for spinal motoneurons: simulation study

Muscle force is modulated by sequential recruitment and firing rates of motor units (MUs). However, discrepancies exist in the literature regarding the relationship between MU firing rates and their recruitment, presenting two contrasting firing-recruitment schemes. The first firing scheme, known as "onion skin," exhibits low-threshold MUs firing faster than high-threshold MUs, forming separate layers akin to an onion. This contradicts the other firing scheme, known as "reverse onion skin" or "afterhyperpolarization (AHP)," with low-threshold MUs firing slower than high-threshold MUs. To study this apparent dichotomy, we used a high-fidelity computational model that prioritizes physiological fidelity and heterogeneity, allowing versatility in the recruitment of different motoneuron types. Our simulations indicate that these two schemes are not mutually exclusive but rather coexist. The likelihood of observing each scheme depends on factors such as the motoneuron pool activation level, synaptic input activation rates, and MU type. The onion skin scheme does not universally govern the encoding rates of MUs but tends to emerge in unsaturated motoneurons (cells firing < their fusion frequency that generates peak force), whereas the AHP scheme prevails in saturated MUs (cells firing at their fusion frequency), which is highly probable for slow (S)-type MUs. When unsaturated, fast fatigable (FF)-type MUs always show the onion skin scheme, whereas S-type MUs do not show either one. Fast fatigue-resistant (FR)-type MUs are generally similar but show weaker onion skin behaviors than FF-type MUs. Our results offer an explanation for the longstanding dichotomy regarding MU firing patterns, shedding light on the factors influencing the firing-recruitment schemes.NEW & NOTEWORTHY The literature reports two contrasting schemes, namely the onion skin and the afterhyperpolarization (AHP) regarding the relationship between motor units (MUs) firing rates and recruitment order. Previous studies have examined these schemes phenomenologically, imposing one scheme on the firing-recruitment relationship. Here, we used a high-fidelity computational model that prioritizes biological fidelity and heterogeneity to investigate motoneuron firing schemes without bias toward either scheme. Our objective findings offer an explanation for the longstanding dichotomy on MU firing patterns.

Neural Filtering of Physiological Tremor Oscillations to Spinal Motor Neurons Mediates Short-Term Acquisition of a Skill Learning Task

The acquisition of a motor skill involves adaptations of spinal and supraspinal pathways to alpha motoneurons. In this study, we estimated the shared synaptic contributions of these pathways to understand the neural mechanisms underlying the short-term acquisition of a new force-matching task. High-density surface electromyography (HDsEMG) was acquired from the first dorsal interosseous (FDI; 7 males and 6 females) and tibialis anterior (TA; 7 males and 4 females) during 15 trials of an isometric force-matching task. For two selected trials (pre- and post-skill acquisition), we decomposed the HDsEMG into motor unit spike trains, tracked motor units between trials, and calculated the mean discharge rate and the coefficient of variation of interspike interval (COVISI). We also quantified the post/pre ratio of motor units' coherence within delta, alpha, and beta bands. Force-matching improvements were accompanied by increased mean discharge rate and decreased COVISI for both muscles. Moreover, the area under the curve within alpha band decreased by ∼22% (TA) and ∼13% (FDI), with no delta or beta bands changes. These reductions correlated significantly with increased coupling between force/neural drive and target oscillations. These results suggest that short-term force-matching skill acquisition is mediated by attenuation of physiological tremor oscillations in the shared synaptic inputs. Supported by simulations, a plausible mechanism for alpha band reductions may involve spinal interneuron phase-cancelling descending oscillations. Therefore, during skill learning, the central nervous system acts as a matched filter, adjusting synaptic weights of shared inputs to suppress neural components unrelated to the specific task.

Effects of repetition of a car-driving pedal maneuver and neural output in older adults

Understanding the ability of older adults to control pedal position angle and investigating whether this ability can be enhanced through practice may contribute to the prevention of traffic accidents. This study aimed to investigate repetitive effects on variability of the pedal position and neural drive during car-pedal operation in older adults. Thirteen older and 11 young adults performed 105 (21 sets × 5 repetitions) pedal angle control tasks with plantar flexor contraction. High-density surface electromyograms were recorded of triceps surae muscles. A cumulative spike train as a neural drive was calculated using continuously active motor unit activities. The coefficient of variation of the angle was higher in older (1.47 ± 1.06 %) than young (0.41 ± 0.21 %) adults in the first sets, and improved to 0.67 ± 0.51 % in the final sets in older adults only. There was no significant difference in neural drive variability between older and young adults. Our results suggest that repetition improves angular steadiness in older adults. However, this effect could not be explained by neural output which is estimated from lower threshold motor units that are continuously active.

Motor unit modes in the calf muscles during a submaximal isometric contraction are changed by brief stretches

The purpose of our study was to investigate the influence of a stretch intervention on the common modulation of discharge rate among motor units in the calf muscles during a submaximal isometric contraction. The current report comprises a computational analysis of a motor unit dataset that we published previously (Mazzo et al., 2021). Motor unit activity was recorded from the three main plantar flexor muscles while participants performed an isometric contraction at 10% of the maximal voluntary contraction force before and after each of two interventions. The interventions were a control task (standing balance) and static stretching of the plantar flexor muscles. A factorization analysis on the smoothed discharge rates of the motor units from all three muscles yielded three modes that were independent of the individual muscles. The composition of the modes was not changed by the standing-balance task, whereas the stretching exercise reduced the average correlation in the second mode and increased it in the third mode. A centroid analysis on the correlation values showed that most motor units were associated with two or three modes, which were presumed to indicate shared synaptic inputs. The percentage of motor units adjacent to the seven centroids changed after both interventions: Control intervention, mode 1 decreased and the shared mode 1 + 2 increased; stretch intervention, shared modes either decreased (1 + 2) or increased (1 + 3). These findings indicate that the neuromuscular adjustments during both interventions were sufficient to change the motor unit modes when the same task was performed after each intervention. KEY POINTS: Based on covariation of the discharge rates of motor units in the calf muscles during a submaximal isometric contraction, factor analysis was used to assign the correlated discharge trains to three motor unit modes. The motor unit modes were determined from the combined set of all identified motor units across the three muscles before and after each participant performed a control and a stretch intervention. The composition of the motor unit modes changed after the stretching exercise, but not after the control task (standing balance). A centroid analysis on the distribution of correlation values found that most motor units were associated with a shared centroid and this distribution, presumably reflecting shared synaptic input, changed after both interventions. Our results demonstrate how the distribution of multiple common synaptic inputs to the motor neurons innervating the plantar flexor muscles changes after a brief series of stretches.

