The optimal neural strategy for a stable motor task requires a compromise between level of muscle cocontraction and synaptic gain of afferent feedback

Oscillatory drive is increased and steadiness is impaired when torque but not EMG is matched during a fatiguing contraction

The increasing descending drive needed to sustain submaximal isometric torque makes it difficult to isolate fatigue-related changes to neural excitability because evoked electromyography (EMG) responses are influenced by the relative activation of the motoneuron pool. Hence, it is becoming increasingly common to investigate fatigue using a sustained contraction with maintained output from the motoneuron pool; i.e., matched-surface EMG. Although this approach controls motoneuron pool output, it is unknown how cortical contributions to ongoing muscle activity or common modulation between muscles are altered during a matched-EMG contraction. During separate visits, 16 participants performed a sustained 10-min isometric elbow flexion contraction at 20% maximal voluntary contraction (MVC) torque or the level of integrated biceps brachii EMG recorded at 20% MVC torque. Electroencephalographic and surface EMG recordings were obtained from the sensorimotor area and biceps and triceps brachii, respectively. The matched-torque contraction caused increased corticomuscular coherence for biceps brachii (∼75%) and intermuscular coherence (∼97%), but reduced MVC torque (∼33%), voluntary activation (∼9%), and torque steadiness (∼83%). In contrast, the matched-EMG contraction caused reduced MVC torque (∼21%), with no change in coherence, voluntary activation, or EMG steadiness. Furthermore, participants reported higher ratings of perceived effort scores by 6 min into the matched-torque compared with matched-EMG contraction. These findings indicate that, during a matched-torque contraction, the nervous system enhanced common oscillatory activity to continue the task, but this did not prevent degradation of performance (torque steadiness). In contrast, when motoneuron pool output was maintained, other neural strategies were used to preserve muscle output.NEW & NOTEWORTHY Sustained electromyography (EMG) tasks offer valuable insights into fatigue-related changes to neural excitability, yet nothing is known about communication between the cortex and active muscles. A 10-min matched-EMG contraction reduced maximal torque-generating capacity but did not alter corticomuscular coherence (CMC), intermuscular coherence (IMC), or task performance (EMG steadiness). In contrast, a matched-torque contraction increased CMC and IMC yet further impaired maximal torque and compromised torque steadiness, which reveals unique neural strategies for the two tasks.

Personalized Alpha-Motoneuron Pool Models Driven by Neural Data Encode the Mechanisms Controlling Rate of Force Development

The central nervous system employs distinct motor control strategies depending on task demands. Accordingly, the activity of alpha-motoneuron (MN) pools innervating skeletal muscle fibers is modulated based on muscle force and rate of force development (RFD). In human subjects, biophysical MN models enable inferring in vivo the neural processes (e.g., synaptic input, activity of the entire MN pool, etc.) underlying this modulation, which are otherwise challenging to measure experimentally. Due to unique neurophysiological characteristics of individuals, personalizing these models is essential to study motor control in humans. Therefore, this work studied the mechanisms involved in the modulation of RFD using person-specific MN pool models driven by in vivo common synaptic input estimates (i.e., derived from surface high-density electromyography). Specifically, we assessed how in vivo MN activity changed across RFD and muscle force. This included modulation of recruitment and rate coding in the complete MN pool, as well as model-based estimates of excitatory synaptic gains ( ∆ IF). We found RFD-specific changes in MN activity associated to changes in ∆ IF. Moreover, we showed that MN pool models driven by RFD-specific ∆ IFs reproduced in vivo MN firing features and associated force profiles at different RFDs. Altogether, this work represents a step towards modelling the mechanisms of force generation in humans and creating person-specific models of the spinal circuitry. This will open a window for studying in vivo human neuromechanics and motor restoring interventions.

