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

An alpha- to gamma-motoneurone collateral can mitigate velocity-dependent stretch reflexes during voluntary movement: A computational study

The primary motor cortex does not uniquely or directly produce alpha motoneurone (α-MN) drive to muscles during voluntary movement. Rather, α-MN drive emerges from the synthesis and competition among excitatory and inhibitory inputs from multiple descending tracts, spinal interneurons, sensory inputs, and proprioceptive afferents. One such fundamental input is velocity-dependent stretch reflexes in lengthening muscles, which should be inhibited to enable voluntary movement. It remains an open question, however, the extent to which unmodulated stretch reflexes disrupt voluntary movement, and whether and how they are inhibited in limbs with numerous multi-articular muscles. We used a computational model of a Rhesus Macaque arm to simulate movements with feedforward α-MN commands only, and with added velocity-dependent stretch reflex feedback. We found that velocity-dependent stretch reflex caused movement-specific, typically large and variable disruptions to arm movements. These disruptions were greatly reduced when modulating velocity-dependent stretch reflex feedback (i) as per the commonly proposed (but yet to be clarified) idealized alpha-gamma (α-γ) co-activation or (ii) an alternative α-MN collateral projection to homonymous γ-MNs. We conclude that such α-MN collaterals are a physiologically tenable, but previously unrecognized, propriospinal circuit in the mammalian fusimotor system. These collaterals could still collaborate with α-γ co-activation, and the few skeletofusimotor fibers (β-MNs) in mammals, to create a flexible fusimotor ecosystem to enable voluntary movement. By locally and automatically regulating the highly nonlinear neuro-musculo-skeletal mechanics of the limb, these collaterals could be a critical low-level enabler of learning, adaptation, and performance via higher-level brainstem, cerebellar and cortical mechanisms.

Motor unit activity and synaptic inputs to motoneurons in the caudal part of the injured spinal cord

Spinal cord injury (SCI) disrupts neuronal function below the lesion epicenter, causing disuse muscle atrophy. We investigated motor unit (MU) activity and synaptic inputs to motoneurons in the caudal region of the injured spinal cord. Participants with C4-C7 cervical injuries were studied. The extensor digitorum communis (EDC) muscle, which is mainly innervated by C8, was assessed for disuse muscle atrophy. Using advanced electromyography and signal-processing techniques, we examined the concurrent activation of a substantial population of MUs during force-tracking tasks. We found that in participants with SCI (n = 9), both MU discharge rates and the amplitudes of MU action potentials were significantly lower than in controls (n = 9). After SCI, MUs were recruited in a limited force range as the strength of muscle contractions increased, implying a disruption in the orderly MU recruitment pattern. Coherence analysis revealed reduced synaptic inputs to motoneurons in the delta band (0.5-5 Hz) for participants with SCI, suggesting diminished common synaptic inputs to the EDC muscle. In addition, participants with SCI exhibited greater muscle force variability. Using principal component analysis on low-frequency MU discharge rates, we found that the first common component (FCC) captured the most discharge variability in participants with SCI. The coefficients of variation (CV) of the FCC correlated with force signal CVs, suggesting force variability mainly results from common synaptic inputs to the EDC muscle after SCI. These results advance our understanding of the neurophysiology of disuse muscle atrophy in human SCI, paving the way for therapeutic interventions to restore muscle function.NEW & NOTEWORTHY This study analyzed motor unit (MU) function below the lesion epicenter in patients with spinal cord injury (SCI). We found reduced MU discharge rates and action potential amplitudes in participants with SCI compared with controls. The strength of common synaptic inputs to motoneurons was reduced in patients with SCI, with increased force variability primarily due to low-frequency oscillations of common inputs. This study enhances understanding of neurophysiological and behavioral changes in disuse muscle atrophy post-SCI.