Control of motor output during steady submaximal contractions is modulated by contraction history

The purpose of the study was to investigate the influence of contraction history on force steadiness and the associated EMG activity during submaximal isometric contractions performed with the dorsiflexor muscles. The key feature of the protocol was a triangular ramp contraction performed in the middle of a steady contraction at a lower target force. The target force during the ramp contraction was 20% MVC greater than that during the steady contraction. Thirty-seven healthy individuals (21 men and 16 women) performed the submaximal tasks with the ankle dorsiflexors. Electromyography (EMG) signals were recorded from tibialis anterior with a pair of surface electrodes. The coefficient of variation for force was significantly greater during the second steady contraction compared with the first one at each of the seven target forces (p < 0.015; d = 0.38-0.92). Although the average applied force during the steady contractions before and after the triangular contraction was the same (p = 0.563), the mean EMG amplitude for the steady contractions performed after the triangular contraction was significantly greater at each of the seven target forces (p < 0.0001; d = 0.44-0.68). Also, there were significant differences in mean EMG frequency between the steady contractions performed before and after the triangular contraction (p < 0.01; d = 0.13-0.82), except at 10 and 20% MVC force. The greater force fluctuations during a steady submaximal contraction after an intervening triangular contraction indicate a change in the discharge characteristics of the involved motor units.

Postinhibitory excitation in motoneurons can be facilitated by hyperpolarization-activated inward currents: A simulation study

Postinhibitory excitation is a transient overshoot of a neuron's baseline firing rate following an inhibitory stimulus and can be observed in vivo in human motoneurons. However, the biophysical origin of this phenomenon is still unknown and both reflex pathways and intrinsic motoneuron properties have been proposed. We hypothesized that postinhibitory excitation in motoneurons can be facilitated by hyperpolarization-activated inward currents (h-currents). Using an electrical circuit model, we investigated how h-currents can modulate the postinhibitory response of motoneurons. Further, we analyzed the spike trains of human motor units from the tibialis anterior muscle during reciprocal inhibition. The simulations revealed that the activation of h-currents by an inhibitory postsynaptic potential can cause a short-term increase in a motoneuron's firing probability. This result suggests that the neuron can be excited by an inhibitory stimulus. In detail, the modulation of the firing probability depends on the time delay between the inhibitory stimulus and the previous action potential. Further, the postinhibitory excitation's strength correlates with the inhibitory stimulus's amplitude and is negatively correlated with the baseline firing rate as well as the level of input noise. Hallmarks of h-current activity, as identified from the modeling study, were found in 50% of the human motor units that showed postinhibitory excitation. This study suggests that h-currents can facilitate postinhibitory excitation and act as a modulatory system to increase motoneuron excitability after a strong inhibition.

Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy

The computational simulation of human voluntary muscle contraction is possible with EMG-driven Hill-type models of whole muscles. Despite impactful applications in numerous fields, the neuromechanical information and the physiological accuracy such models provide remain limited because of multiscale simplifications that limit comprehensive description of muscle internal dynamics during contraction. We addressed this limitation by developing a novel motoneuron-driven neuromuscular model, that describes the force-generating dynamics of a population of individual motor units, each of which was described with a Hill-type actuator and controlled by a dedicated experimentally derived motoneuronal control. In forward simulation of human voluntary muscle contraction, the model transforms a vector of motoneuron spike trains decoded from high-density EMG signals into a vector of motor unit forces that sum into the predicted whole muscle force. The motoneuronal control provides comprehensive and separate descriptions of the dynamics of motor unit recruitment and discharge and decodes the subject's intention. The neuromuscular model is subject-specific, muscle-specific, includes an advanced and physiological description of motor unit activation dynamics, and is validated against an experimental muscle force. Accurate force predictions were obtained when the vector of experimental neural controls was representative of the discharge activity of the complete motor unit pool. This was achieved with large and dense grids of EMG electrodes during medium-force contractions or with computational methods that physiologically estimate the discharge activity of the motor units that were not identified experimentally. This neuromuscular model advances the state-of-the-art of neuromuscular modelling, bringing together the fields of motor control and musculoskeletal modelling, and finding applications in neuromuscular control and human-machine interfacing research.

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.

Sensorimotor integration is affected by acute whole-body vibration: a coherence study

Introduction: Several whole-body vibration (WBV) effects on performance have been related to potential changes in the neural drive, motor unit firing rate, and sensorimotor integration. In the present paper, motor unit coherence analysis was performed to detect the source of neural modulation based on the frequency domain. Methods: Thirteen men [25 ± 2.1 years; Body Mass Index (BMI) = 23.9 ± 1.3 kg m2; maximal voluntary force (MVF): 324.36 ± 41.26 N] performed sustained contractions of the Tibialis Anterior (TA) at 10%MVF before and after acute WBV. The vibrating stimulus was applied barefoot through a platform to target the TA. High-Density surface Electromyography (HDsEMG) was used to record the myoelectrical activity of TA to evaluate coherence from motor unit cumulative spike-trains (CSTs). Results: Mean coherence showed a significant decrease in the alpha and low-beta bandwidths (alpha: from 0.143 ± 0.129 to 0.132 ± 0.129, p = 0.035; low-beta: from 0.117 ± 0.039 to 0.086 ± 0.03, p = 0.0001), whereas no significant changes were found in the other ones (p > 0.05). The discharge rate (DR) and the Force Covariance (CovF%) were not significantly affected by acute WBV exposure (p > 0.05). Discussion: According to the significant effects found in alpha and low-beta bandwidths, which reflect sensorimotor integration parameters, accompanied by no differences in the DR and CovF%, the present results underlined that possible neural mechanisms at the base of the previously reported performance enhancements following acute WBV are likely based on sensorimotor integration rather than direct neural drive modulation.

Standard intensities of transcranial alternating current stimulation over the motor cortex do not entrain corticospinal inputs to motor neurons

Transcranial alternating current stimulation (TACS) is commonly used to synchronize a cortical area and its outputs to the stimulus waveform, but gathering evidence for this based on brain recordings in humans is challenging. The corticospinal tract transmits beta oscillations (∼21 Hz) from the motor cortex to tonically contracted limb muscles linearly. Therefore, muscle activity may be used to measure the level of beta entrainment in the corticospinal tract due to TACS over the motor cortex. Here, we assessed whether TACS is able to modulate the neural inputs to muscles, which would provide indirect evidence for TACS-driven neural entrainment. In the first part of the study, we ran simulations of motor neuron (MN) pools receiving inputs from corticospinal neurons with different levels of beta entrainment. Results suggest that MNs are highly sensitive to changes in corticospinal beta activity. Then, we ran experiments on healthy human subjects (N = 10) in which TACS (at 1 mA) was delivered over the motor cortex at 21 Hz (beta stimulation), or at 7 Hz or 40 Hz (control conditions) while the abductor digiti minimi or the tibialis anterior muscle were tonically contracted. Muscle activity was measured using high-density electromyography, which allowed us to decompose the activity of pools of motor units innervating the muscles. By analysing motor unit pool activity, we observed that none of the TACS conditions could consistently alter the spectral contents of the common neural inputs received by the muscles. These results suggest that 1 mA TACS over the motor cortex given at beta frequencies does not entrain corticospinal activity. KEY POINTS: Transcranial alternating current stimulation (TACS) is commonly used to entrain the communication between brain regions. It is challenging to find direct evidence supporting TACS-driven neural entrainment due to the technical difficulties in recording brain activity during stimulation. Computational simulations of motor neuron pools receiving common inputs in the beta (∼21 Hz) band indicate that motor neurons are highly sensitive to corticospinal beta entrainment. Motor unit activity from human muscles does not support TACS-driven corticospinal entrainment.

