Motor unit

NeuroMechanics: Electrophysiological and computational methods to accurately estimate the neural drive to muscles in humans in vivo

The ultimate neural signal for muscle control is the neural drive sent from the spinal cord to muscles. This neural signal comprises the ensemble of action potentials discharged by the active spinal motoneurons, which is transmitted to the innervated muscle fibres to generate forces. Accurately estimating the neural drive to muscles in humans in vivo is challenging since it requires the identification of the activity of a sample of motor units (MUs) that is representative of the active MU population. Current electrophysiological recordings usually fail in this task by identifying small MU samples with over-representation of higher-threshold with respect to lower-threshold MUs. Here, we describe recent advances in electrophysiological methods that allow the identification of more representative samples of greater numbers of MUs than previously possible. This is obtained with large and very dense arrays of electromyographic electrodes. Moreover, recently developed computational methods of data augmentation further extend experimental MU samples to infer the activity of the full MU pool. In conclusion, the combination of new electrode technologies and computational modelling allows for an accurate estimate of the neural drive to muscles and opens new perspectives in the study of the neural control of movement and in neural interfacing.

Common synaptic inputs and persistent inward currents of vastus lateralis motor units are reduced in older male adults

Although muscle atrophy may partially account for age-related strength decline, it is further influenced by alterations of neural input to muscle. Persistent inward currents (PIC) and the level of common synaptic inputs to motoneurons influence neuromuscular function. However, these have not yet been described in the aged human quadriceps. High-density surface electromyography (HDsEMG) signals were collected from the vastus lateralis of 15 young (mean ± SD, 23 ± 5 y) and 15 older (67 ± 9 y) men during submaximal sustained and 20-s ramped contractions. HDsEMG signals were decomposed to identify individual motor unit discharges, from which PIC amplitude and intramuscular coherence were estimated. Older participants produced significantly lower knee extensor torque (p < 0.001) and poorer force tracking ability (p < 0.001) than young. Older participants also had lower PIC amplitude (p = 0.001) and coherence estimates in the alpha frequency band (p < 0.001) during ramp contractions when compared to young. Persistent inward currents and common synaptic inputs are lower in the vastus lateralis of older males when compared to young. These data highlight altered neural input to the clinically and functionally important quadriceps, further underpinning age-related loss of function which may occur independently of the loss of muscle mass.

Muscle contractile properties directly influence shared synaptic inputs to spinal motor neurons

Alpha band oscillations in shared synaptic inputs to the alpha motor neuron pool can be considered an involuntary source of noise that hinders precise voluntary force production. This study investigated the impact of changing muscle length on the shared synaptic oscillations to spinal motor neurons, particularly in the physiological tremor band. Fourteen healthy individuals performed low-level dorsiflexion contractions at ankle joint angles of 90° and 130°, while high-density surface electromyography (HDsEMG) was recorded from the tibialis anterior (TA). We decomposed the HDsEMG into motor units spike trains and calculated the motor units' coherence within the delta (1-5 Hz), alpha (5-15 Hz), and beta (15-35 Hz) bands. Additionally, force steadiness and force spectral power within the tremor band were quantified. Results showed no significant differences in force steadiness between 90° and 130°. In contrast, alpha band oscillations in both synaptic inputs and force output decreased as the length of the TA was moved from shorter (90°) to longer (130°), with no changes in delta and beta bands. In a second set of experiments (10 participants), evoked twitches were recorded with the ankle joint at 90° and 130°, revealing longer twitch durations in the longer TA muscle length condition compared to the shorter. These experimental results, supported by a simple computational simulation, suggest that increasing muscle length enhances the muscle's low-pass filtering properties, influencing the oscillations generated by the Ia afferent feedback loop. Therefore, this study provides valuable insights into the interplay between muscle biomechanics and neural oscillations. KEY POINTS: We investigated whether changes in muscle length, achieved by changing joint position, could influence common synaptic oscillations to spinal motor neurons, particularly in the tremor band (5-15 Hz). Our results demonstrate that changing muscle length from shorter to longer induces reductions in the magnitude of alpha band oscillations in common synaptic inputs. Importantly, these reductions were reflected in the oscillations of muscle force output within the alpha band. Longer twitch durations were observed in the longer muscle length condition compared to the shorter, suggesting that increasing muscle length enhances the muscle's low-pass filtering properties. Changes in the peripheral contractile properties of motor units due to changes in muscle length significantly influence the transmission of shared synaptic inputs into muscle force output. These findings prove the interplay between muscle mechanics and neural adaptations.

Motor unit discharge rate modulation during isometric contractions to failure is intensity- and modality-dependent

The physiological mechanisms determining the progressive decline in the maximal muscle torque production capacity during isometric contractions to task failure are known to depend on task demands. Task-specificity of the associated adjustments in motor unit discharge rate (MUDR), however, remains unclear. This study examined MUDR adjustments during different submaximal isometric knee extension tasks to failure. Participants performed a sustained and an intermittent task at 20% and 50% of maximal voluntary torque (MVT), respectively (Experiment 1). High-density surface EMG signals were recorded from vastus lateralis (VL) and medialis (VM) and decomposed into individual MU discharge timings, with the identified MUs tracked from recruitment to task failure. MUDR was quantified and normalised to intervals of 10% of contraction time (CT). MUDR of both muscles exhibited distinct modulation patterns in each task. During the 20% MVT sustained task, MUDR decreased until ∼50% CT, after which it gradually returned to baseline. Conversely, during the 50% MVT intermittent task, MUDR remained stable until ∼40-50% CT, after which it started to continually increase until task failure. To explore the effect of contraction intensity on the observed patterns, VL and VM MUDR was quantified during sustained contractions at 30% and 50% MVT (Experiment 2). During the 30% MVT sustained task, MUDR remained stable until ∼80-90% CT in both muscles, after which it continually increased until task failure. During the 50% MVT sustained task the increase in MUDR occurred earlier, after ∼70-80% CT. Our results suggest that adjustments in MUDR during submaximal isometric contractions to failure are contraction modality- and intensity-dependent. KEY POINTS: During prolonged muscle contractions a constant motor output can be maintained by recruitment of additional motor units and adjustments in their discharge rate. Whilst contraction-induced decrements in neuromuscular function are known to depend on task demands, task-specificity of motor unit discharge behaviour adjustments is still unclear. In this study, we tracked and compared discharge activity of several concurrently active motor units in the vastii muscles during different submaximal isometric knee extension tasks to failure, including intermittent vs. sustained contraction modalities performed in the same intensity domain (Experiment 1), and two sustained contractions performed at different intensities (Experiment 2). During each task, motor units modulated their discharge rate in a distinct, biphasic manner, with the modulation pattern depending on contraction intensity and modality. These results provide insight into motoneuronal adjustments during contraction tasks posing different demands on the neuromuscular system.

Effect of Warm-Up Exercise on Functional Regulation of Motor Unit Activation during Isometric Torque Production

In this study, we tested several hypotheses related to changes in motor unit activation patterns after warm-up exercise. Fifteen healthy young men participated in the experiment and the main task was to produce voluntary torque through the elbow joint under the isometric condition. The experimental conditions consisted of two directions of torque, including flexion and extension, at two joint angles, 10° and 90°. Participants were asked to increase the joint torque to the maximal level at a rate of 10% of the maximum voluntary torque. The warm-up protocol followed the ACSM guidelines, which increased body temperature by approximately 1.5°C. Decomposition electromyography electrodes, capable of extracting multiple motor unit action potentials from surface signals, were placed on the biceps and triceps brachii muscles, and joint torque was measured on the dynamometer. The mean firing rate and the recruitment threshold of the decomposed motor units were quantified. In addition, a single motor unit activity from the spike train was quantified for each of five selected motor units. The magnitude of joint torque increased with the warm-up exercise for all the experimental conditions. The results of the motor unit analyses showed a positive and beneficial effect of the warm-up exercise, with an increase in both the mean firing rate and the recruitment threshold by about 56% and 33%, respectively, particularly in the agonist muscle. Power spectral density in the gamma band, which is thought to be the dominant voluntary activity, was also increased by the warm-up exercise only in the high threshold motor units.