Neuromuscular control: from a biomechanist's perspective

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

Numerical instability of Hill-type muscle models

Hill-type muscle models are highly preferred as phenomenological models for musculoskeletal simulation studies despite their introduction almost a century ago. The use of simple Hill-type models in simulations, instead of more recent cross-bridge models, is well justified since computationally 'light-weight'-although less accurate-Hill-type models have great value for large-scale simulations. However, this article aims to invite discussion on numerical instability issues of Hill-type muscle models in simulation studies, which can lead to computational failures and, therefore, cannot be simply dismissed as an inevitable but acceptable consequence of simplification. We will first revisit the basic premises and assumptions on the force-length and force-velocity relationships that Hill-type models are based upon, and their often overlooked but major theoretical limitations. We will then use several simple conceptual simulation studies to discuss how these numerical instability issues can manifest as practical computational problems. Lastly, we will review how such numerical instability issues are dealt with, mostly in an ad hoc fashion, in two main areas of application: musculoskeletal biomechanics and computer animation.

Reference Values of the Forearm Tremor Power Spectra for Youth Athletes

The aim of the study was to determine reference graphs of power spectral density functions of forearm physiological tremor and to compare their parameters in the male and female population of young athletes from various sports. One hundred fifty-nine (159) female (15.7 ± 2.1 years, 59.8 ± 8.1 kg, 169.1 ± 7.5 cm) and 276 male (16.4 ± 1.9 years 72.7 ± 10.3 kg and 180.9 ± 8.7 cm) youth athletes participated in the study. Forearm tremor was measured accelerometrically in a sitting position. Power spectrum density (PSD) function was calculated for each individual tremor waveform. Because of right skewness of power distribution, the PSD functions were subjected to logarithmic transformation. Average log-powers in low (2–4 Hz) and high (8–14 Hz) frequency ranges and mean frequencies in those ranges were analyzed. Tremor log-powers for male were greater than for female athletes (p < 0.001), while frequencies of spectrum maxima did not differ from each other. Frequencies of spectrum maxima correlated (p < 0.001) with age (r = 0.277 and 0.326 for males and females, respectively). The obtained reference functions may be utilized in order to quantify and assess tremor size and its changes evoked by stress and fatigue, which can be applied for selection and training monitoring in sports, but also in medicine for detection and diagnosis of pathologic tremor in young individuals.

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.

Physiological tremor is suppressed and force steadiness is enhanced with increased availability of serotonin regardless of muscle fatigue

Although there is evidence that 5-HT acts as an excitatory neuromodulator to enhance maximal force generation, it is largely unknown how 5-HT activity influences the ability to sustain a constant force during steady-state contractions. A total of 22 healthy individuals participated in the study, where elbow flexion force was assessed during brief isometric contractions at 10% maximal voluntary contraction (MVC), 60% MVC, MVC, and during a sustained MVC. The selective serotonin reuptake inhibitor, paroxetine, suppressed physiological tremor and increased force steadiness when performing the isometric contractions. In particular, a main effect of drug was detected for peak power of force within the 8-12 Hz range (P = 0.004) and the coefficient of variation (CV) of force (P < 0.001). A second experiment was performed where intermittent isometric elbow flexions (20% MVC sustained for 2 min) were repeatedly performed so that serotonergic effects on physiological tremor and force steadiness could be assessed during the development of fatigue. Main effects of drug were once again detected for peak power of force in the 8-12 Hz range (P = 0.002) and CV of force (P = 0.003), where paroxetine suppressed physiological tremor and increased force steadiness when the elbow flexors were fatigued. The findings of this study suggest that enhanced availability of 5-HT in humans has a profound influence of maintaining constant force during steady-state contractions. The action of 5-HT appears to suppress fluctuations in force regardless of the fatigue state of the muscle.NEW & NOTEWORTHY Converging lines of research indicate that enhanced serotonin availability increases maximal force generation. However, it is largely unknown how serotonin influences the ability to sustain a constant force. We performed two experiments to assess physiological tremor and force steadiness in unfatigued and fatigued muscle when serotonin availability was enhanced in the central nervous system. Enhanced availability of serotonin reduced physiological tremor amplitude and improved steadiness regardless of muscle fatigue.

