The volitional control of individual motor units is constrained within low-dimensional neural manifolds by common inputs.

The implementation of low-dimensional movement control by the central nervous system has been debated for decades. In this study, we investigated the dimensionality of the control signals received by spinal motor neurons when controlling either the ankle or knee joint torque. We first identified the low-dimensional latent factors underlying motor unit activity during torque-matched isometric contractions in male participants. Subsequently, we evaluated the extent to which motor units could be independently controlled. To this aim, we used an online control paradigm in which participants received the corresponding motor unit firing rates as visual feedback. We identified two main latent factors, regardless of the muscle group (vastus lateralis-medialis and gastrocnemius lateralis-medialis). The motor units of the gastrocnemius lateralis could be controlled largely independently from those of the gastrocnemius medialis during ankle plantarflexion. This dissociation of motor unit activity imposed similar behavior to the motor units that were not displayed in the feedback. Conversely, it was not possible to dissociate the activity of the motor units between the vastus lateralis and medialis muscles during the knee extension tasks. These results demonstrate that the number of latent factors estimated from linear dimensionality reduction algorithms does not necessarily reflect the dimensionality of volitional control of motor units. Overall, individual motor units were never controlled independently of all others but rather belonged to synergistic groups. Together, these findings provide evidence for a low-dimensional control of motor units constrained by common inputs, with notable differences between muscle groups.Significance statement In this study, we initially examined the latent factors underlying motor unit activity in the vastii or gastrocnemii muscles during torque-matched isometric contractions. We then explored the extent to which these motor units could be controlled independently, using an online control paradigm where participants received visual information on motor unit firing rates. Although participants were able to dissociate the activity of a few motor unit pairs (from the gastrocnemius medialis and lateralis muscles), our results provide direct evidence of a low-dimensional control, constrained by common inputs, limiting flexibility in motor unit recruitment. Furthermore, we show that the number of latent factors identified by dimensionality reduction algorithms does not necessarily reflect the dimensionality of volitional control of motor units.

ERR2 and ERR3 promote the development of gamma motor neuron functional properties required for proprioceptive movement control.

The ability of terrestrial vertebrates to effectively move on land is integrally linked to the diversification of motor neurons into types that generate muscle force (alpha motor neurons) and types that modulate muscle proprioception, a task that in mammals is chiefly mediated by gamma motor neurons. The diversification of motor neurons into alpha and gamma types and their respective contributions to movement control have been firmly established in the past 7 decades, while recent studies identified gene expression signatures linked to both motor neuron types. However, the mechanisms that promote the specification of gamma motor neurons and/or their unique properties remained unaddressed. Here, we found that upon selective loss of the orphan nuclear receptors ERR2 and ERR3 (also known as ERRß, ERRγ or NR3B2, NR3B3, respectively) in motor neurons in mice, morphologically distinguishable gamma motor neurons are generated but do not acquire characteristic functional properties necessary for regulating muscle proprioception, thus disrupting gait and precision movements. Complementary gain-of-function experiments in chick suggest that ERR2 and ERR3 could operate via transcriptional activation of neural activity modulators to promote a gamma motor neuron biophysical signature of low firing thresholds and high firing rates. Our work identifies a mechanism specifying gamma motor neuron functional properties essential for the regulation of proprioceptive movement control.

NeuroMotion: Open-source platform with neuromechanical and deep network modules to generate surface EMG signals during voluntary movement.

