Less common synaptic input between muscles from the same group allows for more flexible coordination strategies during a fatiguing task

Changes in torque complexity with fatigue are related to motor unit behaviour

Physiological complexity is believed to reflect a system's adaptability to environmental challenges having been proposed as an indirect indicator of the functional capacity of the neuromuscular system. This study aimed to investigate the association between torque complexity's changes with neuromuscular fatigue and motor unit parameters. Twenty-one healthy and young adults visited the laboratory on one occasion. Knee extension maximum voluntary isometric contractions and isometric contractions at 30% of maximum were collected at baseline and immediately after a fatiguing knee extension protocol, which consisted of a series of concentric and eccentric knee extensions at 90°/s until exhaustion. Torque signals were sampled continuously, and torque complexity was assessed through an entropy measure. Motor unit-related parameters were extracted from the submaximal trials and further analysed. Our findings demonstrate that torque complexity's alteration pre-to-post neuromuscular fatigue is highly correlated with vastus lateralis and medialis average firing rate (r = - 0.618 and r = - 0.659, respectively) and peak motor unit action potential amplitude (rs = - 0.801 and rs = - 0.703, respectively) pre-fatigue. Moreover, alterations in torque complexity were observed, indicating a loss of adaptability within the neuromuscular system with neuromuscular fatigue. Overall, our findings supported our hypothesis by demonstrating alterations in torque complexity with neuromuscular fatigue, rendering the system less adaptable. Moreover, our results added to the current knowledge by highlighting the association between torque complexity's changes with neuromuscular fatigue and motor unit parameters.

Age-related breakdown in networks of inter-muscular coordination

Assessing inter-muscular coordination in older adults is crucial, as it directly impacts an individual's ability for independent functioning, injury prevention, and active engagement in daily activities. However, the precise mechanisms by which distinct muscle fiber types synchronize their activity across muscles to generate coordinated movements in older adults remain unknown. Our objective is to investigate how distinct muscle groups dynamically synchronize with each other in young and older adults during exercise. Thirty-five young adults and nine older adults performed one bodyweight squat set until exhaustion. Simultaneous surface electromyography (sEMG) recordings were taken from the left and right vastus lateralis, and left and right erector spinae. To quantify inter-muscular coordination, we first obtained ten time series of sEMG band power for each muscle, representing the dynamics of different muscle fiber types. Next, we calculated the bivariate equal-time Pearson's cross-correlation for each pair of sEMG band power time series across all leg and back muscles. The main results show (i) an overall reduction in the degree of inter-muscular coordination, and (ii) increased stratification of the inter-muscular network in older adults compared to young adults. These findings suggest that as individuals age, the global inter-muscular network becomes less flexible and adaptable, hindering its ability to reorganize effectively in response to fatigue or other stimuli. This network approach opens new avenues for developing novel network-based markers to characterize multilevel inter-muscular interactions, which can help target functional deficits and potentially reduce the risk of falls and neuro-muscular injuries in older adults.

Motor unit discharge behavior in human muscles throughout force gradation: a systematic review and meta-analysis with meta-regression

The analysis of motor unit (MU) discharge behavior provides an effective way of assembling information about the generation and control of movement. In this systematic review and meta-analysis, we identified and summarized the literature investigating MU discharge rate and discharge rate variability (CoV-ISI) during voluntary isometric contractions at various force levels. Databases were searched up to January 7, 2025, and a total of 262 studies were included. The meta-means of MU discharge rate and CoV-ISI were estimated and compared across human muscles. The influence of contraction intensity on MU discharge behavior was assessed through linear meta-regressions. At low-to-moderate forces [<60% maximal voluntary contraction (MVC)], the first dorsal interosseous, biceps brachii (BB), and forearm extensors (FEs) had the highest discharge rate, whereas the soleus had the lowest. At high force levels (>60% MVC), the tibialis anterior (TA) had the highest mean discharge rate compared with all other muscles, with the soleus maintaining the lowest. Regarding CoV-ISI results at low forces (<30% MVC), the TA had the lowest CoV-ISI values, except in comparison with the vastii. In addition, the vastii had lower CoV-ISI values than the FE, gastrocnemius medialis, and soleus. Contraction intensity was positively associated with the mean discharge rates in all muscles investigated, although some muscles showed steeper slopes than others. Similar results were observed for CoV-ISI meta-regressions, with muscle-specific differences in slope. These findings suggest potential variations in neural control strategies across muscles during force gradation, such as differences in the relative contribution of rate coding to facilitate increasing force demands.