Lower limb suspension induces threshold-specific alterations of motor units properties that are reversed by active recovery

PURPOSE

This study aimed to non-invasively test the hypothesis that (a) short-term lower limb unloading would induce changes in the neural control of force production (based on motor units (MUs) properties) in the vastus lateralis muscle and (b) possible changes are reversed by active recovery (AR).

METHODS

Ten young males underwent 10 days of unilateral lower limb suspension (ULLS) followed by 21 days of AR. During ULLS, participants walked exclusively on crutches with the dominant leg suspended in a slightly flexed position (15°-20°) and with the contralateral foot raised by an elevated shoe. The AR was based on resistance exercise (leg press and leg extension) and executed at 70% of each participant's 1 repetition maximum, 3 times/week. Maximal voluntary isometric contraction (MVC) of knee extensors and MUs properties of the vastus lateralis muscle were measured at baseline, after ULLS, and after AR. MUs were identified using high-density electromyography during trapezoidal isometric contractions at 10%, 25%, and 50% of the current MVC, and individual MUs were tracked across the 3 data collection points.

RESULTS

We identified 1428 unique MUs, and 270 of them (18.9%) were accurately tracked. After ULLS, MVC decreased by 29.77%, MUs absolute recruitment/derecruitment thresholds were reduced at all contraction intensities (with changes between the 2 variables strongly correlated), while discharge rate was reduced at 10% and 25% but not at 50% MVC. Impaired MVC and MUs properties fully recovered to baseline levels after AR. Similar changes were observed in the pool of total as well as tracked MUs.

CONCLUSION

Our novel results demonstrate, non-invasively, that 10 days of ULLS affected neural control predominantly by altering the discharge rate of lower-threshold but not of higher-threshold MUs, suggesting a preferential impact of disuse on motoneurons with a lower depolarization threshold. However, after 21 days of AR, the impaired MUs properties were fully restored to baseline levels, highlighting the plasticity of the components involved in neural control.

Motor Unit Firing Properties During Force Control Task and Associations With Neurological Tests in Children

The present study aimed to clarify the development of motor unit (MU) firing properties and the association between those neural properties and force steadiness (FS)/neurological tests in 6- to 12-year-old children. Fifty-eight school-aged children performed maximal voluntary knee extension contraction, a submaximal FS test at 10% of maximal voluntary knee extension contraction, knee extension reaction time to light stimulus test, and single-leg standing test, and data from 38 children who passed the criteria were subject to analysis. During the FS test, high-density surface electromyography was recorded from the vastus lateralis muscle to identify individual MU firing activity. FS was improved with an increase in age (r = -.540, P < .001). The MU firing rate (MUFR) was significantly decreased with an increase in age (r = -.343, P = .035). MUFR variability was not associated with age. Although there was no significant correlation between FS and MUFR, FS was significantly correlated with MUFR variability even after adjustment for the effect of age (r = .551, P = .002). Neither the reaction time nor the single-leg standing test was correlated with any MU firing properties. These findings suggest that MUFR variability makes an important contribution to precise force control in children but does not naturally develop with age.

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.

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.

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.

Computational evidence for nonlinear feedforward modulation of fusimotor drive to antagonistic co-contracting muscles