Neuromuscular consequences of spinal cord injury: New mechanistic insights and clinical considerations

The spinal cord facilitates communication between the brain and the body, containing intrinsic systems that work with lower motor neurons (LMNs) to manage movement. Spinal cord injuries (SCIs) can lead to partial paralysis and dysfunctions in muscles below the injury. While traditionally this paralysis has been attributed to disruptions in the corticospinal tract, a growing body of work demonstrates LMN damage is a factor. Motor units, comprising the LMN and the muscle fibers with which they connect, are essential for voluntary movement. Our understanding of their changes post-SCI is still emerging, but the health of motor units is vital, especially when considering innovative SCI treatments like nerve transfer surgery. This review seeks to collate current literature on how SCI impact motor units and explore neuromuscular clinical implications and treatment avenues. SCI reduced motor unit number estimates, and surviving motor units had impaired signal transmission at the neuromuscular junction, force-generating capacity, and excitability, which have the potential to recover chronically, yet the underlaying mechanisms are unclear. Furthermore, electrodiagnostic evaluations can aid in assessing the health lower and upper motor neurons, identify suitable targets for nerve transfer surgeries, and detect patients with time sensitive injuries. Lastly, many electrodiagnostic abnormalities occur in both chronic and acute SCI, yet factors contributing to these abnormalities are unknown. Future studies are required to determine how motor units adapt following SCI and the clinical implications of these adaptations.

Developmental changes in motor unit activity patterns: child-adult comparison using discrete motor unit analysis

Using global surface electromyography (sEMG) and the sEMG threshold it has been suggested that children activate their type-II motor unit (MU) to a lesser extent compared with adults. However, when age-related differences in discrete MU activation are examined using sEMG decomposition this phenomenon is not observed. Furthermore, findings from these studies are inconsistent and conflicting. Therefore, the purpose of this study was to examine differences in discrete MU activation of the vastus lateralis (VL) between boys and men during moderate-intensity knee extensions. Seventeen boys and 20 men completed two laboratory sessions. Following a habituation session, maximal voluntary isometric knee extension (MVIC) torque was determined before completing trapezoidal contractions at 70% MVIC. sEMG of the VL was captured and mathematically decomposed into individual MU action potential trains. Motor unit action potential amplitude (MUAPamp), recruitment threshold (RT), and MU firing rates (MUFR) were calculated. We observed that MUAPamp-RT slope was steeper in men compared with boys (p < 0.05) even after accounting for fat thickness and quadriceps muscle depth. The mean MUFR and y-intercept of the MUFR-RT relationship were significantly (p < 0.001) lower in boys than in men. The slope of the MUFR-RT relationship tended to be steeper in men, but the differences did not reach statistical significance (p = 0.056). Overall, our results suggest that neural strategies used to produce torque are different among boys and men. Such differences may be related, in part, to boys' lower MUFR and lesser ability to activate their higher-threshold MUs. Although, other factors (e.g., muscle composition) likely also play a role.

Tutorial: Analysis of central and peripheral motor unit properties from decomposed High-Density surface EMG signals with openhdemg

High-Density surface Electromyography (HD-sEMG) is the most established technique for the non-invasive analysis of single motor unit (MU) activity in humans. It provides the possibility to study the central properties (e.g., discharge rate) of large populations of MUs by analysis of their firing pattern. Additionally, by spike-triggered averaging, peripheral properties such as MUs conduction velocity can be estimated over adjacent regions of the muscles and single MUs can be tracked across different recording sessions. In this tutorial, we guide the reader through the investigation of MUs properties from decomposed HD-sEMG recordings by providing both the theoretical knowledge and practical tools necessary to perform the analyses. The practical application of this tutorial is based on openhdemg, a free and open-source community-based framework for the automated analysis of MUs properties built on Python 3 and composed of different modules for HD-sEMG data handling, visualisation, editing, and analysis. openhdemg is interfaceable with most of the available recording software, equipment or decomposition techniques, and all the built-in functions are easily adaptable to different experimental needs. The framework also includes a graphical user interface which enables users with limited coding skills to perform a robust and reliable analysis of MUs properties without coding.

Visual Information Processing in Older Adults: Force Control and Motor Unit Pool Modulation

Increased visual information about a task impairs force control in older adults. To date, however, it remains unclear how increased visual information changes the activation of the motor unit pool differently for young and older adults. Therefore, this study aimed to determine how increased visual information alters the activation of the motor neuron pool and influences force control in older adults. Fifteen older adults (66-86 years, seven women) and fifteen young adults (18-30 years, eight women) conducted a submaximal constant force task (15% of maximum) with ankle dorsiflexion for 20 s. The visual information processing was manipulated by changing the amount of force visual feedback into a low-gain (0.05°) or high-gain (1.2°) condition. Older adults exhibited greater force variability, especially at high-gain visual feedback. This exacerbated force variability from low- to high-gain visual feedback was associated with modulations of multiple motor units, not single motor units. Specifically, increased modulation of multiple motor units from 10 to 35 Hz may contribute to the amplification in force variability. Therefore, our findings suggest evidence that high-gain visual feedback amplifies force variability of older adults which is related to increases in the activation of motor neuron pool from 10 to 35 Hz.

The role of clinical neurophysiology in the definition and assessment of fatigue and fatigability

Though a common symptom, fatigue is difficult to define and investigate, occurs in a wide variety of neurological and systemic disorders, with differing pathological causes. It is also often accompanied by a psychological component. As a symptom of long-term COVID-19 it has gained more attention. In this review, we begin by differentiating fatigue, a perception, from fatigability, quantifiable through biomarkers. Central and peripheral nervous system and muscle disorders associated with these are summarised. We provide a comprehensive and objective framework to help identify potential causes of fatigue and fatigability in a given disease condition. It also considers the effectiveness of neurophysiological tests as objective biomarkers for its assessment. Among these, twitch interpolation, motor cortex stimulation, electroencephalography and magnetencephalography, and readiness potentials will be described for the assessment of central fatigability, and surface and needle electromyography (EMG), single fibre EMG and nerve conduction studies for the assessment of peripheral fatigability. The purpose of this review is to guide clinicians in how to approach fatigue, and fatigability, and to suggest that neurophysiological tests may allow an understanding of their origin and interactions. In this way, their differing types and origins, and hence their possible differing treatments, may also be defined more clearly.

Spatial decomposition of ultrafast ultrasound images to identify motor unit activity - A comparative study with intramuscular and surface EMG

The smallest voluntarily controlled structure of the human body is the motor unit (MU), comprised of a motoneuron and its innervated fibres. MUs have been investigated in neurophysiology research and clinical applications, primarily using electromyographic (EMG) techniques. Nonetheless, EMG (both surface and intramuscular) has a limited detection volume. A recent alternative approach to detect MUs is ultrafast ultrasound (UUS) imaging. The possibility of identifying MU activity from UUS has been shown by blind source separation (BSS) of UUS images, using optimal separation spatial filters. However, this approach has yet to be fully compared with EMG techniques for a large population of unique MU spike trains. Here we identify individual MU activity in UUS images using the BSS method for 401 MU spike trains from eleven participants based on concurrent recordings of either surface or intramuscular EMG from forces up to 30% of the maximum voluntary contraction (MVC) force. We assessed the BSS method's ability to identify MU spike trains from direct comparison with the EMG-derived spike trains as well as twitch areas and temporal profiles from comparison with the spike-triggered-averaged UUS images when using the EMG-derived spikes as triggers. We found a moderate rate of correctly identified spikes (53.0 ± 16.0%) with respect to the EMG-identified firings. However, the MU twitch areas and temporal profiles could still be identified accurately, including at 30% MVC force. These results suggest that the current BSS methods for UUS can accurately identify the location and average twitch of a large pool of MUs in UUS images, providing potential avenues for studying neuromechanics from a large cross-section of the muscle. On the other hand, more advanced methods are needed to address the convolutive and partly non-linear summation of velocities for recovering the full spike trains.