Influence of age and feedback modality on the proprioceptive sense of force: insights from motor unit recordings

The primary purpose of our study was to compare the influence of feedback modality (visual vs. auditory) on force-reproduction accuracy in middle-aged and older adults. As a secondary objective, we investigated whether expected differences would be reflected in the neural drive sent to a hand muscle during the task. Participants (n = 42; 40-84 yr) performed a force-reproduction task with the first dorsal interosseus muscle at two target forces [5% and 20% of maximal voluntary contraction (MVC)]. Each trial involved a target phase that was guided by visual or auditory feedback and then a reproduction phase without feedback. The neural drive was characterized by measures of force steadiness and motor unit discharge characteristics during the target phase. Force-reproduction accuracy at the lower target force declined with increasing age and with visual feedback compared with auditory feedback. In contrast, there was no evidence of an effect of age or condition on force-reproduction accuracy at the moderate target force (20% MVC). Force steadiness was worse and motor unit coherence in the delta and beta bands was greater when the task was guided by auditory feedback at both target forces. These findings indicate that greater accuracy during the low-force task in the auditory-feedback condition was accompanied by a noisier control signal and differences in motor unit coherence in the delta and beta bands during the target phase.NEW & NOTEWORTHY The sense of force can be assessed with force-reproduction tasks, which typically involve visual feedback of the applied force during the target phase. Middle-aged and older adults improved force-reproduction accuracy when using auditory instead of visual feedback. This effect was accompanied by an increase in motor unit coherence in the beta band. This provides evidence for different sensorimotor processing of proprioceptive inputs when these sensory modalities are used to provide feedback of the applied force.

Postural control of sway dynamics on an unstable surface reduces similarity in activation patterns of synergistic lower leg muscles

Introduction

Diversity of activation patterns within synergistic muscles can be important for stability control in challenging conditions. This study investigates the similarity of activation patterns within the triceps surae and quadriceps femoris muscles and the effects of unstable surface during a visually guided postural task.

Methods

Eighteen healthy adults performed a visually guided anteroposterior tracking task on both stable and unstable surfaces. Electromyographic activity of triceps surae (gastrocnemius medialis, gastrocnemius lateralis, soleus) and quadriceps femoris (vastus medialis, vastus lateralis, rectus femoris) was recorded at 1,000 Hz. Cosine similarity (CS) between muscle pairs within each muscle group was calculated to assess the similarity of activation patterns of synergistic muscles for stable and unstable conditions. To compare the CS of the muscle pairs, a linear mixed model was used. For all tests the level of significance was set to α = 0.05.

Results

Across all surface conditions, CS values within the triceps surae muscles were lower than those of the quadriceps (p < 0.001), indicating a greater diversity in activation patterns of the distal muscles. The unstable surface reduced CS values for both muscle groups (p = 0.021). No significant interaction was observed between muscle pair and surface condition (p = 0.833).

Discussion

The reduced similarity of activation patterns within the synergistic triceps surae and quadriceps femoris muscles on the soft surface indicates an increased flexibility of neuromotor control for the unstable condition. The lower similarity within the synergistic triceps surae muscles suggests a higher diversity of activation patterns compared to the quadriceps femoris muscles, which may increase the flexibility of neuromotor control to meet specific joint stabilization challenges during the studied tracking task.