Neuromechanical studies investigate how the nervous system interacts with the musculoskeletal (MSK) system to generate volitional movements. Such studies have been supported by simulation models that provide insights into variables that cannot be measured experimentally and allow a large number of conditions to be tested before the experimental analysis. However, current simulation models of electromyography (EMG), a core physiological signal in neuromechanical analyses, remain either limited in accuracy and conditions or are computationally heavy to apply. Here, we provide a computational platform to enable future work to overcome these limitations by presenting NeuroMotion, an open-source simulator that can modularly test a variety of approaches to the full-spectrum synthesis of EMG signals during voluntary movements. We demonstrate NeuroMotion using three sample modules. The first module is an upper-limb MSK model with OpenSim API to estimate the muscle fibre lengths and muscle activations during movements. The second module is BioMime, a deep neural network-based EMG generator that receives nonstationary physiological parameter inputs, like the afore-estimated muscle fibre lengths, and efficiently outputs motor unit action potentials (MUAPs). The third module is a motor unit pool model that transforms the muscle activations into discharge timings of motor units. The discharge timings are convolved with the output of BioMime to simulate EMG signals during the movement. We first show how MUAP waveforms change during different levels of physiological parameter variations and different movements. We then show that the synthetic EMG signals during two-degree-of-freedom hand and wrist movements can be used to augment experimental data for regressing joint angles. Ridge regressors trained on the synthetic dataset were directly used to predict joint angles from experimental data. In this way, NeuroMotion was able to generate full-spectrum EMG for the first use-case of human forearm electrophysiology during voluntary hand, wrist, and forearm movements. All intermediate variables are available, which allows the user to study cause-effect relationships in the complex neuromechanical system, fast iterate algorithms before collecting experimental data, and validate algorithms that estimate non-measurable parameters in experiments. We expect this modular platform will enable validation of generative EMG models, complement experimental approaches and empower neuromechanical research.

A direct spinal cord-computer interface enables the control of the paralysed hand in spinal cord injury.

The paralysis of the muscles controlling the hand dramatically limits the quality of life of individuals living with spinal cord injury (SCI). Here, with a non-invasive neural interface, we demonstrate that eight motor complete SCI individuals (C5-C6) are still able to task-modulate in real-time the activity of populations of spinal motor neurons with residual neural pathways. In all SCI participants tested, we identified groups of motor units under voluntary control that encoded various hand movements. The motor unit discharges were mapped into more than 10 degrees of freedom, ranging from grasping to individual hand-digit flexion and extension. We then mapped the neural dynamics into a real-time controlled virtual hand. The SCI participants were able to match the cue hand posture by proportionally controlling four degrees of freedom (opening and closing the hand and index flexion/extension). These results demonstrate that wearable muscle sensors provide access to spared motor neurons that are fully under voluntary control in complete cervical SCI individuals. This non-invasive neural interface allows the investigation of motor neuron changes after the injury and has the potential to promote movement restoration when integrated with assistive devices.

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.

The neural control of movement: a century of in vivo motor unit recordings is the legacy of Adrian and Bronk.

In two papers dated 1928 to 1929 in The Journal of Physiology, Edgar Adrian and Detlev Bronk described recordings from motor nerve and muscle fibres. The recordings from motor nerve fibres required progressive dissection of the nerve until a few fibres remained, from which isolated single fibre activity could be detected. The muscle fibre recordings were performed in humans during voluntary contractions with an intramuscular electrode - the concentric needle electrode - that they describe for the first time in the second paper. They recognised that muscle fibres would respond to each impulse sent by the innervating motor neurone and that therefore muscle fibre recordings provided information on the times of activation of the motor nerve fibres which were as accurate as a direct record from the nerve. These observations and the description of the concentric needle electrode opened the era of motor unit recordings in humans, which have continued for almost a century and have provided a comprehensive view of the neural control of movement at the motor unit level. Despite important advances in technology, many of the principles of motor unit behaviour that would be investigated in the subsequent decades were canvassed in the two papers by Adrian and Bronk. For example, they described the concomitant motor neurones' recruitment and rate coding for force modulation, synchronisation of motor unit discharges, and the dependence of discharge rate on motor unit recruitment threshold. Here, we summarise their observations and discuss the impact of their work. We highlight the advent of the concentric needle, and its subsequent influence on motor control research.

Specificity of early motor unit adaptations with resistive exercise training.

After exposure of the human body to resistive exercise, the force-generation capacity of the trained muscles increases significantly. Despite decades of research, the neural and muscular stimuli that initiate these changes in muscle force are not yet fully understood. The study of these adaptations is further complicated by the fact that the changes may be partly specific to the training task. For example, short-term strength training does not always influence the neural drive to muscles during the early phase (<100 ms) of force development in rapid isometric contractions. Here we discuss some of the studies that have investigated neuromuscular adaptations underlying changes in maximal force and rate of force development produced by different strength training interventions, with a focus on changes observed at the level of spinal motor neurons. We discuss the different motor unit adjustments needed to increase force or speed, and the specificity of some of the adaptations elicited by differences in the training tasks.

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.

Design, Fabrication and Evaluation of a Stretchable High-Density Electromyography Array.