Physical strength levels and short-term memory efficiency in primary school children: a possible match?

BACKGROUND

Physical strength stimulation and, in general, physical activity induces brain plasticity (functional and structural adaptations) in different cerebral areas, benefiting executive function, cognition, attention and academic performance, which is usually estimated by measuring the Intelligent Quotient (IQ), and IQ is related to short-term memory, generally during school age. However, very little is known about the role of physical strength on short-term memory efficiency. Therefore, the primary aim of this study is to examine whether the level of physical strength can positively impact short-term memory efficiency in primary school children. Additionally, if this effect is observed, the secondary goal of this study is to determine whether the age of the participants plays a role in mediating and moderating this influence.

METHODS

Seventy-five children from a primary school in the metropolitan area of Turin were recruited for this study. Each subject performed the overhead medicine ball toss (backwards) test to assess physical strength and the Digit Span test from the Wechsler Intelligence Scale for Children (WISC) to evaluate short-term memory efficiency. Firstly, a simple mediation model was used to identify the possible impact of physical strength levels on short-term memory efficiency and the potential role of participants' chronological age. Secondly, a moderation model was carried out to observe if age could moderate the impact of physical training on short-term memory efficiency and the different significance levels of the moderator. Significance was assumed at P<0.05.

RESULTS

The results showed a statistically significant direct effect of physical strength on short-term memory (Β=0.429, t(72)=3.247, P<0.01). On the contrary, age was not statistically significant (Β=0.167, t(72)=3.247, P=0.211). Furthermore, a significant interaction between strength and age was identified by the moderation model (β=-0.270, P<0.01). Specifically, the impact of physical strength levels on short-term memory increased for individuals who were above the mean age (β=0.755, P<0.001). but not for those under the mean age (β=0.215, P=0.153). This model explains 37.2% of the variance in memory (R2=0.372, F(3, 71)=14.031, P<0.001).

CONCLUSIONS

These findings suggest that physical strength can positively influence short-term memory. In addition, this impact is enhanced in older-age children. Thus, primary school programs should stimulate physical strength to help children develop cognitive abilities.

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.

How Posture and Previous Sensorimotor Experience Influence Muscle Activity during Gait Imagery in Young Healthy Individuals

This study explores how gait imagery (GI) influences lower-limb muscle activity with respect to posture and previous walking experience. We utilized surface electromyography (sEMG) in 36 healthy young individuals aged 24 (±1.1) years to identify muscle activity during a non-gait imagery task (non-GI), as well as GI tasks before (GI-1) and after the execution of walking (GI-2), with assessments performed in both sitting and standing postures. The sEMG was recorded on both lower limbs on the tibialis anterior (TA) and on the gastrocnemius medialis (GM) for all tested tasks. As a result, a significant muscle activity decrease was found in the right TA for GI-1 compared to GI-2 in both sitting (p = 0.008) and standing (p = 0.01) positions. In the left TA, the activity decreased in the sitting posture during non-GI (p = 0.004) and GI-1 (p = 0.009) in comparison to GI-2. No differences were found for GM. The subjective level of imagination difficulty improved for GI-2 in comparison to GI-1 in both postures (p < 0.001). Previous sensorimotor experience with real gait execution and sitting posture potentiate TA activity decrease during GI. These findings contribute to the understanding of neural mechanisms beyond GI.

Characterization of Motor Unit Firing and Twitch Properties for Decoding Musculoskeletal Force in the Human Ankle Joint In Vivo

Understanding how motor units (MUs) contribute to skeletal mechanical force is crucial for unraveling the underlying mechanism of human movement. Alterations in MU firing, contractile and force-generating properties emerge in response to physical training, aging or injury. However, how changes in MU firing and twitch properties dictate skeletal muscle force generation in healthy and impaired individuals remains an open question. In this work, we present a MU-specific approach to identify firing and twitch properties of MU samples and employ them to decode musculoskeletal function in vivo. First, MU firing events were decomposed offline from high-density electromyography (HD-EMG) of six lower leg muscles involved in ankle plantar-dorsi flexion. We characterized their twitch responses based on the statistical distributions of their firing properties and employed them to compute MU-specific activation dynamics. Subsequently, we decoded ankle joint moments by linking our framework to a subject-specific musculoskeletal model. We validated our approach at different ankle positions and levels of activation and compared it with traditional EMG-driven models. Our proposed MU-specific formulation achieves higher generalization across conditions than the EMG-driven models, with significantly lower coefficients of variation in torque predictions. Furthermore, our approach shows distinct neural strategies across a large repertoire of contractile conditions in different muscles. Our proposed approach may open new avenues for characterizing the relationship between MU firing and twitch properties and their influence on force capacity. This can facilitate the development of targeted rehabilitation strategies tailored to individuals with specific neuromuscular conditions.

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.

Extracting Individual Muscle Drive and Activity From High-Density Surface Electromyography Signals Based on the Center of Gravity of Motor Unit

Neural interfacing has played an essential role in advancing our understanding of fundamental movement neurophysiology and the development of human-machine interface. However, direct neural interfaces from brain and nerve recording are currently limited in clinical areas for their invasiveness and high selectivity. Here, we applied the surface electromyogram (EMG) in studying the neural control of movement and proposed a new non-invasive way of extracting neural drive to individual muscles. Sixteen subjects performed isometric contractions to complete six hand tasks. High-density surface EMG signals (256 channels in total) recorded from the forearm muscles were decomposed into motor unit firing trains. The location of each decomposed motor unit was represented by its center of gravity and was put into clustering for distinct muscle regions. All the motor units in the same cluster served as a muscle-specific motor pool from which individual muscle drive could be extracted directly. Moreover, we cross-validated the self-clustered muscle regions by magnetic resonance imaging (MRI) recorded from the subjects' forearms. All motor units that fall within the MRI region are considered correctly clustered. We achieved a clustering accuracy of 95.72% ± 4.01% for all subjects. We provided a new framework for collecting experimental muscle-specific drives and generalized the way of surface electrode placement without prior knowledge of the targeting muscle architecture.

Ageing reduces persistent inward current contribution to motor neurone firing: Potential mechanisms and the role of exercise

Nervous system deterioration is a primary driver of age-related motor impairment. The motor neurones, which act as the interface between the central nervous system and the muscles, play a crucial role in amplifying excitatory synaptic input to produce the desired motor neuronal firing output. For this, they utilise their ability to generate persistent (long-lasting) depolarising currents that increase cell excitability, and both amplify and prolong the output activity of motor neurones for a given synaptic input. Modulation of these persistent inward currents (PICs) contributes to the motor neurones' capacities to attain the required firing frequencies and rapidly modulate them to competently complete most tasks. Thus, PICs are crucial for adequate movement generation. Impairments in intrinsic motor neurone properties can impact motor unit firing capacity, with convincing evidence indicating that the PIC contribution to motor neurone firing is reduced in older adults. Indeed, this could be an important mechanism underpinning the age-related reductions in strength and physical function. Furthermore, resistance training has emerged as a promising intervention to counteract age-associated PIC impairments, with changes in PICs being correlated with improvements in muscular strength and physical function after training. In this review, we present the current knowledge of the PIC magnitude decline during ageing and discuss whether reduced serotonergic and noradrenergic input onto the motor neurones, voltage-gated calcium channel dysfunction or inhibitory input impairments are candidates that: (i) explain age-related reductions in the PIC contribution to motor neurone firing and (ii) underpin the enhanced PIC contribution to motor neurone firing following resistance training in older adults.