Higher dominant muscle strength is mediated by motor unit discharge rates and proportion of common synaptic inputs

Neural determinants explaining the asymmetrical force and skill observed in limb dominance still need to be comprehensively investigated. To address this gap, we recorded myoelectrical activity from biceps brachii using high-density surface electromyography in twenty participants, identifying the maximal voluntary force (MVF) and performing isometric ramp contractions at 35% and 70%MVF and sustained contractions at 10%MVF. Motor unit discharge characteristics were assessed during ramp contractions, the proportion of common synaptic input to motoneurons was calculated with coherence analysis, and the firing rate hysteresis (∆F) was used to estimate spinal motoneuron intrinsic properties. The dominant limbs presented a greater MVF compared to the non-dominant side (+ 9%, p = 0.001), with similar relative recruitment and derecruitment thresholds of motor units (p > 0.05). The discharge rate was significantly higher on the dominant side (p < 0.001), along with a greater proportion of common synaptic input (+ 14%, p = 0.002). No significant differences were observed in the ∆F (p > 0.05). Our findings suggest that greater strength on the dominant side is associated with higher neural drive to muscles due to a greater proportion of common synaptic inputs rather than differences in motoneuron intrinsic properties. These results underscore neural asymmetries at the motor unit level, corresponding to different mechanical outputs underlying limb dominance.

Adaptive Modification in Agonist Common Drive After Combined Blood Flow Restriction and Neuromuscular Electrical Stimulation

Neuromuscular electrical stimulation (NMES) combined with blood flow restriction (BFR) has garnered attention in rehabilitation for its ability to enhance muscle strength, despite the potential to accelerate training-related fatigue. This study examined changes in force scaling capacity immediately following combined NMES and BFR, focusing on motor unit synergy between agonist pairs. Fifteen participants (23.3 ± 1.8 years) trained with combined BFR and NMES on the extensor carpi radialis longus (ECRL) muscle, with maximal voluntary contraction (MVC) of wrist extension, along with force and EMG in the ECRL and extensor carpi radialis brevis (ECRB), measured during a designate force-tracking before and after training. Factor analysis identified latent modes influencing motor unit coordination between the ECRB and ECRL. The results showed a significant decrease in MVC after training (p < 0.001). Post-test force fluctuations increased (p = 0.031), along with a decrease in the mean inter-spike interval (M_ISI) in the ECRL (p = 0.022). Factor analysis revealed an increase in the proportion of motor units (MUs) jointly regulated by the neural mode for both ECRB and ECRL, coupled with a decline in independently regulated MUs. Specifically, the proportion of MUs governed by the ECRL mode decreased, while those regulated by the ECRB mode increased. In conclusion, force generation capacity and force scaling are impaired after receiving combined NMES and BFR treatment. It involves redistribution of the common drive to MUs within two agonists, affecting the flexible coordination of muscle synergy and necessitating compensatory recruitment of MUs from the less fatigable agonist.

Distinct Neural Drives along the Semitendinosus Muscle

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Effect of prior neuromuscular electrical stimulation of vastus lateralis on the fatigue induced by a sustained voluntary knee extension in men

PURPOSE

The purpose of this study was to investigate the effect of vastus lateralis (VL) selective fatigue induced by neuromuscular electrical stimulation (NMES) on knee extensor electromyographic (EMG) activity during a sustained submaximal isometric contraction.

METHODS

Thirteen healthy men (28 ± 5 years) completed two experimental sessions in which either the VL was pre-fatigued for 17 min (NMES session) or no intervention was performed (control session, CTRL). Subsequently, participants were asked to sustain an isometric knee extension at 20 % of maximal voluntary contraction (MVC) torque until task failure.

RESULTS

VL M-wave amplitude was reduced (-34 ± 26 %, P = 0.008) following the NMES intervention, while MVC torque was reduced by 26 ± 10 %. The time to task failure was 23 ± 10 % shorter (P = 0.002) in NMES (186 ± 75 s) than in CTRL (251 ± 128 s). EMG activity measured during the sustained contraction was higher for vastus medialis and rectus femoris muscles in NMES compared to CTRL (P < 0.001), but was comparable for VL (P > 0.05). The extent and origin of neuromuscular fatigue at task failure measured through MVCs combined with electrically-evoked contractions did not differ between NMES and CTRL.

CONCLUSION

Compensatory activity from synergist muscles occurred in response to a pre-fatigue intervention, which reduced the time to task failure of a sustained submaximal contraction but did not affect the extent and origin of neuromuscular fatigue.