Linking cortex and contraction-Integrating models along the corticomuscular pathway

Computational models of the neuromusculoskeletal system provide a deterministic approach to investigate input-output relationships in the human motor system. Neuromusculoskeletal models are typically used to estimate muscle activations and forces that are consistent with observed motion under healthy and pathological conditions. However, many movement pathologies originate in the brain, including stroke, cerebral palsy, and Parkinson's disease, while most neuromusculoskeletal models deal exclusively with the peripheral nervous system and do not incorporate models of the motor cortex, cerebellum, or spinal cord. An integrated understanding of motor control is necessary to reveal underlying neural-input and motor-output relationships. To facilitate the development of integrated corticomuscular motor pathway models, we provide an overview of the neuromusculoskeletal modelling landscape with a focus on integrating computational models of the motor cortex, spinal cord circuitry, α-motoneurons  and skeletal muscle in regard to their role in generating voluntary muscle contraction. Further, we highlight the challenges and opportunities associated with an integrated corticomuscular pathway model, such as challenges in defining neuron connectivities, modelling standardisation, and opportunities in applying models to study emergent behaviour. Integrated corticomuscular pathway models have applications in brain-machine-interaction, education, and our understanding of neurological disease.

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.

Real-time myoelectric control of wrist/hand motion in Duchenne muscular dystrophy: A case study

Introduction: Duchenne muscular dystrophy (DMD) is a genetic disorder that induces progressive muscular degeneration. Currently, the increase in DMD individuals' life expectancy is not being matched by an increase in quality of life. The functioning of the hand and wrist is central for performing daily activities and for providing a higher degree of independence. Active exoskeletons can assist this functioning but require the accurate decoding of the users' motor intention. These methods have, however, never been systematically analyzed in the context of DMD. Methods: This case study evaluated direct control (DC) and pattern recognition (PR), combined with an admittance model. This enabled customization of myoelectric controllers to one DMD individual and to a control population of ten healthy participants during a target-reaching task in 1- and 2- degrees of freedom (DOF). We quantified real-time myocontrol performance using target reaching times and compared the differences between the healthy individuals and the DMD individual. Results and Discussion: Our findings suggest that despite the muscle tissue degeneration, the myocontrol performance of the DMD individual was comparable to that of the healthy individuals in both DOFs and with both control approaches. It was also evident that PR control performed better for the 2-DOF tasks for both DMD and healthy participants, while DC performed better for the 1-DOF tasks. The insights gained from this study can lead to further developments for the intuitive multi-DOF myoelectric control of active hand exoskeletons for individuals with DMD.

Blockade of 5-HT2 receptors suppresses motor unit firing and estimates of persistent inward currents during voluntary muscle contraction in humans

Serotonergic neuromodulation contributes to enhanced voluntary muscle activation. However, it is not known how the likely motoneurone receptor candidate (5-HT₂ ) influences the firing rate and activation threshold of motor units (MUs) in humans. The purpose of this study was to determine whether 5-HT₂ receptor activity contributes to human MU behaviour during voluntary ramped contractions of differing intensity. High-density surface EMG (HDsEMG) of the tibialis anterior was assessed during ramped isometric dorsiflexions at 10, 30, 50 and 70% of maximal voluntary contraction (MVC). MU characteristics were successfully extracted from HDsEMG of 11 young adults (four female) pre- and post-ingestion of 8 mg cyproheptadine or a placebo. Antagonism of 5-HT₂ receptors caused a reduction in MU discharge rate during steady-state muscle activation that was independent of the level of contraction intensity [P < 0.001; estimated mean difference (∆) = 1.06 pulses/s], in addition to an increase in MU derecruitment threshold (P < 0.013, ∆ = 1.23% MVC), without a change in force during MVC (P = 0.652). A reduction in estimates of persistent inward current amplitude was observed at 10% MVC (P < 0.001, ∆ = 0.99 Hz) and 30% MVC (P = 0.003, ∆ = 0.75 Hz) that aligned with 5-HT changes in MU firing behaviour attributable to 5-HT₂ antagonism. Overall, these findings indicate that 5-HT₂ receptor activity has a role in regulating the discharge rate in populations of spinal motoneurones when performing voluntary contractions. This study provides evidence of a direct link between MU discharge properties, persistent inward current activity and 5-HT₂ receptor activity in humans. KEY POINTS: Activation of 5-HT receptors on the soma and dendrites of motoneurones regulates their excitability. Previous work using chlorpromazine and cyproheptadine has demonstrated that the 5-HT₂ receptor regulates motoneurone activity in humans with chronic spinal cord injury and non-injured control subjects. It is not known how the 5-HT₂ receptor directly influences motor unit (MU) discharge and MU recruitment in larger populations of human motoneurones during voluntary contractions of differing intensity. Despite the absence of change in force during maximal voluntary dorsiflexions, 5-HT₂ receptor antagonism caused a reduction in MU discharge rate during submaximal steady-state muscle contraction, in addition to an increase in MU derecruitment threshold, irrespective of the submaximal contraction intensity. Reductions in estimates of persistent inward currents after 5-HT₂ receptor antagonism support the viewpoint that the 5-HT₂ receptor plays a crucial role in regulating motor activity, whereby a persistent inward current-based mechanism is involved in regulating the excitability of human motoneurones.

Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix

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., intramuscular electromyography (EMG)), however, recent advances in signal processing techniques have enabled the identification of single motor unit (SMU) activity in high-density surface electromyography (HDsEMG) recordings. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, provides recommendations for the recording and analysis of SMU activity with both invasive (needle and fine-wire EMG) and non-invasive (HDsEMG) SMU identification methods, summarizing their advantages and disadvantages when used during different testing conditions. Recommendations for the analysis and reporting of discharge rate and peripheral (i.e., muscle fiber conduction velocity) SMU properties are also provided. The results of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers to collect, report, and interpret SMU data in the context of both research and clinical applications.