Larger and Denser: An Optimal Design for Surface Grids of EMG Electrodes to Identify Greater and More Representative Samples of Motor Units

The spinal motor neurons are the only neural cells whose individual activity can be noninvasively identified. This is usually done using grids of surface electromyographic (EMG) electrodes and source separation algorithms; an approach called EMG decomposition. In this study, we combined computational and experimental analyses to assess how the design parameters of grids of electrodes influence the number and the properties of the identified motor units. We first computed the percentage of motor units that could be theoretically discriminated within a pool of 200 simulated motor units when decomposing EMG signals recorded with grids of various sizes and interelectrode distances (IEDs). Increasing the density, the number of electrodes, and the size of the grids, increased the number of motor units that our decomposition algorithm could theoretically discriminate, i.e., up to 83.5% of the simulated pool (range across conditions: 30.5-83.5%). We then identified motor units from experimental EMG signals recorded in six participants with grids of various sizes (range: 2-36 cm2) and IED (range: 4-16 mm). The configuration with the largest number of electrodes and the shortest IED maximized the number of identified motor units (56 ± 14; range: 39-79) and the percentage of early recruited motor units within these samples (29 ± 14%). Finally, the number of identified motor units further increased with a prototyped grid of 256 electrodes and an IED of 2 mm. Taken together, our results showed that larger and denser surface grids of electrodes allow to identify a more representative pool of motor units than currently reported in experimental studies.

Acute intermittent hypoxia enhances strength, and modulates spatial distribution of muscle activation in persons with chronic incomplete spinal cord injury

Acute intermittent hypoxia (AIH) is an emerging technique for facilitating neural plasticity in individuals with chronic incomplete spinal cord injury (iSCI). A single sequence of AIH enhances hand grip strength and ankle plantarflexion torque, but underlying mechanisms are not yet clear. We sought to examine how AIH-induced changes in magnitude and spatial distribution of the electromyogram (EMG) of the biceps and triceps brachii contributes to improved strength. Seven individuals with iSCI visited the laboratory on two occasions, and received either AIH or Sham AIH intervention in a randomized order. AIH consisted of 15 brief (∼60s) periods of low oxygen (fraction of inspired O2 = 0.09) alternating with 60s of normoxia, whereas Sham AIH consisted of repeated exposures to normoxic air. High-density surface EMG of biceps and triceps brachii was recorded during maximal elbow flexion and extension. We then generated spatial maps which distinguished active muscle regions prior to and 60 min after AIH or Sham AIH. After an AIH sequence, elbow flexion and extension forces increased by 91.7 ± 88.4% and 51.7 ± 57.8% from baseline, respectively, whereas there was no difference after Sham AIH. Changes in strength were associated with an altered spatial distribution of EMG and increased root mean squared EMG amplitude in both biceps and triceps brachii muscles. These data suggest that altered motor unit activation profiles may underlie improved volitional strength after a single dose of AIH and warrant further investigation using single motor unit analysis techniques to further elucidate mechanisms of AIH-induced plasticity.

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.

Evolution of surface electromyography: From muscle electrophysiology towards neural recording and interfacing

Surface electromyography (EMG) comprises a recording of electrical activity from the body surface generated by muscle fibres during muscle contractions. Its characteristics depend on the fibre membrane potentials and the neural activation signal sent from the motor neurons to the muscles. EMG has been classically used as the primary investigation tool in kinesiology studies in a variety of applications. More recently, surface EMG techniques have evolved from single-channel methods to high-density systems with hundreds of electrodes. High-density EMG recordings can be deconvolved to estimate the discharge times of spinal motor neurons innervating the recorded muscles, with algorithms that have been developed and validated in the last two decades. Within limits and with some variability across muscles, these techniques provide a non-invasive method to study relatively large populations of motor neurons in humans. Surface EMG is thus evolving from a peripheral measure of muscle electrical activity towards a neural recording and neural interfacing signal. These advances in technology have had a major impact on our fundamental understanding of the neural control of movement and have exposed new perspectives in neurotechnologies. Here we provide an overview and perspective of modern EMG technology, as derived from past achievements, and its impact in neurophysiology and neural engineering.

Estimates of persistent inward currents in lower limb motoneurons are larger in females than in males

Noninvasive recordings of motor unit (MU) spike trains help us understand how the nervous system controls movement and how it adapts to various physiological conditions. The majority of participants in human and nonhuman animal physiology studies are male, and it is assumed that mechanisms uncovered in these studies are shared between males and females. However, sex differences in neurological impairment and physical performance warrant the study of sex as a biological variable in human physiology and performance. To begin addressing this gap in the study of biophysical properties of human motoneurons, we quantified MU discharge rates and estimates of persistent inward current (PIC) magnitude in both sexes. We decomposed MU spike trains from the tibialis anterior (TA), medial gastrocnemius (MG), and soleus (SOL) using high-density surface electromyography and blind source separation algorithms. Ten participants of each sex performed slow triangular (10 s up and down) isometric contractions to a peak of 30% of their maximum voluntary contraction. We then used linear mixed-effects models to determine if peak discharge rate and estimates of PICs were predicted by the fixed effects of sex, muscle, and their interaction. Despite a lack of sex-differences in peak discharge rates across all muscles, estimates of PICs were larger [χ2(1) = 6.26, P = 0.012] in females [4.73 ± 0.242 pulses per second (pps)] than in males (3.81 ± 0.240 pps). These findings suggest that neuromodulatory drive, inhibitory input, and/or biophysical properties of motoneurons differ between the sexes and may contribute to differences in MU discharge patterns.NEW & NOTEWORTHY Sex-related differences in motoneuron analyses have emerged with greater inclusion of female participants, however, mechanisms for these differences remain unclear. Estimates of persistent inward currents (i.e., ΔF) in motoneurons of the lower limb muscles were larger in females than in males. This suggests neuromodulatory drive, monoaminergic signaling, intrinsic motoneuron properties, and/or descending motor commands may differ between the sexes, which provides a potential mechanism underlying previously reported sex-related differences in motoneuron discharge patterns.

Size-dependent differences in mitochondrial volume density in phrenic motor neurons

Neuromotor control of diaphragm muscle (DIAm) motor units is dependent on an orderly size-dependent recruitment of phrenic motor neurons (PhMNs). Slow (type S) and fast, fatigue resistant (type FR) DIAm motor units, which are frequently recruited to sustain ventilation, comprise smaller PhMNs that innervate type I and IIa DIAm fibers. More fatigable fast (type FF) motor units, which are infrequently recruited for higher force, expulsive behaviors, comprise larger PhMNs that innervate more type IIx/IIb DIAm fibers. We hypothesize that due to the more frequent activation and thus higher energy demand of type S and FR motor units, the mitochondrial volume density (MVD) of smaller PhMNs is greater compared with larger PhMNs. In eight adult (6 mo old) Fischer 344 rats, PhMNs were identified via intrapleural injection of Alexa488-conjugated cholera toxin B (CTB). Following retrograde CTB labeling, mitochondria in PhMNs were labeled by transdural infusion of MitoTracker Red. PhMNs and mitochondria were imaged using multichannel confocal microscopy using a ×60 oil objective. Following optical sectioning and three-dimensional (3-D) rendering, PhMNs and mitochondria were analyzed volumetrically using Nikon Elements software. Analysis of MVD in somal and dendritic compartments was stratified by PhMN somal surface area. Smaller PhMNs (likely S and FR units) had greater somal MVDs compared with larger PhMNs (likely FF units). By contrast, proximal dendrites or larger PhMNs had higher MVD compared with dendrites of smaller PhMNs. We conclude that more active smaller PhMNs have a higher mitochondrial volume density to support their higher energy demand in sustaining ventilation.NEW & NOTEWORTHY Type S and FR motor units, comprising smaller phrenic motor neurons (PhMNs) are regularly activated to perform indefatigable ventilatory requirements. By contrast, type FF motor units, comprising larger PhMNs, are infrequently activated to perform expulsive straining and airway defense maneuvers. This difference in activation history is mirrored in the mitochondrial volume density (MVD), with smaller PhMNs having higher MVD than larger PhMNs. In proximal dendrites, this trend was reversed, with larger PhMNs having higher MVD than smaller PhMNs, likely due to the maintenance requirements for the larger dendritic arbor of FF PhMNs.