The adoption of high-density electrode systems for human-machine interfaces in real-life applications has been impeded by practical and technical challenges, including noise interference, motion artefacts and the lack of compact electrode interfaces. To overcome some of these challenges, we introduce a wearable and stretchable electromyography (EMG) array, and present its design, fabrication methodology, characterisation, and comprehensive evaluation. Our proposed solution comprises dry-electrodes on flexible printed circuit board (PCB) substrates, eliminating the need for time-consuming skin preparation. The proposed fabrication method allows the manufacturing of stretchable sleeves, with consistent and standardised coverage across subjects. We thoroughly tested our developed prototype, evaluating its potential for application in both research and real-world environments. The results of our study showed that the developed stretchable array matches or outperforms traditional EMG grids and holds promise in furthering the real-world translation of high-density EMG for human-machine interfaces.

Reading and Modulating Cortical ß Bursts from Motor Unit Spiking Activity.

ß Oscillations (13-30 Hz) are ubiquitous in the human motor nervous system. Yet, their origins and roles are unknown. Traditionally, ß activity has been treated as a stationary signal. However, recent studies observed that cortical ß occurs in "bursting events," which are transmitted to muscles. This short-lived nature of ß events makes it possible to study the main mechanism of ß activity found in the muscles in relation to cortical ß. Here, we assessed whether muscle ß activity mainly results from cortical projections. We ran two experiments in healthy humans of both sexes (N = 15 and N = 13, respectively) to characterize ß activity at the cortical and motor unit (MU) levels during isometric contractions of the tibialis anterior muscle. We found that ß rhythms observed at the cortical and MU levels are indeed in bursts. These bursts appeared to be time-locked and had comparable average durations (40-80 ms) and rates (approximately three to four bursts per second). To further confirm that cortical and MU ß have the same source, we used a novel operant conditioning framework to allow subjects to volitionally modulate MU ß. We showed that volitional modulation of ß activity at the MU level was possible with minimal subject learning and was paralleled by similar changes in cortical ß activity. These results support the hypothesis that MU ß mainly results from cortical projections. Moreover, they demonstrate the possibility to decode cortical ß activity from MU recordings, with a potential translation to future neural interfaces that use peripheral information to identify and modulate activity in the central nervous system.SIGNIFICANCE STATEMENT We show for the first time that ß activity in motor unit (MU) populations occurs in bursting events. These bursts observed in the output of the spinal cord appear to be time-locked and share similar characteristics of ß activity at the cortical level, such as the duration and rate at which they occur. Moreover, when subjects were exposed to a novel operant conditioning paradigm and modulated MU ß activity, cortical ß activity changed in a similar way as peripheral ß. These results provide evidence for a strong correspondence between cortical and peripheral ß activity, demonstrating the cortical origin of peripheral ß and opening the pathway for a new generation of neural interfaces.

Interfacing Motor Units in Non-Human Primates Identifies a Principal Neural Component for Force Control Constrained by the Size Principle.

Motor units convert the last neural code of movement into muscle forces. The classic view of motor unit control is that the central nervous system sends common synaptic inputs to motoneuron pools and that motoneurons respond in an orderly fashion dictated by the size principle. This view however is in contrast with the large number of dimensions observed in motor cortex which may allow individual and flexible control of motor units. Evidence for flexible control of motor units may be obtained by tracking motor units longitudinally during tasks with some level of behavioural variability. Here we identified and tracked populations of motor units in the brachioradialis muscle of two macaque monkeys during ten sessions spanning over one month with a broad range of rate of force development (1.8 - 38.6 N·m·s-1). We found a very stable recruitment order and discharge characteristics of the motor units over sessions and contraction trials. The small deviations from orderly recruitment were fully predicted by the motor unit recruitment intervals, so that small shifts in recruitment thresholds happened only during contractions at high rate of force development. Moreover, we also found that one component explained more than ∼50% of the motor unit discharge rate variance, and that the remaining components represented a time-shifted version of the first. In conclusion, our results show that motoneurons recruitment is determined by the interplay of the size principle and common input and that this recruitment scheme is not violated over time nor by the speed of the contractions.SIGNIFICANCE STATEMENT:With a new non-invasive high-density electromyographic framework we show the activity of motor unit ensembles in macaques during voluntary contractions. The discharge characteristics of brachioradialis motor units revealed a relatively fixed recruitment order and discharge characteristics across days and rate of force developments. These results were further confirmed through invasive axonal stimulation and recordings of intramuscular electromyographic activity from 16 arm muscles. The study shows for the first time the feasibility of longitudinal non-invasive motor unit interfacing and tracking of the same motor units in non-human primates.