Establishing Task-Relevant MVC Protocols for Modelling Sustained Isometric Force Variability: A Manual Control Study

The present study examined how prevalent methods for determining maximal voluntary contraction (MVC) impact the experimentally derived functions of graded force-force variability. Thirty-two young healthy subjects performed continuous isometric force tracking (20 s trials) at 10 target percentages (5-95% MVC) normalized to a conventional discrete-point (n = 16), or sustained (n = 16) MVC calculation. Distinct rates and magnitudes of change were observed for absolute variability (standard deviation (SD), root mean squared error (RMSE)), tracking error (RMSE, constant error (CE)), and complexity (detrended fluctuation analysis (DFA)) (all p < 0.05) of graded force fluctuations between the MVC groups. Differential performance strategies were observed beyond ~65% MVC, with the discrete-point group minimizing their SD at force values below that of the criterion target (higher CE/RMSE). Moreover, the sustained group's capacity to minimize SD/RMSE/CE corresponded to a more complex structure in their force fluctuations. These findings reveal that the time component of MVC estimation has a direct influence on the corrective strategies supporting near-maximal manual force control. While discrete MVC protocols predominate in the study of manual strength/endurance/precision, a 1:1 MVC-task mapping appears more to be ecologically valid if visuo-motor precision outcomes are of central importance.

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.

Autonomous Control of a Tendon-driven Robotic Limb with Elastic Elements Reveals that Added Elasticity can Enhance Learning

Passive elastic elements can contribute to stability, energetic efficiency, and impact absorption in both biological and robotic systems. They also add dynamical complexity which makes them more challenging to model and control. The impact of this added complexity to autonomous learning has not been thoroughly explored. This is especially relevant to tendon-driven limbs whose cables and tendons are inevitably elastic. Here, we explored the efficacy of autonomous learning and control on a simulated bio-plausible tendon-driven leg across different tendon stiffness values. We demonstrate that increasing stiffness of the simulated muscles can require more iterations for the inverse map to converge but can then perform more accurately, especially in discrete tasks. Moreover, the system is robust to subsequent changes in muscle stiffnesses and can adapt on-the-go within 5 attempts. Lastly, we test the system for the functional task of locomotion and found similar effects of muscle stiffness to learning and performance. Given that a range of stiffness values led to improved learning and maximized performance, we conclude the robot bodies and autonomous controllers-at least for tendon-driven systems-can be co-developed to take advantage of elastic elements. Importantly, this opens also the door to development efforts that recapitulate the beneficial aspects of the co-evolution of brains and bodies in vertebrates.

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.

Parkinson's Disease Exhibits Amplified Intermuscular Coherence During Dynamic Voluntary Action

Parkinson's disease (PD) is typically diagnosed and evaluated on the basis of overt motor dysfunction, however, subtle changes in the frequency spectrum of neural drive to muscles have been reported as well. During dynamic actions, coactive muscles of healthy adults often share a common source of 6-15 Hz (alpha-band) neural drive, creating synchronous alpha-band activity in their EMG signals. Individuals with PD commonly exhibit kinetic action tremor at similar frequencies, but the potential relationship between the intermuscular alpha-band neural drive seen in healthy adults and the action tremor associated with PD is not well-understood. A close relationship is most tenable during voluntary dynamic tasks where alpha-band neural drive is strongest in healthy adults, and where neural circuits affected by PD are most engaged. In this study, we characterized the frequency spectrum of EMG synchronization (intermuscular coherence) in 16 participants with PD and 15 age-matched controls during two dynamic motor tasks: (1) rotation of a dial between the thumb and index finger, and (2) dynamic scaling of isometric precision pinch force. These tasks produce different profiles of coherence between the first dorsal interosseous and abductor pollicis brevis muscles. We sought to determine if alpha-band intermuscular coherence would be amplified in participants with PD relative to controls, if such differences would be task-specific, and if they would correlate with symptom severity. We found that relative to controls, the PD group displayed amplified, but similarly task-dependent, coherence in the alpha-band. The magnitude of coherence during the rotation task correlated with overall symptom severity as per the UPDRS rating scale. Finally, we explored the potential for our coherence measures, with no additional information, to discriminate individuals with PD from controls. The area under the Receiver Operating Characteristic curve (AUC) indicated a clear separation between groups (AUC = 0.96), even though participants with PD were on their typical medication and displayed only mild-moderate symptoms. We conclude that a task-dependent, intermuscular neural drive within the alpha-band is amplified in PD. Its quantification via intermuscular coherence analysis may provide a useful tool for detecting the presence of PD, or assessing its progression.

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.

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.