Adjustments in the motor unit discharge behavior following neuromuscular electrical stimulation compared to voluntary contractions

Introduction: The application of neuromuscular electrical stimulation superimposed on voluntary muscle contractions (NMES+) has demonstrated a considerable potential to enhance or restore muscle function in both healthy and individuals with neurological or orthopedic disorders. Improvements in muscle strength and power have been commonly associated with specific neural adaptations. In this study, we investigated changes in the discharge characteristics of the tibialis anterior motor units, following three acute exercises consisting of NMES+, passive NMES and voluntary isometric contractions alone. Methods: Seventeen young participants participated in the study. High-density surface electromyography was used to record myoelectric activity in the tibialis anterior muscle during trapezoidal force trajectories involving isometric contractions of ankle dorsi flexors with target forces set at 35, 50% and 70% of maximal voluntary isometric contraction (MVIC). From decomposition of the electromyographic signal, motor unit discharge rate, recruitment and derecruitment thresholds were extracted and the input-output gain of the motoneuron pool was estimated. Results: Global discharge rate increased following the isometric condition compared to baseline at 35% MVIC while it increased after all experimental conditions at 50% MVIC target force. Interestingly, at 70% MVIC target force, only NMES + led to greater discharge rate compared to baseline. Recruitment threshold decreased after the isometric condition, although only at 50% MVIC. Input-output gain of the motoneurons of the tibialis anterior muscle was unaltered after the experimental conditions. Discussion: These results indicated that acute exercise involving NMES + induces an increase in motor unit discharge rate, particularly when higher forces are required. This reflects an enhanced neural drive to the muscle and might be strongly related to the distinctive motor fiber recruitment characterizing NMES+.

High and Hyper: Fentanyl Induces Psychomotor Side-Effects in Healthy Pigs

Analgesic effects of fentanyl have been investigated using behavior. The behavioral effects of fentanyl and possible serotonergic influence are largely unknown. We therefore investigated behavioral effects of fentanyl, with or without the serotonin antagonist ketanserin, in pigs. Fourteen mixed-breed pigs, weighing 17-25 kg were included in a randomised blinded prospective, balanced three-group study. Ten pigs received first 5 and then 10 µg/kg of fentanyl intravenously. Ketanserin at 1 mg/kg or saline was given intravenously as a third injection. Four control pigs received three injections of saline. Behavior was video-recorded. The distance moved was automatically measured by commercially available software, and behaviors manually scored in retrospect. Fentanyl inhibited resting and playing, and induced different repetitive behaviors. The mean (SD) distance moved in the control group and fentanyl group was 21.3 (13.0) and 57.8 (20.8) metres respectively (p < 0.05 for pairwise comparison). A stiff gait pattern was seen after fentanyl injection for median (range) 4.2 (2.8-5.1) minutes per 10 min, which was reduced to 0 (0-4) s after ketanserin administration. Conclusion: fentanyl-induced motor and behavioral effects, and serotonergic transmission may be involved in some of them. The psychomotor side effects of fentanyl could potentially interfere with post-operative pain evaluation in pigs.

Linking cortex and contraction-Integrating models along the corticomuscular pathway

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

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

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

Skeletal muscle models composed of motor units: A review

The mathematical muscle models should include several aspects of muscle structure and physiology. First, muscle force is the sum of forces of multiple motor units (MUs), which have different contractile properties and play different roles in generating muscle force. Second, whole muscle activity is an effect of net excitatory inputs to a pool of motoneurons innervating the muscle, which have different excitability, influencing MU recruitment. In this review, we compare various methods for modeling MU twitch and tetanic forces and then discuss muscle models composed of different MU types and number. We first present four different analytical functions used for twitch modeling and show limitations related to the number of twitch describing parameters. We also show that a nonlinear summation of twitches should be considered in modeling tetanic contractions. We then compare different muscle models, most of which are variations of Fuglevand's model, adopting a common drive hypothesis and the size principle. We pay attention to integrating previously developed models into a consensus model based on physiological data from in vivo experiments on the rat medial gastrocnemius muscle and its respective motoneurons. Finally, we discuss the shortcomings of existing models and potential applications for studying MU synchronization, potentiation, and fatigue.

Revisiting the use of Hoffmann reflex in motor control research on humans

Research in movement science aims at unravelling mechanisms and designing methods for restoring and maximizing human functional capacity, and many techniques provide access to neural adjustments (acute changes) or long-term adaptations (chronic changes) underlying changes in movement capabilities. First described by Paul Hoffmann over a century ago, when an electrical stimulus is applied to a peripheral nerve, this causes action potentials in afferent axons, primarily the Ia afferents of the muscle spindles, which recruit homonymous motor neurons, thereby causing an electromyographic response known as the Hoffmann (H) reflex. This technique is a valuable tool in the study of the neuromuscular function in humans and has provided relevant information in the neural control of movement. The large use of the H reflex in motor control research on humans relies in part to its relative simplicity. However, such simplicity masks subtleties that require rigorous experimental protocols and careful data interpretation. After highlighting basic properties and methodological aspects that should be considered for the correct use of the H-reflex technique, this brief narrative review discusses the purpose of the H reflex and emphasizes its use as a tool to assess the effectiveness of Ia afferents in discharging motor neurones. The review also aims to reconsider the link between H-reflex modulation and Ia presynaptic inhibition, the use of the H-reflex technique in motor control studies, and the effects of ageing. These aspects are summarized as recommendations for the use of the H reflex in motor control research on humans.

Intrinsic motor neuron excitability is increased after resistance training in older adults

This study investigated the effects of high-intensity resistance training on estimates of the motor neuron persistent inward current (PIC) in older adults. Seventeen participants (68.5 ± 2.8 yr) completed a 2-wk nonexercise control period followed by 6 wk of resistance training. Surface electromyographic signals were collected with two 32-channel electrodes placed over soleus to investigate motor unit discharge rates. Paired motor unit analysis was used to calculate delta frequency (ΔF) as an estimate of PIC amplitudes during 1) triangular-shaped contractions to 20% of maximum torque capacity and 2) trapezoidal- and triangular-shaped contractions to 20% and 40% of maximum torque capacity, respectively, to understand their ability to modulate PICs as contraction intensity increases. Maximal strength and functional capacity tests were also assessed. For the 20% triangular-shaped contractions, ΔF [0.58-0.87 peaks per second (pps); P ≤ 0.015] and peak discharge rates (0.78-0.99 pps; P ≤ 0.005) increased after training, indicating increased PIC amplitude. PIC modulation also improved after training. During the control period, mean ΔF differences between 20% trapezoidal-shaped and 40% triangular-shaped contractions were 0.09-0.18 pps (P = 0.448 and 0.109, respectively), which increased to 0.44 pps (P < 0.001) after training. Also, changes in ΔF showed moderate to very large correlations (r = 0.39-0.82) with changes in peak discharge rates and broad measures of motor function. Our findings indicate that increased motor neuron excitability is a potential mechanism underpinning training-induced improvements in motor neuron discharge rate, strength, and motor function in older adults. This increased excitability is likely mediated by enhanced PIC amplitudes, which are larger at higher contraction intensities.NEW & NOTEWORTHY Resistance training elicited important alterations in soleus intrinsic motor neuronal excitability, likely mediated by enhanced persistent inward current (PIC) amplitude, in older adults. Estimates of PICs increased after the training period, accompanied by an enhanced ability to increase PIC amplitudes at higher contraction intensities. Our data also suggest that changes in PIC contribution to self-sustained discharging may contribute to increases in motor neuron discharge rates, maximal strength, and functional capacity in older adults after resistance training.

The effects of α-lactalbumin supplementation and handgrip contraction on soleus motoneuron excitability

INTRODUCTION

We tested two strategies that hypothetically increase serotonin availability (α-lactalbumin consumption and a remote submaximal handgrip contraction) on estimates of persistent inward currents (PICs) amplitude of soleus muscle in healthy participants.

METHODS

With a randomised, double-blind, and cross-over design, 13 healthy participants performed triangular-shaped ramp contractions with their plantar flexors (20% of maximal torque), followed by a 30-s handgrip sustained contraction (40% of maximal force) and consecutive repeated triangular-shaped contractions. This was performed before and after the consumption of either 40 g of α-lactalbumin, an isonitrogenous beverage (Zein) or an isocaloric beverage (Corn-starch). Soleus motor units discharge rates were analysed from high-density surface electromyography signals. PICs were estimated by calculating the delta frequency (ΔF) of motor unit train spikes using the paired motor unit technique.