Common synaptic input between motor units from the lateral and medial posterior soleus compartments does not differ from that within each compartment

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. Fourteen male participants performed three different heel-raise tasks that were considered to place a different mechanical demand on the medial and lateral soleus compartments. High-density electromyography (EMG) signals from the medial and lateral soleus compartments and the medial gastrocnemius of the right leg were decomposed into individual motor unit spike trains. The coherence between cumulative spike trains of the motor units was estimated. The coherence analysis was also repeated for motor units that were matched across all three tasks. Furthermore, we calculated the ratio of significant correlations between the spike trains of pairs of motor units. We observed that the coherence between motor units of the two soleus compartments was similar as the coherence between motor units within each compartment, regardless of the task. The correlation analysis performed on pairs of motor units confirmed these results. We conclude that the level of common synaptic input between the motor units innervating the medial and lateral posterior soleus compartment is not different than the common synaptic input between motor units innervating each of these compartments, which contrasts with findings from previous studies on finger muscles. This suggests that there is no independent neural control for the individual posterior soleus compartments.NEW & NOTEWORTHY The human soleus muscle is anatomically subdivided into four compartments. The functional role for this compartmentalization remains unknown. Here, we showed that, contrary to previous findings in finger muscles, the common synaptic input between motor units innervating the medial and lateral posterior soleus compartment was similar as that between motor units within the individual compartments. We suggest that the contradictory findings with other compartmentalized muscles may be explained by differences in muscle-tendon anatomy and function.

Electrophysiological and functional signs of Guillain-Barré syndrome predicted by a multiscale neuromuscular computational model

Objective. The diagnosis of nerve disorders in humans has relied heavily on the measurement of electrical signals from nerves or muscles in response to electrical stimuli applied at appropriate locations on the body surface. The present study investigated the demyelinating subtype of Guillain-Barré syndrome using multiscale computational model simulations to verify how demyelination of peripheral axons may affect plantar flexion torque as well as the ongoing electromyogram (EMG) during voluntary isometric or isotonic contractions. Approach. Changes in axonal conduction velocities, mimicking those found in patients with the disease at different stages, were imposed on a multiscale computational neuromusculoskeletal model to simulate subjects performing unipodal plantar flexion force and position tasks. Main results. The simulated results indicated changes in the torque signal during the early phase of the disease while performing isotonic tasks, as well as in torque variability after partial conduction block while performing both isometric and isotonic tasks. Our results also indicated changes in the root mean square values and in the power spectrum of the soleus EMG signal as well as changes in the synchronisation index computed from the firing times of the active motor units. All these quantitative changes in functional indicators suggest that the adoption of such additional measurements, such as torques and ongoing EMG, could be used with advantage in the diagnosis and be relevant in providing extra information for the neurologist about the level of the disease. Significance. Our findings enrich the knowledge of the possible ways demyelination affects force generation and position control during plantarflexion. Moreover, this work extends computational neuroscience to computational neurology and shows the potential of biologically compatible neuromuscular computational models in providing relevant quantitative signs that may be useful for diagnosis in the clinic, complementing the tools traditionally used in neurological electrodiagnosis.

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

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 decomposition of electromyographical (EMG) signals. 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 single-compartment 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. A representative application of the method in MN-driven neuromuscular modelling is also presented. 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 neuromechanics of human MN pools, support future experimental investigations, and advance neuromuscular modelling for investigating the neural strategies controlling human voluntary contractions.

The control and training of single motor units in isometric tasks are constrained by a common input signal

Recent developments in neural interfaces enable the real-time and non-invasive tracking of motor neuron spiking activity. Such novel interfaces could provide a promising basis for human motor augmentation by extracting potentially high-dimensional control signals directly from the human nervous system. However, it is unclear how flexibly humans can control the activity of individual motor neurons to effectively increase the number of degrees of freedom available to coordinate multiple effectors simultaneously. Here, we provided human subjects (N = 7) with real-time feedback on the discharge patterns of pairs of motor units (MUs) innervating a single muscle (tibialis anterior) and encouraged them to independently control the MUs by tracking targets in a 2D space. Subjects learned control strategies to achieve the target-tracking task for various combinations of MUs. These strategies rarely corresponded to a volitional control of independent input signals to individual MUs during the onset of neural activity. Conversely, MU activation was consistent with a common input to the MU pair, while individual activation of the MUs in the pair was predominantly achieved by alterations in de-recruitment order that could be explained by history-dependent changes in motor neuron excitability. These results suggest that flexible MU recruitment based on independent synaptic inputs to single MUs is unlikely, although de-recruitment might reflect varying inputs or modulations in the neuron's intrinsic excitability.

Association between effective neural drive to the triceps surae and fluctuations in plantar-flexion torque during submaximal isometric contractions

What is the central question of this study? What is the association between the fluctuations in various estimates of effective neural drive to the triceps surae muscles and fluctuations in net plantar-flexion torque during steady submaximal contractions? What is the main finding and its importance? The fluctuations in estimates of effective neural drive to the triceps surae were moderately correlated with fluctuations in net torque at light and moderate plantar-flexion torques. Significant variability was observed in the association between neural drive and torque across participants, trials, short epochs of individual contractions, and varying motor unit number. ABSTRACT: The influence of effective neural drive on low-frequency fluctuations in torque during steady contractions can be estimated from the cumulative spike train (CST) or first principal component (FPC) of smoothed motor unit discharge rates obtained with high-density electromyography. However, the association between these estimates of total neural drive to synergist muscles and the fluctuations in net torque has not been investigated. We exposed the variability and compared the correlations between estimates of effective neural drive to the triceps surae muscles and fluctuations in plantar-flexion torque during steady contractions at 10% and 35% of maximal voluntary contraction (MVC) torque. Both neural drive estimates were moderately correlated with torque (CST, 0.55 ± 0.14, FPC, 0.58 ± 0.16) and highly correlated with one another (0.81 ± 0.1) during the 30-s steady contractions. There was substantial variability in cross-correlation values across participants, trials, and the 1-s and 5-s epochs of single contractions. Moreover, epoch duration significantly influenced cross-correlation values. Motor unit number was weakly associated with cross-correlation strength at 35% MVC (marginal R² 0.09 - 0.11; all p < 2.2×10^-5 ), but not at 10% MVC (all p > 0.37). Approximately one fifth of the variance in the coefficient of variation (CV) for torque was explained by CV for the CST estimate of neural drive (p = 6.6×10^-13 , R² = 0.21). Estimates of total neural drive to the synergistic triceps surae muscles obtained by pooling motor unit discharge times were moderately correlated with fluctuations in net plantar-flexion torque. This article is protected by copyright. All rights reserved.

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.