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

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

Fatigue-related changes in intermuscular electromyographic coherence across rotator cuff and deltoid muscles in individuals with and without subacromial pain

Neuromuscular fatigue induces superior migration of the humeral head in individuals with subacromial pain. This has been attributed to weakness of rotator cuff muscles and overactive deltoid muscles. Investigation of common inputs to motoneuron pools of the rotator cuff and deltoid muscles offers valuable insight into the underlying mechanisms of neuromuscular control deficits associated with subacromial pain. This study aims to investigate intermuscular coherence across the rotator cuff and deltoid muscles during a sustained submaximal isometric fatiguing contraction in individuals with and without subacromial pain. Twenty symptomatic and 18 asymptomatic young adults participated in this study. Surface electromyogram (EMG) was recorded from the middle deltoid (MD) and infraspinatus (IS). Intramuscular EMG was recorded with fine-wire electrodes in the supraspinatus (SS). Participants performed an isometric fatiguing contraction of 30° scaption at 25% maximum voluntary contraction (MVC) until endurance limit. Pooled coherence of muscle pairs (SS-IS, SS-MD, IS-MD) in the 2-5 Hz (delta), 5-15 Hz (alpha), and 15-35 Hz (beta) frequency bands during the initial and final 30 s of the fatigue task were compared. SS-IS and SS-MD delta-band coherence increased with fatigue in the asymptomatic group but not the symptomatic group. In the alpha and beta bands, SS-IS and SS-MD coherence increased with fatigue in both groups. IS-MD beta-band coherence was greater in the symptomatic than the asymptomatic group. Individuals with subacromial pain failed to increase common drive across rotator cuff and deltoid muscles and have altered control strategies during neuromuscular fatigue. This may contribute to glenohumeral joint instability and subacromial pain experienced by these individuals.NEW & NOTEWORTHY Through the computation of shared neural drive across glenohumeral muscles, this study reveals that individuals with subacromial pain were unable to increase shared neural drive within the rotator cuff and across the supraspinatus and deltoid muscles during neuromuscular fatigue induced by sustained isometric contraction. These deficits in common drive across the shoulder muscles likely contribute to the joint instability and pain experienced by these individuals.

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

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

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.

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.

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.

Online prediction of sustained muscle force from individual motor unit activities using adaptive surface EMG decomposition

Decoding movement intentions from motor unit (MU) activities to represent neural drive information plays a central role in establishing neural interfaces, but there remains a great challenge for obtaining precise MU activities during sustained muscle contractions. In this paper, we presented an online muscle force prediction method driven by individual MU activities that were decomposed from prolonged surface electromyogram (SEMG) signals in real time. In the training stage of the proposed method, a set of separation vectors was initialized for decomposing MU activities. After transferring each decomposed MU activity into a twitch force train according to its action potential waveform, a neural network was designed and trained for predicting muscle force. In the subsequent online stage, a practical double-thread-parallel algorithm was developed. One frontend thread predicted the muscle force in real time utilizing the trained network and the other backend thread simultaneously updated the separation vectors. To assess the performance of the proposed method, SEMG signals were recorded from the abductor pollicis brevis muscles of eight subjects and the contraction force was simultaneously collected. With the update procedure in the backend thread, the force prediction performance of the proposed method was significantly improved in terms of lower root mean square deviation (RMSD) of around 10% and higher fitness (R2) of around 0.90, outperforming two conventional methods. This study provides a promising technique for real-time myoelectric applications in movement control and health.