RESULTS

ΔF (0.19 pps; p = 0.001; d = 0.30) and peak discharge rate (0.20 pps; p < 0.001; d = 0.37) increased after the handgrip contraction, irrespective of the consumed supplement. No effects of α-lactalbumin were observed.

CONCLUSIONS

Our results indicate that 40 g of α-lactalbumin was unable to modify intrinsic motoneuron excitability. However, performing a submaximal handgrip contraction before the plantar flexion triangular contraction was capable of increasing ΔF and discharge rates on soleus motor units. These findings highlight the diffused effects of serotonergic input, its effects on motoneuron discharge behaviour, and suggest a cross-effector effect within human motoneurons.

Effects of α-lactalbumin on strength, fatigue and psychological parameters: a randomised double-blind cross-over study

PURPOSE

The neurotransmitter serotonin has a strong effect on behaviour and motor control. Regarding motor control, serotonin contributes to the development of fatigue and is also involved in the ability of motor neurones to operate across a large range of forces (gain control). The consumption of tryptophan-rich supplements (such as α-lactalbumin) is of interest because this amino acid is the only precursor for brain serotonin synthesis. Therefore, the purpose of this study was to determine the effects of α-lactalbumin supplementation on neuromuscular performance.

METHODS

Using a randomised double-blind cross-over design, 16 healthy participants performed plantar flexor and handgrip maximal voluntary contractions, a 30-s submaximal handgrip contraction, and a plantar flexor fatigue protocol before and 90 min after consuming either 40 g of α-lactalbumin, an isonitrogenous beverage (Zein) or an isocaloric beverage (corn-starch). Sleepiness, mood, and cognition were assessed to evaluate any psychological effects.

RESULTS

α-Lactalbumin decreased force steadiness by 25% during the sustained submaximal handgrip contraction (p < 0.01) and induced greater fatigue (15% reduction in total torque-time integral, p = 0.01) during the fatigue protocol. These effects were not observed for the other control beverages. No effects were found for maximal or explosive strength, or psychological measurements.

CONCLUSIONS

40 g of α-lactalbumin increased handgrip force variability and reduced performance during fatiguing muscle contractions but did not influence brief maximal contractions or psychological parameters in healthy individuals. These findings support the hypothesis that the consumption of α-lactalbumin can increase motor neurone input-output gain and exacerbate central fatigue during sustained maximal exercise.

Differences in motor unit behavior during isometric contractions in patients with diabetic peripheral neuropathy at various disease severities

The aim of this study was to determine whether HD-sEMG is sensitive to detecting changes in motor unit behavior amongst healthy adults and type 2 diabetes mellitus (T2DM) patients presenting diabetic peripheral neuropathy (DPN) at different levels. Healthy control subjects (CON, n = 8) and T2DM patients presenting no DPN symptoms (ABS, n = 8), moderate DPN (MOD, n = 18), and severe DPN (SEV, n = 12) performed isometric ankle dorsiflexion at 30 % maximum voluntary contraction while high-density surface EMG (HD-sEMG) was recorded from the tibialis anterior muscle. HD-sEMG signals were decomposed, providing estimates of discharge rate, motor unit conduction velocity (MUCV), and motor unit territory area (MUTA). As a result, the ABS group presented reduced MUCV compared to CON. The groups with diabetes presented significantly larger MUTA compared to the CON group (p < 0.01), and the SEV group presented a significantly lower discharge rate compared to CON and ABS (p < 0.01). In addition, the SEV group presented significantly higher CoV_force compared to CON and MOD. These results support the use of HD-SEMG as a method to detect peripheral and central changes related to DPN.

A geometric approach to quantifying the neuromodulatory effects of persistent inward currents on individual motor unit discharge patterns

Objective.All motor commands flow through motoneurons, which entrain control of their innervated muscle fibers, forming a motor unit (MU). Owing to the high fidelity of action potentials within MUs, their discharge profiles detail the organization of ionotropic excitatory/inhibitory as well as metabotropic neuromodulatory commands to motoneurons. Neuromodulatory inputs (e.g. norepinephrine, serotonin) enhance motoneuron excitability and facilitate persistent inward currents (PICs). PICs introduce quantifiable properties in MU discharge profiles by augmenting depolarizing currents upon activation (i.e. PIC amplification) and facilitating discharge at lower levels of excitatory input than required for recruitment (i.e. PIC prolongation).Approach. Here, we introduce a novel geometric approach to estimate neuromodulatory and inhibitory contributions to MU discharge by exploiting discharge non-linearities introduced by PIC amplification during time-varying linear tasks. In specific, we quantify the deviation from linear discharge ('brace height') and the rate of change in discharge (i.e. acceleration slope, attenuation slope, angle). We further characterize these metrics on a simulated motoneuron pool with known excitatory, inhibitory, and neuromodulatory inputs and on human MUs (number of MUs; Tibialis Anterior: 1448, Medial Gastrocnemius: 2100, Soleus: 1062, First Dorsal Interosseus: 2296).Main results. In the simulated motor pool, we found brace height and attenuation slope to consistently indicate changes in neuromodulation and the pattern of inhibition (excitation-inhibition coupling), respectively, whereas the paired MU analysis (ΔF) was dependent on both neuromodulation and inhibition pattern. Furthermore, we provide estimates of these metrics in human MUs and show comparable variability in ΔFand brace height measures for MUs matched across multiple trials.Significance. Spanning both datasets, we found brace height quantification to provide an intuitive method for achieving graded estimates of neuromodulatory and inhibitory drive to individual MUs. This complements common techniques and provides an avenue for decoupling changes in the level of neuromodulatory and pattern of inhibitory motor commands.

Optimizing NV magnetometry for Magnetoneurography and Magnetomyography applications

Magnetometers based on color centers in diamond are setting new frontiers for sensing capabilities due to their combined extraordinary performances in sensitivity, bandwidth, dynamic range, and spatial resolution, with stable operability in a wide range of conditions ranging from room to low temperatures. This has allowed for its wide range of applications, from biology and chemical studies to industrial applications. Among the many, sensing of bio-magnetic fields from muscular and neurophysiology has been one of the most attractive applications for NV magnetometry due to its compact and proximal sensing capability. Although SQUID magnetometers and optically pumped magnetometers (OPM) have made huge progress in Magnetomyography (MMG) and Magnetoneurography (MNG), exploring the same with NV magnetometry is scant at best. Given the room temperature operability and gradiometric applications of the NV magnetometer, it could be highly sensitive in the pT / Hz -range even without magnetic shielding, bringing it close to industrial applications. The presented work here elaborates on the performance metrics of these magnetometers to the state-of-the-art techniques by analyzing the sensitivity, dynamic range, and bandwidth, and discusses the potential benefits of using NV magnetometers for MMG and MNG applications.

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.

Altered intramuscular network of lipid droplets and mitochondria in type 2 diabetes

Excessive storage of lipid droplets (LDs) in skeletal muscles is a hallmark of type 2 diabetes. However, LD morphology displays a high degree of subcellular heterogeneity and varies between single muscle fibers, which impedes the current understanding of lipid-induced insulin resistance. Using quantitative transmission electron microscopy (TEM), we conducted a comprehensive single-fiber morphological analysis to investigate the intramuscular network of LDs and mitochondria, and the effects of 8 wk of high-intensity interval training (HIIT) targeting major muscle groups, in patients with type 2 diabetes and nondiabetic obese and lean controls. We found that excessive storage of intramuscular lipids in patients with type 2 diabetes was exclusively explained by extremely large LDs situated in distinct muscle fibers with a location-specific deficiency in subsarcolemmal mitochondria. After HIIT, this intramuscular deficiency was improved by a remodeling of LD size and subcellular distribution and mitochondrial content. Analysis of LD morphology further revealed that individual organelles were better described as ellipsoids than spheres. Moreover, physical contact between LD and mitochondrial membranes indicated a dysfunctional interplay between organelles in the diabetic state. Taken together, type 2 diabetes should be recognized as a metabolic disease with high cellular heterogeneity in intramuscular lipid storage, underlining the relevance of single-cell technologies in clinical research. Furthermore, HIIT changed intramuscular LD storage toward nondiabetic characteristics.