The sensorimotor integration during unconstrained reaching movements in the presence of variable environmental forces remains poorly understood. The objective of this study was to quantify how much the primary afferent activity of muscle spindles can contribute to shaping muscle coactivation patterns during reaching movements with complex dynamics. To achieve this objective, we designed a virtual reality task that guided healthy human participants through a set of planar reaching movements with controlled kinematic and dynamic conditions that were accompanied by variable muscle co-contraction. Next, we approximated the Ia afferent activity using a phenomenological model of the muscle spindle and muscle lengths derived from a musculoskeletal model. The parameters of the spindle model were altered systematically to evaluate the effect of fusimotor drive on the shape of the temporal profile of afferent activity during movement. The experimental and simulated data were analyzed with hierarchical clustering. We found that the pattern of co-activation of agonistic and antagonistic muscles changed based on whether passive forces in each movement played assistive or resistive roles in limb dynamics. The reaching task with assistive limb dynamics was associated with the most muscle co-contraction. In contrast, the simulated Ia afferent profiles were not changing between tasks and they were largely reciprocal with homonymous muscle activity. Simulated physiological changes to the fusimotor drive were not sufficient to reproduce muscle co-contraction. These results largely rule out the static set and α-γ coactivation as the main types of fusimotor drive that transform the monosynaptic Ia afferent feedback into task-dependent co-contraction of antagonistic muscles. We speculate that another type of nonlinear transformation of Ia afferent signals that is independent of signals modulating the activity of α motoneurons is required for Ia afferent-based co-contraction. This transformation could either be applied through a complex nonlinear profile of fusimotor drive that is not yet experimentally observed or through presynaptic inhibition.

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.

Amplitude cancellation influences the association between frequency components in the neural drive to muscle and the rectified EMG signal

The rectified surface EMG signal is commonly used as an estimator of the neural drive to muscles and therefore to infer sources of synaptic input to motor neurons. Loss of EMG amplitude due to the overlap of motor unit action potentials (amplitude cancellation), however, may distort the spectrum of the rectified EMG and thereby its correlation with the neural drive. In this study, we investigated the impact of amplitude cancelation on this correlation using analytical derivations and a computational model of motor neuron activity, force, and the EMG signal. First, we demonstrated analytically that an ideal rectified EMG signal without amplitude cancellation (EMG_nc) is superior to the actual rectified EMG signal as estimator of the neural drive to muscle. This observation was confirmed by the simulations, as the average coefficient of determination (r²) between the neural drive in the 1–30 Hz band and EMG_nc (0.59±0.08) was matched by the correlation between the rectified EMG and the neural drive only when the level of amplitude cancellation was low (<40%) at low contraction levels (<5% of maximum voluntary contraction force; MVC). This correlation, however, decreased linearly with amplitude cancellation (r = -0.83) to values of r² <0.2 at amplitude cancellation levels >60% (contraction levels >15% MVC). Moreover, the simulations showed that a stronger (i.e. more variable) neural drive implied a stronger correlation between the rectified EMG and the neural drive and that amplitude cancellation distorted this correlation mainly for low-frequency components (<5 Hz) of the neural drive. In conclusion, the results indicate that amplitude cancellation distorts the spectrum of the rectified EMG signal. This implies that valid use of the rectified EMG as an estimator of the neural drive requires low contraction levels and/or strong common synaptic input to the motor neurons.

The rectified surface EMG signal is commonly used to analyze the neural activation of muscles. However, since this signal is most often exposed to so-called amplitude cancellation (loss of EMG amplitude due to overlap of positive and negative phases of different motor unit action potentials), the frequency content of the rectified EMG may not fully reflect that of the neural drive to the muscle. In this study we prove this notion analytically and demonstrate, using simulations, that the rectified EMG signal accurately reflects the neural drive to the muscle only in a limited set of conditions. Specifically, these conditions include low contraction levels and/or high variability of the neural drive. In other conditions, the rectified EMG signal from a muscle is a poor predictor of its neural input. This finding has potentially large implications for the way neural drive to muscles and neural connectivity (e.g. across muscles or between the brain and a muscle) should be analyzed.