Synergistic Organization of Neural Inputs from Spinal Motor Neurons to Extrinsic and Intrinsic Hand Muscles

Our current understanding of synergistic muscle control is based on the analysis of muscle activities. Modules (synergies) in muscle coordination are extracted from electromyographic (EMG) signal envelopes. Each envelope indirectly reflects the neural drive received by a muscle; therefore, it carries information on the overall activity of the innervating motor neurons. However, it is not known whether the output of spinal motor neurons, whose number is orders of magnitude greater than the muscles they innervate, is organized in a low-dimensional fashion when performing complex tasks. Here, we hypothesized that motor neuron activities exhibit a synergistic organization in complex tasks and therefore that the common input to motor neurons results in a large dimensionality reduction in motor neuron outputs. To test this hypothesis, we factorized the output spike trains of motor neurons innervating 14 intrinsic and extrinsic hand muscles and analyzed the dimensionality of control when healthy individuals exerted isometric forces using seven grip types. We identified four motor neuron synergies, accounting for >70% of the variance of the activity of 54.1 ± 12.9 motor neurons, and we identified four functionally similar muscle synergies. However, motor neuron synergies better discriminated individual finger forces than muscle synergies and were more consistent with the expected role of muscles actuating each finger. Moreover, in a few cases, motor neurons innervating the same muscle were active in separate synergies. Our findings suggest a highly divergent net neural inputs to spinal motor neurons from spinal and supraspinal structures, contributing to the dimensionality reduction captured by muscle synergies.SIGNIFICANCE STATEMENT We addressed whether the output of spinal motor neurons innervating multiple hand muscles could be accounted for by a modular organization, i.e., synergies, previously described to account for the coordination of multiple muscles. We found that motor neuron synergies presented similar dimensionality (implying a >10-fold reduction in dimensionality) and structure as muscle synergies. Nonetheless, the synergistic behavior of subsets of motor neurons within a muscle was also observed. These results advance our understanding of how neuromuscular control arises from mapping descending inputs to muscle activation signals. We provide, for the first time, insights into the organization of neural inputs to spinal motor neurons which, to date, has been inferred through analysis of muscle synergies.

Greater fatigability and motor unit discharge variability in human type 2 diabetes

This study determined the discharge characteristics of motor units from two lower limb muscles before and after fatiguing exercise in people with type 2 diabetes (T2D) with no symptoms of polyneuropathy and activity‐matched controls. Seventeen people with T2D (65.0 ± 5.6 years; 8 women) and 17 controls (63.6 ± 4.5 years; 8 women) performed: (a) intermittent, isometric contractions at 50% maximal voluntary isometric contraction (MVIC) sustained to failure with the ankle dorsiflexors, and (b) a dynamic fatiguing task (30% MVIC load) for 6 min with the knee extensors. Before and after the fatiguing tasks, motor unit characteristics (including coefficient of variation (CV) of interspike intervals (ISI)) were quantified from high‐density electromyography and muscle contractile properties were assessed via electrical stimulation. Fatigability was ~50% greater for people with T2D than controls for the dorsiflexors (time‐to‐failure: 7.3 ± 4.1 vs. 14.3 ± 9.1 min, p = .010) and knee extensors (power reduction: 56.7 ± 11.9 vs. 31.5 ± 25.5%, p < .001). The CV of ISI was greater for the T2D than control group for the tibialis anterior (23.1 ± 11.0 vs. 21.3 ± 10.7%, p < .001) and vastus lateralis (27.8 ± 20.2 vs. 24.5 ± 16.1%, p = .011), but these differences did not change after the fatiguing exercises. People with T2D had greater reductions in the electrically evoked twitch amplitude of the dorsiflexors (8.5 ± 5.1 vs. 4.0 ± 3.4%·min^‐1, p = .013) and knee extensors (49.1 ± 10.0 vs. 31.8 ± 15.9%, p = .004) than controls. Although motor unit activity was more variable in people with T2D than controls, the greater fatigability of the T2D group for lower limb muscles was due to mechanisms involving disruption of contractile function of the exercising muscles rather than motor unit behavior.

Feedforward modulation of gamma motor neuron activity can improve motor command accuracy

Objective. Coactivation of gamma and alpha motor neuron activity ensures that muscle spindle responsiveness is maintained during muscle contractions. However, some evidence suggests that the activity of gamma motor neurons is phase-advanced with respect to that of alpha motor neurons during manual control tasks. We hypothesized that this might be a deliberate control strategy to maximize movement accuracy.Approach. Using a computational model of the neural activation of a muscle and its type Ia sensory feedback to the motor neurons, we systematically investigated the impact of the phase difference between oscillatory descending input to alpha and dynamic gamma motor neurons. Specifically, the amplification of the alpha motor neuron drive to the muscle was investigated as a function of the frequency of the synaptic input (1-9 Hz individually or superimposed) and the alpha-gamma phase difference (0-2π).Main results. Simulation results showed that when the phase advance of the dynamic gamma drive resulted in delays between muscle velocity and type Ia afferent feedback similar to those previously observed experimentally, low-frequency components (1 and 2 Hz) of the motor neuron synaptic input were amplified (gain up to 1.7). On the other hand, synaptic input at higher frequencies was unaffected.Significance. This finding suggests that by imposing a phase advance of the input to dynamic gamma motor neurons, components of the neural drive usually associated with voluntary control are amplified. In this way, our study suggests that this neural strategy increases the control-to-neural-noise ratio of the motor output during movement.

Force variability is mostly not motor noise: Theoretical implications for motor control

Variability in muscle force is a hallmark of healthy and pathological human behavior. Predominant theories of sensorimotor control assume 'motor noise' leads to force variability and its 'signal dependence' (variability in muscle force whose amplitude increases with intensity of neural drive). Here, we demonstrate that the two proposed mechanisms for motor noise (i.e. the stochastic nature of motor unit discharge and unfused tetanic contraction) cannot account for the majority of force variability nor for its signal dependence. We do so by considering three previously underappreciated but physiologically important features of a population of motor units: 1) fusion of motor unit twitches, 2) coupling among motoneuron discharge rate, cross-bridge dynamics, and muscle mechanics, and 3) a series-elastic element to account for the aponeurosis and tendon. These results argue strongly against the idea that force variability and the resulting kinematic variability are generated primarily by 'motor noise.' Rather, they underscore the importance of variability arising from properties of control strategies embodied through distributed sensorimotor systems. As such, our study provides a critical path toward developing theories and models of sensorimotor control that provide a physiologically valid and clinically useful understanding of healthy and pathologic force variability.

Muscles from the same muscle group do not necessarily share common drive: evidence from the human triceps surae

In this study, we demonstrated that the three muscles composing the human triceps surae share minimal common drive during isometric contractions. Our results suggest that reducing the number of effectively controlled degrees of freedom may not always be the strategy used by the central nervous system to control movements. Independent control of some, but not all, synergist muscles may allow for more flexible control to comply with secondary goals (e.g., joint stabilization).