Autonomic nerve fibers aberrantly reinnervate denervated facial muscles and alter muscle fiber population.

The surgical redirection of efferent neural input to a denervated muscle via a nerve transfer can reestablish neuromuscular control after nerve injuries. The role of autonomic nerve fibers during the process of muscular reinnervation remains largely unknown. Here, we investigated the neurobiological mechanisms behind the spontaneous functional recovery of denervated facial muscles in male rodents. Recovered facial muscles demonstrated an abundance of cholinergic axonal endings establishing functional neuromuscular junctions. The parasympathetic source of the neuronal input was confirmed to be in the pterygopalatine ganglion. Furthermore, the autonomically reinnervated facial muscles underwent a muscle fiber change to a purely intermediate muscle fiber population (MHCIIa). Finally, electrophysiological tests revealed that the postganglionic parasympathetic fibers travel to the facial muscles via the sensory infraorbital nerve. Our findings demonstrated expanded neuromuscular plasticity of denervated striated muscles enabling functional recovery via alien autonomic fibers. These findings may further explain the underlying mechanisms of sensory protection implemented to prevent atrophy of a denervated muscle.SIGNIFICANCE STATEMENT:Nerve injuries represent significant morbidity and disability for patients. Rewiring motor nerve fibers to other target muscles have shown to be a successful approach in the restoration of motor function. This demonstrates the remarkable capacity of the central nervous system to adapt to the needs of the neuromuscular system. Yet, the capability of skeletal muscles being reinnervated by non-motor axons remains largely unknown. Here, we show that under deprivation of original efferent input, the neuromuscular system can undergo functional and morphological remodeling via autonomic nerve fibers. This may explain neurobiological mechanisms of the sensory protection phenomenon, which is due to parasympathetic reinnervation.

Beta inputs to motor neurons do not directly contribute to volitional force modulation.

Neural oscillatory activity in the beta band (13-30 Hz) is prominent in the brain and it is transmitted partly linearly to the spinal cord and muscles. Multiple views on the functional relevance of beta activity in the motor system have been proposed. Previous simulation work suggested that pools of spinal motoneurons (MNs) receiving a common beta input could demodulate this activity, transforming it into low-frequency neural drive that could alter force production in muscles. This may suggest that common beta inputs to muscles have a direct role in force modulation. Here we report the experimental average levels and ranges of common beta activity in spinal MNs projecting to single muscles and use a computational model of a MN pool to test if the experimentally observed beta levels in MNs can influence force. When beta was modelled as a continuous activity, the amplitude needed to produce non-negligible changes in force corresponded to beta representation in the MN pool that was far above the experimental observations. On the other hand, when beta activity was modelled as short-lived events (i.e. bursts of beta activity separated by intervals without beta oscillations), this activity approximated levels that could cause small changes in force with estimated average common beta inputs to the MNs compatible with the experimental observations. Nonetheless, bursting beta is unlikely to be used for force control due to the temporal sparsity of this activity. It is therefore concluded that beta oscillations are unlikely to contribute to the voluntary modulation of force. KEY POINTS: It has been previously proposed that beta (13-30 Hz) common inputs to a motor neuron pool may have a non-linear effect in voluntary force control. The needed strength of beta oscillations to modulate forces has not been analysed yet. Based on computer simulations, we show that sustained beta inputs to a spinal motoneuron pool at physiologically reported levels have minimal effect on force. Levels of sustained beta rhythmic activity that can cause a significant change in force are not compatible with experimental observations of intramuscular coherence in human skeletal muscles.

Common synaptic input, synergies and size principle: Control of spinal motor neurons for movement generation.