Cardinal features of involuntary force variability can arise from the closed-loop control of viscoelastic afferented muscles

Involuntary force variability below 15 Hz arises from, and is influenced by, many factors including descending neural drive, proprioceptive feedback, and mechanical properties of muscles and tendons. However, their potential interactions that give rise to the well-structured spectrum of involuntary force variability are not well understood due to a lack of experimental techniques. Here, we investigated the generation, modulation, and interactions among different sources of force variability using a physiologically-grounded closed-loop simulation of an afferented muscle model. The closed-loop simulation included a musculotendon model, muscle spindle, Golgi tendon organ (GTO), and a tracking controller which enabled target-guided force tracking. We demonstrate that closed-loop control of an afferented musculotendon suffices to replicate and explain surprisingly many cardinal features of involuntary force variability. Specifically, we present 1) a potential origin of low-frequency force variability associated with co-modulation of motor unit firing rates (i.e.,'common drive'), 2) an in-depth characterization of how proprioceptive feedback pathways suffice to generate 5-12 Hz physiological tremor, and 3) evidence that modulation of those feedback pathways (i.e., presynaptic inhibition of Ia and Ib afferents, and spindle sensitivity via fusimotor drive) influence the full spectrum of force variability. These results highlight the previously underestimated importance of closed-loop neuromechanical interactions in explaining involuntary force variability during voluntary 'isometric' force control. Furthermore, these results provide the basis for a unifying theory that relates spinal circuitry to various manifestations of altered involuntary force variability in fatigue, aging and neurological disease.

Physiological tremor increases when skeletal muscle is shortened: implications for fusimotor control

KEY POINTS

In tonic, isometric, plantarflexion contractions, physiological tremor increases as the ankle joint becomes plantarflexed. Modulation of physiological tremor as a function of muscle stretch differs from that of the stretch reflex amplitude. Amplitude of physiological tremor may be altered as a function of reflex pathway gains. Healthy humans likely increase their γ-static fusimotor drive when muscles shorten. Quantification of physiological tremor by manipulation of joint angle may be a useful experimental probe of afferent gains and/or the integrity of automatic fusimotor control.

ABSTRACT

The involuntary force fluctuations associated with physiological (as distinct from pathological) tremor are an unavoidable component of human motor control. While the origins of physiological tremor are known to depend on muscle afferentation, it is possible that the mechanical properties of muscle-tendon systems also affect its generation, amplification and maintenance. In this paper, we investigated the dependence of physiological tremor on muscle length in healthy individuals. We measured physiological tremor during tonic, isometric plantarflexion torque at 30% of maximum at three ankle angles. The amplitude of physiological tremor increased as calf muscles shortened in contrast to the stretch reflex whose amplitude decreases as muscle shortens. We used a published closed-loop simulation model of afferented muscle to explore the mechanisms responsible for this behaviour. We demonstrate that changing muscle lengths does not suffice to explain our experimental findings. Rather, the model consistently required the modulation of  γ-static fusimotor drive to produce increases in physiological tremor with muscle shortening - while successfully replicating the concomitant reduction in stretch reflex amplitude. This need to control γ-static fusimotor drive explicitly as a function of muscle length has important implications. First, it permits the amplitudes of physiological tremor and stretch reflex to be decoupled. Second, it postulates neuromechanical interactions that require length-dependent γ drive modulation to be independent from α drive to the parent muscle. Lastly, it suggests that physiological tremor can be used as a simple, non-invasive measure of the afferent mechanisms underlying healthy motor function, and their disruption in neurological conditions.

Voluntary activation and variability during maximal dynamic contractions with aging

Whether reduced supraspinal activation contributes to age-related reductions in maximal torque during dynamic contractions is not known. The purpose was to determine whether there are age differences in voluntary activation and its variability when assessed with stimulation at the motor cortex and the muscle during maximal isometric, concentric, and eccentric contractions. Thirty young (23.6 ± 4.1 years) and 31 old (69.0 ± 5.2 years) adults performed maximal isometric, shortening (concentric) and lengthening (eccentric) contractions with the elbow flexor muscles. Maximal isometric contractions were performed at 90° elbow flexion and dynamic contractions at a velocity of 60°/s. Voluntary activation was assessed by superimposing an evoked contraction with transcranial magnetic stimulation (TMS) or with electrical stimulation over the muscle during maximal voluntary contractions (MVCs). Old adults had lower MVC torque during isometric (- 17.9%), concentric (- 19.7%), and eccentric (- 9.9%) contractions than young adults, with less of an age difference for eccentric contractions. Voluntary activation was similar between the three contraction types when assessed with TMS and electrical stimulation, with no age group differences. Old adults, however, were more variable in voluntary activation than young (standard deviation 0.99 ± 0.47% vs. 0.73 ± 0.43%, respectively) to both the motor cortex and muscle, and had greater coactivation of the antagonist muscles during dynamic contractions. Thus, the average voluntary activation to the motor cortex and muscle did not differ with aging; however, supraspinal activation was more variable during maximal dynamic and isometric contractions in the old adults. Lower predictability of voluntary activation may indicate subclinical changes in the central nervous system with advanced aging.