Spinal motoneurons of the human newborn are highly synchronized during leg movements

Motoneurons of neonatal rodents show synchronous activity that modulates the development of the neuromuscular system. However, the characteristics of the activity of human neonatal motoneurons are largely unknown. Using a noninvasive neural interface, we identified the discharge timings of individual spinal motoneurons in human newborns. We found highly synchronized activities of motoneurons of the tibialis anterior muscle, which were associated with fast leg movements. Although neonates' motor units exhibited discharge rates similar to those of adults, their synchronization was significantly greater than in adults. Moreover, neonatal motor units showed coherent oscillations in the delta band, which is directly translated into force generation. These results suggest that motoneuron synchronization in human neonates might be an important mechanism for controlling fast limb movements, such as those of primitive reflexes. In addition to help revealing mechanisms of development, the proposed neural interface might monitor children at risk of developing motor disorders.

Control of Spinal Motoneurons by Feedback From a Non-Invasive Real-Time Interface

Interfacing with human neural cells during natural tasks provides the means for investigating the working principles of the central nervous system and for developing human-machine interaction technologies. Here we present a computationally efficient non-invasive, real-time interface based on the decoding of the activity of spinal motoneurons from wearable high-density electromyogram (EMG) sensors. We validate this interface by comparing its decoding results with those obtained with invasive EMG sensors and offline decoding, as reference. Moreover, we test the interface in a series of studies involving real-time feedback on the behavior of a relatively large number of decoded motoneurons. The results on accuracy, intuitiveness, and stability of control demonstrate the possibility of establishing a direct non-invasive interface with the human spinal cord without the need for extensive training. Moreover, in a control task, we show that the accuracy in control of the proposed neural interface may approach that of the natural control of force. These results are the first that demonstrate the feasibility and validity of a non-invasive direct neural interface with the spinal cord, with wearable systems and matching the neural information flow of natural movements.

Interfacing With Alpha Motor Neurons in Spinal Cord Injury Patients Receiving Trans-spinal Electrical Stimulation

Trans-spinal direct current stimulation (tsDCS) provides a non-invasive, clinically viable approach to potentially restore physiological neuromuscular function after neurological impairment, e.g., spinal cord injury (SCI). Use of tsDCS has been hampered by the inability of delivering stimulation patterns based on the activity of neural targets responsible to motor function, i.e., α-motor neurons (α-MNs). State of the art modeling and experimental techniques do not provide information about how individual α-MNs respond to electrical fields. This is a major element hindering the development of neuro-modulative technologies highly tailored to an individual patient. For the first time, we propose the use of a signal-based approach to infer tsDCS effects on large α-MNs pools in four incomplete SCI individuals. We employ leg muscles spatial sampling and deconvolution of high-density fiber electrical activity to decode accurate α-MNs discharges across multiple lumbosacral segments during isometric plantar flexion sub-maximal contractions. This is done before, immediately after and 30 min after sub-threshold cathodal stimulation. We deliver sham tsDCS as a control measure. First, we propose a new algorithm for removing compromised information from decomposed α-MNs spike trains, thereby enabling robust decomposition and frequency-domain analysis. Second, we propose the analysis of α-MNs spike trains coherence (i.e., frequency-domain) as an indicator of spinal response to tsDCS. Results showed that α-MNs spike trains coherence analysis sensibly varied across stimulation phases. Coherence analyses results suggested that the common synaptic input to α-MNs pools decreased immediately after cathodal tsDCS with a persistent effect after 30 min. Our proposed non-invasive decoding of individual α-MNs behavior may open up new avenues for the design of real-time closed-loop control applications including both transcutaneous and epidural spinal electrical stimulation where stimulation parameters are adjusted on-the-fly.

Estimation of self-sustained activity produced by persistent inward currents using firing rate profiles of multiple motor units in humans

Persistent inward calcium and sodium currents (I_P) activated during motoneuron recruitment help synaptic inputs maintain self-sustained firing until derecruitment. Here, we estimate the contribution of the I_P to self-sustained firing in human motoneurons of varying recruitment threshold by measuring the difference in synaptic input needed to maintain minimal firing once the I_P is fully activated compared with the larger synaptic input required to initiate firing before full I_P activation. Synaptic input to ≈20 dorsiflexor motoneurons simultaneously recorded during ramp contractions was estimated from firing profiles of motor units decomposed from high-density surface electromyography (EMG). To avoid errors introduced when using high-threshold units firing in their nonlinear range, we developed methods where the lowest threshold units firing linearly with force were used to construct a composite (control) unit firing rate profile to estimate synaptic input to higher threshold (test) units. The difference in the composite firing rate (synaptic input) at the time of test unit recruitment and derecruitment (ΔF = F_recruit - F_derecruit) was used to measure I_P amplitude that sustained firing. Test units with recruitment thresholds 1-30% of maximum had similar ΔF values, which likely included both slow and fast motor units activated by small and large motoneurons, respectively. This suggests that the portion of the I_P that sustains firing is similar across a wide range of motoneuron sizes.NEW & NOTEWORTHY A new method of estimating synaptic drive to multiple, simultaneously recorded motor units provides evidence that the portion of the depolarizing drive from persistent inward currents that contributes to self-sustained firing is similar across motoneurons of different sizes.

Fatigue-related modulation of low-frequency common drive to motor units

PURPOSE

This study investigated fatigue-related modulation of common neural inputs to motor units (MUs) under 5 Hz, which determines force precision control.

METHODS

Twenty-seven adults performed a sequence of fatiguing contractions. The participants were assessed with a static isometric index abduction at 20% maximal voluntary contraction in the pre-test and post-test. Discharge characteristics of MUs of the first dorsal interosseous muscle were analyzed with decomposed EMG signals.

RESULTS

Along with increases in the mean (58.40 ± 11.76 ms → 62.55 ± 10.83 ms, P = 0.029) and coefficient of variation (0.204 ± .014 → 0.215 ± 0.017, P = 0.002) in inter-spike intervals, the fatiguing contraction caused reductions in the mean frequency (16.84 ± 3.31 Hz → 15.59 ± 3.21 Hz, P = 0.027) and spectral dispersions (67.54 ± 4.49 → 62.64 ± 6.76 Hz, P = 0.007) of common neural drive, as estimated with smoothed cumulative motor unit spike trains (SCMUSTs). Stabilogram diffusion analysis of SCMUSTs revealed significant fatigue-related reductions in the long-term effective diffusion coefficient (1.91 ± 0.77 Hz²/s → 1.61 ± 0.61 Hz²/s, P = 0.020) and long-term scaling exponent (0.480 ± 0.013 Hz²/s → 0.471 ± 0.017 Hz²/s, P = 0.014). After fatiguing contraction, mutual information of force fluctuations and SCMUSTs was augmented roughly by 12.95% (P = 0.041).

CONCLUSIONS

Muscular fatigue could compress and shift the low-frequency common drive to MUs toward lower spectral bands, thereby enhancing transmission of twitch forces through the muscle-tendon complex with a low-pass filter property. The fatigue-induced changes involve increased closed-loop control of the common modulation of MU discharge rates.