Understanding how movement is controlled by the CNS remains a major challenge, with ongoing debate about basic features underlying this control. In current established views, the concepts of motor neuron recruitment order, common synaptic input to motor neurons and muscle synergies are usually addressed separately and therefore seen as independent features of motor control. In this review, we analyse the body of literature in a broader perspective and we identify a unified approach to explain apparently divergent observations at different scales of motor control. Specifically, we propose a new conceptual framework of the neural control of movement, which merges the concept of common input to motor neurons and modular control, together with the constraints imposed by recruitment order. This framework is based on the following assumptions: (1) motor neurons are grouped into functional groups (clusters) based on the common inputs they receive; (2) clusters may significantly differ from the classical definition of motor neuron pools, such that they may span across muscles and/or involve only a portion of a muscle; (3) clusters represent functional modules used by the CNS to reduce the dimensionality of the control; and (4) selective volitional control of single motor neurons within a cluster receiving common inputs cannot be achieved. Here, we discuss this framework and its underlying theoretical and experimental evidence.

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

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

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.

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.

Non-invasive estimation of muscle fibre size from high-density electromyography.

Because of the biophysical relation between muscle fibre diameter and the propagation velocity of action potentials along the muscle fibres, motor unit conduction velocity could be a non-invasive index of muscle fibre size in humans. However, the relation between motor unit conduction velocity and fibre size has been only assessed indirectly in animal models and in human patients with invasive intramuscular EMG recordings, or it has been mathematically derived from computer simulations. By combining advanced non-invasive techniques to record motor unit activity in vivo, i.e. high-density surface EMG, with the gold standard technique for muscle tissue sampling, i.e. muscle biopsy, here we investigated the relation between the conduction velocity of populations of motor units identified from the biceps brachii muscle, and muscle fibre diameter. We demonstrate the possibility of predicting muscle fibre diameter (R2  = 0.66) and cross-sectional area (R2  = 0.65) from conduction velocity estimates with low systematic bias (∼2% and ∼4% respectively) and a relatively low margin of individual error (∼8% and ∼16%, respectively). The proposed neuromuscular interface opens new perspectives in the use of high-density EMG as a non-invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling. The non-invasive nature of high-density surface EMG for the assessment of muscle fibre size may be useful in studies monitoring child development, ageing, space and exercise physiology, although the applicability and validity of the proposed methodology need to be more directly assessed in these specific populations by future studies. KEY POINTS: Because of the biophysical relation between muscle fibre size and the propagation velocity of action potentials along the sarcolemma, motor unit conduction velocity could represent a potential non-invasive candidate for estimating muscle fibre size in vivo. This relation has been previously assessed in animal models and humans with invasive techniques, or it has been mathematically derived from simulations. By combining high-density surface EMG with muscle biopsy, here we explored the relation between the conduction velocity of populations of motor units and muscle fibre size in healthy individuals. Our results confirmed that motor unit conduction velocity can be considered as a novel biomarker of fibre size, which can be adopted to predict muscle fibre diameter and cross-sectional area with low systematic bias and margin of individual error. The proposed neuromuscular interface opens new perspectives in the use of high-density EMG as a non-invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling.

Essential Tremor accentuates the pattern of tremor-band coherence between upper-limb muscles.

Although Essential Tremor is one of the most common movement disorders, current treatment options are relatively limited. Peripheral tremor suppression methods have shown potential, but we do not currently know which muscles are most responsible for patients' tremor, making it difficult to optimize suppression methods. The purpose of this study was to quantify the relationships between the tremorogenic activity in muscles throughout the upper limb. Muscle activity was recorded from the 15 major superficial upper-limb muscles in 24 subjects with Essential Tremor while they held various postures or made upper-limb movements. We calculated the coherence in the tremor band (4-12 Hz) between the activity of all muscle pairs and the time-varying phase difference between sufficiently coherent muscle pairs. Overall, the observed pattern somewhat mirrored functional relationships: agonistic muscle pairs were most coherent and in phase, whereas antagonist and unrelated muscle pairs exhibited less coherence and were either consistently in phase, consistently antiphase, consistently out of phase (unrelated pairs only), or else inconsistent. Patients exhibited significantly more coherence than control subjects (p<0.001) in the vast majority of muscle pairs (95 out of 105). Furthermore, differences between patients and controls were most pronounced among agonists; thus, the coherence pattern existing in control subjects was accentuated in patients with ET. We conclude that tremor-band activity is broadly distributed among the muscles of the upper limb, challenging efforts to determine which muscles are most responsible for a patient's tremor.

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.