Aging affects the number and morphological heterogeneity of rat phrenic motor neurons and phrenic motor axons

Diaphragm muscle (DIAm) motor units comprise a phrenic motor neuron (PhMN), the phrenic nerve and the muscle fibers innervated, with the size of PhMNs and axons characteristic of motor unit type. Smaller PhMNs and their axons comprise slow (type S) and fatigue-resistant (type FR) DIAm motor units, while larger PhMNs and their axons comprise more fatigable (type FF) motor units. With aging, we have shown a loss of larger PhMNs, consistent with selective atrophy of type IIx/IIb DIAm fibers and reduced maximum DIAm force. In the present study, we hypothesized that with aging there is a loss of larger myelinated phrenic α motor axons. Female and male young (6 months) and old (24 months) Fischer 344 rats were studied. PhMNs were retrogradely labeled by intrapleural injection of 488-conjugated CTB. The phrenic nerves were excised ~1 cm from the DIAm insertion and mounted in resin, and phrenic α motor axons were delineated based on size (i.e., >4 μm diameters). In older rats, the number of larger PhMNs and larger phrenic α motor axons were reduced. There were no differences in non-α axons. In addition, there was evidence of demyelination of larger phrenic α motor axons in older rats. Together, these findings are consistent with the selective age-related vulnerability of larger PhMNs and denervation of type FF motor units, which may underlie DIAm sarcopenia.

Skeletal muscle structure, physiology, and function

Contractions of skeletal muscles provide the stability and power for all body movements. Consequently, any impairment in skeletal muscle function results in some degree of instability or immobility. Factors that influence skeletal muscle structure and function are therefore of great interest scientifically and clinically. Injury, neuromuscular disease, and old age are among the factors that commonly contribute to impairments in skeletal muscle function. The goal of this chapter is to summarize the fundamentals of skeletal muscle structure and function to provide foundational knowledge for this Handbook volume. We examine the molecular interactions that provide the basis for the generation of force and movement, discuss mechanisms of the regulation of contraction at the level of myofibers, and introduce concepts of the activation and control of muscle function in vivo. Where appropriate, the chapter updates the emerging science that will increase understanding of muscle function.

Firing behavior of single motor units of the tibialis anterior in human walking as non-invasively revealed by HDsEMG decomposition

Objective.Investigation of the firing behavior of motor units (MUs) provides essential neuromuscular control information because MUs are the smallest organizational component of the neuromuscular system. The MUs activated during human infants' leg movements and rodent locomotion, mainly controlled by the spinal central pattern generator (CPG), show highly synchronous firing. In addition to spinal CPGs, the cerebral cortex is involved in neuromuscular control during walking in human adults. Based on the difference in the neural control mechanisms of locomotion between rodent, human infants and adults, MU firing behavior during adult walking probably has some different features from the other populations. However, so far, the firing activity of MUs in human adult walking has been largely unknown due to technical issues.Approach.Recent technical advances allow noninvasive investigation of MU firing by high-density surface electromyogram (HDsEMG) decomposition. We investigated the MU firing behavior of the tibialis anterior (TA) muscle during walking at a slow speed by HDsEMG decomposition.Main results.We found recruitment threshold modulation of MU between walking and steady isometric contractions. Doublet firings, and gait phase-specific firings were also observed during walking. We also found high MU synchronization during walking over a wide range of frequencies, probably including cortical and spinal CPG-related components. The amount of MU synchronization was modulated between the gait phases and motor tasks. These results suggest that the central nervous system flexibly controls MU firing to generate appropriate force of TA during human walking.Significance.This study revealed the MU behavior during walking at a slow speed and demonstrated the feasibility of noninvasive investigation of MUs during dynamic locomotor tasks, which will open new frontiers for the study of neuromuscular systems in the fields of neuroscience and biomedical engineering.

Flexible neural control of motor units

Voluntary movement requires communication from cortex to the spinal cord, where a dedicated pool of motor units (MUs) activates each muscle. The canonical description of MU function rests upon two foundational tenets. First, cortex cannot control MUs independently but supplies each pool with a common drive. Second, MUs are recruited in a rigid fashion that largely accords with Henneman's size principle. Although this paradigm has considerable empirical support, a direct test requires simultaneous observations of many MUs across diverse force profiles. In this study, we developed an isometric task that allowed stable MU recordings, in a rhesus macaque, even during rapidly changing forces. Patterns of MU activity were surprisingly behavior-dependent and could be accurately described only by assuming multiple drives. Consistent with flexible descending control, microstimulation of neighboring cortical sites recruited different MUs. Furthermore, the cortical population response displayed sufficient degrees of freedom to potentially exert fine-grained control. Thus, MU activity is flexibly controlled to meet task demands, and cortex may contribute to this ability.

Using fluorescent indicators for in vivo quantification of spontaneous or evoked motor neuron presynaptic activity in transgenic zebrafish

In this protocol, we describe steps that utilize the optical clarity of the zebrafish larvae and the stereotyped motor neuron axon structure in the trunk to measure spontaneous or evoked motor neuron axon activity. This activity is detected with transgenic fluorescent indicators introduced into the larvae by zygotic injection. Fluorescent indicator intensity changes in the small neuromuscular junctions are quantified to measure the presynaptic calcium activity and consequent synaptic vesicle release. For complete details on the use and execution of this protocol, please refer to Mandal et al. (2020).

Neural inputs from spinal motor neurons to lateralis vastus muscle: Comparison between sprinters and nonathletes

The adaptation of neural contractile properties has been observed in previous work. However, the neural changes on the motor unit (MU) level remain largely unknown. Voluntary movements are controlled through the precise activation of MU populations. In this work, we estimate the neural inputs from the spinal motor neurons to the muscles during isometric contractions and characterize the neural adaptation during training by comparing the MU properties decomposed from sprinters and nonathletes. Twenty subjects were recruited and divided into two groups. The high-density surface electromyography (EMG) signals were recorded from the lateralis vastus muscle during the isometric contraction of knee extension and were then decomposed into MU spike trains. Each MU’s action potentials and discharge properties were extracted for comparison across subject groups and tasks. A total of 1097 MUs were identified from all subjects. Results showed that the discharge rates and amplitudes of MUAPs from athletes were significantly higher than those from nonathletes. These results demonstrate the neural adaptations in physical training at the MU population level and indicate the great potential of EMG decomposition in physiological investigations.

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.

Our experimental understanding of the firing behaviour of motoneuron (MN) pools during human voluntary muscle contractions is currently limited to the observation of small samples of active MNs obtained from EMG decomposition. EMG decomposition therefore provides an important but incomplete description of the role of individual MNs in the firing activity of the complete MN pool, which limits our understanding of the neural strategies of the whole MN pool and of how the firing activity of each MN contributes to the neural drive to muscle. Here, we combine decomposed high-density EMG (HDEMG) data and a physiologically realistic model of MN population to predict the unknown recruitment and firing activity of the remaining unidentified MNs in the complete MN pool. In brief, an experimental estimation of the synaptic current is input to a cohort of MN models, which are calibrated using the available decomposed HDEMG data, and predict the MN spike trains fired by the entire MN population. This novel approach is experimentally validated and applied to muscle force prediction from neuromuscular modelling.

Spinal automaticity of movement control and its role in recovering function after spinal injury

INTRODUCTION

The significance of the spinal circuitry in controlling postural and locomotor functions largely re-emerged in the mid-1970s under the leadership of Sten Grillner, demonstrating key phenomena of "central pattern generation" and "fictive locomotion" with an evolutionary perspective. These concepts raised the question of how much function can be recovered after paralysis, given the intrinsic automaticity of spinal networks in injured and uninjured states in adults.