Characterization of Forearm Muscle Activation in Duchenne Muscular Dystrophy via High-Density Electromyography: A Case Study on the Implications for Myoelectric Control

Duchenne muscular dystrophy (DMD) is a genetic disorder that results in progressive muscular degeneration. Although medical advances increased their life expectancy, DMD individuals are still highly dependent on caregivers. Hand/wrist function is central for providing independence, and robotic exoskeletons are good candidates for effectively compensating for deteriorating functionality. Robotic hand exoskeletons require the accurate decoding of motor intention typically via surface electromyography (sEMG). Traditional low-density sEMG was used in the past to explore the muscular activations of individuals with DMD; however, it cannot provide high spatial resolution. This study characterized, for the first time, the forearm high-density (HD) electromyograms of three individuals with DMD while performing seven hand/wrist-related tasks and compared them to eight healthy individuals (all data available online). We looked into the spatial distribution of HD-sEMG patterns by using principal component analysis (PCA) and also assessed the repeatability and the amplitude distributions of muscle activity. Additionally, we used a machine learning approach to assess DMD individuals' potentials for myocontrol. Our analysis showed that although participants with DMD were able to repeat similar HD-sEMG patterns across gestures (similarly to healthy participants), a fewer number of electrodes was activated during their gestures compared to the healthy participants. Additionally, participants with DMD activated their muscles close to maximal contraction level (0.63 ± 0.23), whereas healthy participants had lower normalized activations (0.26 ± 0.2). Lastly, participants with DMD showed on average fewer PCs (3), explaining 90% of the complete gesture space than the healthy (5). However, the ability of the DMD participants to produce repeatable HD-sEMG patterns was unexpectedly comparable to that of healthy participants, and the same holds true for their offline myocontrol performance, disproving our hypothesis and suggesting a clear potential for the myocontrol of wearable exoskeletons. Our findings present evidence for the first time on how DMD leads to progressive alterations in hand/wrist motor control in DMD individuals compared to healthy. The better understanding of these alterations can lead to further developments for the intuitive and robust myoelectric control of active hand exoskeletons for individuals with DMD.

Neurophysiological correlates of force control improvement induced by sinusoidal vibrotactile stimulation

OBJECTIVE

An optimal level of vibrotactile stimulation has been shown to improve sensorimotor control in healthy and diseased individuals. However, the underlying neurophysiological mechanisms behind the enhanced motor performance caused by vibrotactile stimulation are yet to be fully understood. Therefore, here we aim to evaluate the effect of a cutaneous vibration on the firing behavior of motor units in a condition of improved force steadiness.

APPROACH

Participants performed a visuomotor task, which consisted of low-intensity isometric contractions of the first dorsal interosseous (FDI) muscle, while sinusoidal (175 Hz) vibrotactile stimuli with different intensities were applied to the index finger. High-density surface electromyogram was recorded from the FDI muscle, and a decomposition algorithm was used to extract the motor unit spike trains. Additionally, computer simulations were performed using a multiscale neuromuscular model to provide a potential explanation for the experimental findings.

MAIN RESULTS

Experimental outcomes showed that an optimal level of vibration significantly improved force steadiness (estimated as the coefficient of variation of force). The decreased force variability was accompanied by a reduction in the variability of the smoothed cumulative spike train (as an estimation of the neural drive to the muscle), and the proportion of common inputs to the FDI motor nucleus. However, the interspike interval variability did not change significantly with the vibration. A mathematical approach, together with computer simulation results suggested that vibrotactile stimulation would reduce the variance of the common synaptic input to the motor neuron pool, thereby decreasing the low frequency fluctuations of the neural drive to the muscle and force steadiness.

SIGNIFICANCE

Our results demonstrate that the decreased variability in common input accounts for the enhancement in force control induced by vibrotactile stimulation.

A wearable neural interface for detecting and decoding attempted hand movements in a person with tetraplegia

We are developing a wearable neural interface based on high-density surface electromyography (HDEMG) for detecting and decoding signals from spared motor units in the forearms of people with tetraplegia after spinal cord injury (SCI). A lightweight, form-fitting garment containing 150 disc electrodes and covering the entire forearm was used to map the myoelectric activity of forearm muscles during a wide range of voluntary tasks of a person with chronic tetraplegia after SCI (C5 motor and C6 sensory American Spinal Injury Association Impairment Scale B spinal cord injury). Despite exhibiting no overt finger motion, myoelectric signals were detectable for attempted movements of individual digits and were highly discriminable. Motor unit decomposition was used to identify the activity of >30 motor neurons, active specifically during rotation, pronation of the wrist (4 units), and flexion of the elbow joint (7 units), and during attempted movements of individual hand digits (1-5 units). In addition, we performed a neural connectivity analysis based on the power of the common oscillations of the identified motor neurons in the delta (~5Hz), alpha (~6-12 Hz), and beta bands (~15-30 Hz). This analysis showed clear common synaptic inputs to the identified motor neurons in all the analyzed frequency bands. This neural interface offers a new potential for the control of assistive technologies, whereby the motor neurons spared after SCI may serve as a direct readout of motor intent that allows proportional control over several distinct degrees of freedom. Moreover, this framework can be used to study the reorganization and recovery of spinal networks after injury and rehabilitation.

The human central nervous system transmits common synaptic inputs to distinct motor neuron pools during non-synergistic digit actions

KEY POINTS

Neural connectivity between distinct motor neuronal modules in the spinal cord is classically studied through electrical stimulation or multi-muscle EMG recordings. We quantified the strength of correlation in the activity of two distinct populations of motor neurons innervating the thenar and first dorsal interosseous muscles during tasks that required the two hand muscles to exert matched or un-matched forces in different directions. We show that when the two hand muscles are concurrently activated, synaptic input to the two motor neuron pools is shared across all frequency bandwidths (representing cortical and spinal input) associated with force control. The observed connectivity indicates that motor neuron pools receive common input even when digit actions do not belong to a common behavioural repertoire.

ABSTRACT

Neural connectivity between distinct motor neuronal modules in the spinal cord is classically studied through electrical stimulation or multi-muscle EMG recordings. Here we quantify the strength of correlation in the activity of two distinct populations of motor neurons innervating the thenar and first dorsal interosseous muscles in humans during voluntary contractions. To remove confounds associated with previous studies, we used a task that required the two hand muscles to exert matched or un-matched forces in different directions. Despite the force production task consisting of uncommon digit force coordination patterns, we found that synaptic input to motor neurons is shared across all frequency bands, reflecting cortical and spinal inputs associated with force control. The coherence between discharge timings of the two pools of motor neurons was significant at the delta (0-5 Hz), alpha (5-15 Hz) and beta (15-35 Hz) bands (P < 0.05). These results suggest that correlated input to motor neurons of two hand muscles can occur even during tasks not belonging to a common behavioural repertoire and despite lack of common innervation. Moreover, we show that the extraction of activity from motor neurons during voluntary force control removes cross-talk associated with global EMG recordings, thus allowing direct in vivo interrogation of spinal motor neuron activity.