Evidence of splinting in low back pain? A systematic review of perturbation studies

PURPOSE

The purpose of this systematic review was to assess whether LBP patients demonstrate signs of splinting by evaluating the reactions to unexpected mechanical perturbations in terms of (1) trunk muscle activity, (2) kinetic and (3) kinematic trunk responses and (4) estimated mechanical properties of the trunk.

METHODS

The literature was systematically reviewed to identify studies that compared responses to mechanical trunk perturbations between LBP patients and healthy controls in terms of muscle activation, kinematics, kinetics, and/or mechanical properties. If more than four studies reported an outcome, the results of these studies were pooled.

RESULTS

Nineteen studies were included, of which sixteen reported muscle activation, five kinematic responses, two kinetic responses, and two estimated mechanical trunk properties. We found evidence of a longer response time of muscle activation, which would be in line with splinting behaviour in LBP. No signs of splinting behaviour were found in any of the other outcome measures.

CONCLUSIONS

We conclude that there is currently no convincing evidence for the presence of splinting behaviour in LBP patients, because we found no indications for splinting in terms of kinetic and kinematic responses to perturbation and derived mechanical properties of the trunk. Consistent evidence on delayed onsets of muscle activation in response to perturbations was found, but this may have other causes than splinting behaviour.

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

KEY POINTS

Motor neurons in a pool receive both common and independent synaptic inputs, although the proportion and role of their common synaptic input is debated. Classic correlation techniques between motor unit spike trains do not measure the absolute proportion of common input and have limitations as a result of the non-linearity of motor neurons. We propose a method that for the first time allows an accurate quantification of the absolute proportion of low frequency common synaptic input (<5 Hz) to motor neurons in humans. We applied the proposed method to three human muscles and determined experimentally that they receive a similar large amount (>60%) of common input, irrespective of their different functional and control properties. These results increase our knowledge about the role of common and independent input to motor neurons in force control.

ABSTRACT

Motor neurons receive both common and independent synaptic inputs. This observation is classically based on the presence of a significant correlation between pairs of motor unit spike trains. The functional significance of different relative proportions of common input across muscles, individuals and conditions is still debated. One of the limitations in our understanding of correlated input to motor neurons is that it has not been possible so far to quantify the absolute proportion of common input with respect to the total synaptic input received by the motor neurons. Indeed, correlation measures of pairs of output spike trains only allow for relative comparisons. In the present study, we report for the first time an approach for measuring the proportion of common input in the low frequency bandwidth (<5 Hz) to a motor neuron pool in humans. This estimate is based on a phenomenological model and the theoretical fitting of the experimental values of coherence between the permutations of groups of motor unit spike trains. We demonstrate the validity of this theoretical estimate with several simulations. Moreover, we applied this method to three human muscles: the abductor digiti minimi, tibialis anterior and vastus medialis. Despite these muscles having different functional roles and control properties, as confirmed by the results of the present study, we estimate that their motor pools receive a similar and large (>60%) proportion of common low frequency oscillations with respect to their total synaptic input. These results suggest that the central nervous system provides a large amount of common input to motor neuron pools, in a similar way to that for muscles with different functional and control properties.