AREAS COVERED

This review explores biological mechanisms governing spinal control of movements such as posture and locomotion. We focus on concepts that have evolved from experiments performed over the past decade. Rather than a comprehensive review of the vast literature on the neural control of posture and locomotion, we focus on the various mechanisms underlying functional automaticity, and their clinical relevance.

EXPERT OPINION

We propose that multiple combinations of sensory mechanoreceptors linked to proprioception generate an infinite number of different sensory ensembles, having species-specific meaning and extensive influence in controlling posture and locomotion. These sensory ensembles are translated as a probabilistic phenomenon into highly specific but indeterminate actions. Therefore, we opine that spinal translation of these ensembles in real-time plays a central role in the automaticity of motor control in individuals with and without severe neuromotor dysfunction.

Training induced improvements in knee extensor force accuracy are associated with reduced vastus lateralis motor unit firing variability

NEW FINDINGS

What is the central question of this study? We aimed to determine levels of bilateral knee extensor force accuracy and any subsequent alterations to central and/or peripheral motor unit features, following 4 weeks of unilateral force accuracy training. What is the main finding and its importance? In the trained limb only, knee extensor force tracking accuracy improved with reduced motor unit firing rate variability in the vastus lateralis, and no change to neuromuscular junction transmission instability. Interventional strategies to improve force accuracy may be directed to older/clinical populations where such improvements may aid performance of daily living activities.

ABSTRACT

Background Muscle force output during sustained submaximal isometric contractions fluctuates around an average value and is partly influenced by variation in motor unit (MU) firing rates. MU firing rate (FR) variability seemingly reduces following exercise training interventions, however, much less is known with respect to peripheral MU properties. We therefore investigated whether targeted force accuracy training could lead to improved muscle functional capacity and control, in addition to determining any alterations of individual MU features. Methods Ten healthy participants (7 females, 3 males, 27±6 years, 170±8 cm, 69±16kg) underwent a 4-week supervised, unilateral knee extensor force accuracy training intervention. The coefficient of variation for force (FORCE^CoV ) and sinusoidal wave force tracking accuracy (FORCE^Sinu ) were determined at 25% maximal voluntary contraction (MVC) pre- and post-training. Intramuscular electromyography was utilised to record individual MU potentials from the vastus lateralis (VL) muscles at 25% MVC during sustained contractions, pre- and post-training. Results Knee extensor muscle strength remained unchanged following training, with no improvements in unilateral leg-balance. FORCE^CoV and FORCE^Sinu significantly improved in only the trained knee extensors by ∼13% (p = 0.01) and ∼30% (p<0.0001) respectively. MU FR variability significantly reduced in the trained VL by ∼16% (n = 8; p = 0.001), with no further alterations to MU FR or neuromuscular junction transmission instability. Conclusion Our results suggest muscle force control and tracking accuracy is a trainable characteristic in the knee extensors, which is likely explained by the reduction in MU FR variability which was apparent in the trained limb only. This article is protected by copyright. All rights reserved.

Segment-Wise Decomposition of Surface Electromyography to Identify Discharges Across Motor Neuron Populations

OBJECTIVE

The surface electromyography (EMG) decomposition techniques have shown promising results in neurophysiologic investigations, clinical diagnosis, and human-machine interfacing. However, current decomposition methods could only decode a limited number of motor units (MUs) because of the local convergence. The number of identified MUs remains similar even though more muscles or movements are involved, where multiple motor neuron populations are activated. The objective of this study was to develop a segment-wise decomposition strategy to increase the number of MU decoded from multiple motor neuron populations.

METHODS

The EMG signals were divided into several segments depending on the number of involved movements. The motor neurons, activated during each movement, were regarded as a population. The convolution kernel compensation (CKC) method was applied individually for each segment to decode the motor unit discharges from each motor neuron population. The MU filters were obtained in each segment and filtrated to estimate the MU spike trains (MUSTs) from the global EMG signals. The decomposition performance was validated on synthetic and experimental EMG signals.

MAIN RESULTS

From synthetic EMG signals generated by two motor neuron populations, the proposed segment-wise CKC (swCKC) decoded significantly more MUs during low and medium excitation levels, with an increased rate of 16.3% to 75.4% compared with the conventional CKC. From experimental signals recorded during ten motor tasks, 133±24 MUs with the pulse-to-noise ratio of 36.6±6.5 dB were identified for each subject by swCKC, whereas the conventional CKC identified only 43±12 MUs.

CONCLUSION AND SIGNIFICANCE

These results indicate the feasibility and superiority of the proposed swCKC to decode MU activities across motor neuron populations, extending the potential applications of EMG decomposition for neural decoding during multiple motor tasks.

Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units

OBJECTIVE

High-density surface electromyography (HD-sEMG) allows the reliable identification of individual motor unit (MU) action potentials. Despite the accuracy in decomposition, there is a large variability in the number of identified MUs across individuals and exerted forces. Here we present a systematic investigation of the anatomical and neural factors that determine this variability.

APPROACH

We investigated factors of influence on HD-sEMG decomposition, such as synchronization of MU discharges, distribution of MU territories, muscle-electrode distance (MED - subcutaneous adipose tissue thickness), maximum anatomical cross-sectional area (ACSA_max), and fiber CSA. For this purpose, we recorded HD-sEMG signals, ultrasound and, magnetic resonance images, and took a muscle biopsy from the biceps brachii muscle from 30 male participants drawn from two groups to ensure variability within the factors - untrained-controls (UT=14) and strength-trained individuals (ST=16). Participants performed isometric ramp contractions with elbow flexors (at 15, 35, 50 and 70% maximum voluntary torque - MVT). We assessed the correlation between the number of accurately detected MUs by HD-sEMG decomposition and each measured parameter, for each target force level. Multiple regression analysis was then applied.

MAIN RESULTS

ST subjects showed lower MED (UT=5.1±1.4 mm; ST=3.8±0.8 mm) and a greater number of identified motor units (UT:21.3±10.2 vs ST:29.2±11.8 MUs/subject across all force levels). The entire cohort showed a negative correlation between MED and the number of identified MUs at low forces (r= -0.6, p=0.002 at 15%MVT). Moreover, the number of identified MUs was positively correlated to the distribution of MU territories (r=0.56, p=0.01) and ACSA_max(r=0.48, p=0.03) at 15%MVT. By accounting for all anatomical parameters, we were able to partly predict the number of decomposed MUs at low but not at high forces.

SIGNIFICANCE

Our results confirmed the influence of subcutaneous tissue on the quality of HD-sEMG signals and demonstrated that MU spatial distribution and ACSA_maxare also relevant parameters of influence for current decomposition algorithms.

Detecting motor unit abnormalities in amyotrophic lateral sclerosis using high-density surface EMG

OBJECTIVE

The purpose of this study was to detect specific motor unit (MU) abnormalities in people with amyotrophic lateral sclerosis (ALS) compared to controls using high-density surface electromyography (HD-SEMG).

METHODS

Sixteen people with ALS and 16 control subjects. The participants performed ramp up and sustained contractions at 30% of their maximal voluntary contraction. HD-SEMG signals were recorded in the vastus lateralis muscle and decomposed into individual MU firing behavior using a convolution blind source separation method.

RESULTS

In total, 339 MUs were detected (people with ALS; n = 93, control subjects; n = 246). People with ALS showed significantly higher mean firing rate, recruitment threshold, coefficient of variation of the MU firing rate, MU firing rate at recruitment, and motoneurons excitability than those of control subjects (p < 0.001). The number of MU, MU firing rate, recruitment threshold, and MU firing rate at recruitment were significantly correlated with disease severity (p < 0.001). Multivariable analysis revealed that an increased MU firing rate at recruitment was independently associated with ALS.

CONCLUSIONS

These results suggest increased excitability at recruitment, which is consistent with neurodegeneration results in a compensatory increase in MU activity.

SIGNIFICANCE

Abnormal MU firing behavior provides an important physiological index for understanding the pathophysiology of ALS.