Anti-phase cocontraction practice attenuates in-phase low-frequency oscillations between antagonistic muscles as assessed with phase coherence

Voluntary contraction of skeletal muscles involves common in-phase neural oscillations in low frequencies (around 1-2 Hz) across muscles. The purpose of this study was to determine if anti-phase antagonistic cocontraction practice can attenuate the occurrence of in-phase low-frequency oscillations in antagonistic muscle activity. For this purpose, we determined the probability density function of phase coherence in surface electromyogram (EMG) between antagonistic muscles. Healthy young adults were assigned to one of three intervention groups. They performed an isometric transient and steady cocontraction test with elbow flexors and extensors before and after a session of distinct intervention. In the Cocontraction group, subjects practiced alternating anti-phase isometric cocontraction with the flexors and extensors concurrently. In the Contraction group, subjects practiced alternating isometric contraction levels with flexors or extensors independently. Subjects in the Control group did not perform motor practice. The occurrence of in-phase coherence < 3 Hz during the cocontraction test (including transient and steady portions) was determined from the probability density function of phase coherence in rectified EMG between pairs of elbow flexor and extensor muscles. The change in the probability of in-phase coherence after the intervention period was greatest in the Cocontraction group, followed by Contraction group, and then Control group, on average. The Cocontraction group showed significantly greater reductions than the Control group across the cocontraction test portions. The results suggest that a session of anti-phase cocontraction practice can consistently attenuate the occurrence of in-phase low-frequency oscillations between cocontracting antagonistic muscles across steady and non-steady cocontractions in healthy young adults.

Exogenous neuromodulation of spinal neurons induces beta-band coherence during self-sustained discharge of hind limb motor unit populations

The spontaneous or self-sustained discharge of spinal motoneurons can be observed in both animals and humans. Although the origins of this self-sustained discharge are not fully known, it can be generated by activation of persistent inward currents intrinsic to the motoneuron. If self-sustained discharge is generated exclusively through this intrinsic mechanism, the discharge of individual motor units will be relatively independent of one another. Alternatively, if increased activation of premotor circuits underlies this prolonged discharge of spinal motoneurons, we would expect correlated activity among motoneurons. Our aim is to assess potential synaptic drive by quantifying coherence during self-sustained discharge of spinal motoneurons. Electromyographic activity was collected from 20 decerebrate animals using a 64-channel electrode grid placed on the isolated soleus muscle before and following intrathecal administration of methoxamine, a selective α₁-noradrenergic agonist. Sustained muscle activity was recorded and decomposed into the discharge times of ~10-30 concurrently active individual motor units. Consistent with previous reports, the self-sustained discharge of motor units occurred at low mean discharge rates with low-interspike variability. Before methoxamine administration, significant low-frequency coherence (<2 Hz) was observed, while minimal coherence was observed within higher frequency bands. Following intrathecal administration of methoxamine, increases in motor unit discharge rates and strong coherence in both the low-frequency and 15- to 30-Hz beta bands were observed. These data demonstrate beta-band coherence among motor units can be observed through noncortical mechanisms and that neuromodulation of spinal/brainstem neurons greatly influences coherent discharge within spinal motor pools.NEW & NOTEWORTHY The correlated discharge of spinal motoneurons is often used to describe the input to the motor pool. We demonstrate spinal/brainstem neurons devoid of cortical input can generate correlated motor unit discharge in the 15- to 30-Hz beta band, which is amplified through neuromodulation. Activity in the beta band is often ascribed to cortical drive in humans; however, these data demonstrate the capability of the mammalian segmental motor system to generate and modulate this coherent state of motor unit discharge.

The relative strength of common synaptic input to motor neurons is not a determinant of the maximal rate of force development in humans

Correlation between motor unit discharge times, often referred to as motor unit synchronization, is determined by common synaptic input to motor neurons. Although it has been largely speculated that synchronization should influence the rate of force development, the association between the degree of motor unit synchronization and rapid force generation has not been determined. In this study, we examined this association with both simulations and experimental motor unit recordings. The analysis of experimental motor unit discharges from the tibialis anterior muscle of 20 healthy individuals during rapid isometric contractions revealed that the average motor unit discharge rate was associated with the rate of force development. Moreover, the extent of motor unit synchronization was entirely determined by the average motor unit discharge rate ( R > 0.7, P < 0.0001). The simulation model demonstrated that the relative proportion of common synaptic input received by motor neurons, which determines motor unit synchronization, does not influence the rate of force development ( R = 0.03, P > 0.05). Nonetheless, the estimates of correlation between motor unit spike trains were significantly correlated with the rate of force generation ( R > 0.8, P < 0.0001). These results indicate that the average motor unit discharge rate, but not the degree of motor unit synchronization, contributes to most of the variance of human contractile speed among individuals. In addition, estimates of correlation between motor unit discharge times depend strongly on the number of identified motor units and therefore are not indicative of the strength of common input.

NEW & NOTEWORTHY It is commonly assumed that motor unit synchronization has an impact on the rate of force development of a muscle. Here we present computer simulations and experimental data of human tibialis anterior motor units during rapid contractions that show that motor unit synchronization is not a determinant of the rate of force production. This conclusion clarifies the neural determinants of rapid force generation.

Multiscale modeling of the neuromuscular system: Coupling neurophysiology and skeletal muscle mechanics

Mathematical models and computer simulations have the great potential to substantially increase our understanding of the biophysical behavior of the neuromuscular system. This, however, requires detailed multiscale, and multiphysics models. Once validated, such models allow systematic in silico investigations that are not necessarily feasible within experiments and, therefore, have the ability to provide valuable insights into the complex interrelations within the healthy system and for pathological conditions. Most of the existing models focus on individual parts of the neuromuscular system and do not consider the neuromuscular system as an integrated physiological system. Hence, the aim of this advanced review is to facilitate the prospective development of detailed biophysical models of the entire neuromuscular system. For this purpose, this review is subdivided into three parts. The first part introduces the key anatomical and physiological aspects of the healthy neuromuscular system necessary for modeling the neuromuscular system. The second part provides an overview on state-of-the-art modeling approaches representing all major components of the neuromuscular system on different time and length scales. Within the last part, a specific multiscale neuromuscular system model is introduced. The integrated system model combines existing models of the motor neuron pool, of the sensory system and of a multiscale model describing the mechanical behavior of skeletal muscles. Since many sub-models are based on strictly biophysical modeling approaches, it closely represents the underlying physiological system and thus could be employed as starting point for further improvements and future developments. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models.