Adaptive Online Decomposition of Surface EMG Using Progressive FastICA Peel-Off

This study presents a method for adaptive online decomposition of high-density surface electromyogram (SEMG) signals to overcome the performance degradation during long-term recordings. The proposed method utilized the progressive FastICA peel-off (PFP) method and integrated a practical double-thread-parallel algorithm into the conventional two-stage calculation approach. During the offline initialization stage, a set of separation vectors was computed. In the subsequent online decomposition stage, a backend thread was implemented to periodically update the separation vectors using the constrained FastICA algorithm and the automatic PFP method. Concurrently, the frontend thread employed the newly updated separation vectors to accurately extract motor unit (MU) spike trains in real time. To assess the effectiveness of the proposed method, simulated and experimental SEMG signals from abductor pollicis brevis muscles of ten subjects were used for evaluation. The results demonstrated that the proposed method outperformed the conventional method, which relies on fixed separation vectors. Specifically, the proposed method showed an improved matching rate by 3.63% in simulated data and 1.98% in experimental data, along with an increased motor unit number by 2.39 in simulated data and 1.30 in experimental data. These findings illustrated the feasibility of the proposed method to enhance the performance of online SEMG decomposition. As a result, this work holds promise for various applications that require accurate MU firing activities in decoding neural commands and building neural-machine interfaces.

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

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

Menstrual Cycle Associated Alteration of Vastus Lateralis Motor Unit Function

BACKGROUND

Estrogen and progesterone are the primary female sex hormones and have net excitatory and inhibitory effects, respectively, on neuronal function. Fluctuating concentrations across the menstrual cycle has led to several lines of research in relation to neuromuscular function and performance; however evidence from animal and cell culture models has yet to be demonstrated in human motor units coupled with quantification of circulating hormones. Intramuscular electromyography was used to record motor unit potentials and corresponding motor unit potential trains from the vastus lateralis of nine eumenorrheic females during the early follicular, ovulation and mid luteal phases of the menstrual cycle, alongside assessments of neuromuscular performance. Multi-level regression models were applied to explore effects of time and of contraction level. Statistical significance was accepted as p < 0.05.

RESULTS

Knee extensor maximum voluntary contraction, jump power, force steadiness, and balance did not differ across the menstrual phases (all p > 0.4). Firing rate of low threshold motor units (10% maximum voluntary contraction) was lower during the ovulation and mid luteal phases (β = - 0.82 Hz, p < 0.001), with no difference in motor unit potentials analysed from 25% maximum voluntary contraction contractions. Motor unit potentials were more complex during ovulation and mid luteal phase (p < 0.03), with no change in neuromuscular junction transmission instability (p > 0.3).

CONCLUSIONS

Assessments of neuromuscular performance did not differ across the menstrual cycle. The suppression of low threshold motor unit firing rate during periods of increased progesterone may suggest a potential inhibitory effect and an alteration of recruitment strategy; however this had no discernible effect on performance. These findings highlight contraction level-dependent modulation of vastus lateralis motor unit function over the eumenorrheic cycle, occurring independently of measures of performance.

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.

Network of muscle fibers activation facilitates inter-muscular coordination, adapts to fatigue and reflects muscle function

Fundamental movement patterns require continuous skeletal muscle coordination, where muscle fibers with different timing of activation synchronize their dynamics across muscles with distinct functions. It is unknown how muscle fibers integrate as a network to generate and fine tune movements. We investigate how distinct muscle fiber types synchronize across arm and chest muscles, and respond to fatigue during maximal push-up exercise. We uncover that a complex inter-muscular network of muscle fiber cross-frequency interactions underlies push-up movements. The network exhibits hierarchical organization (sub-networks/modules) with specific links strength stratification profile, reflecting distinct functions of muscles involved in push-up movements. We find network reorganization with fatigue where network modules follow distinct phase-space trajectories reflecting their functional role and adaptation to fatigue. Consistent with earlier observations for squat movements under same protocol, our findings point to general principles of inter-muscular coordination for fundamental movements, and open a new area of research, Network Physiology of Exercise.

Neuromuscular control: from a biomechanist's perspective

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

Decoding firings of a large population of human motor units from high-density surface electromyogram in response to transcranial magnetic stimulation

We describe a novel application of methodology for high-density surface electromyography (HDsEMG) decomposition to identify motor unit (MU) firings in response to transcranial magnetic stimulation (TMS). The method is based on the MU filter estimation from HDsEMG decomposition with convolution kernel compensation during voluntary isometric contractions and its application to contractions elicited by TMS. First, we simulated synthetic HDsEMG signals during voluntary contractions followed by simulated motor evoked potentials (MEPs) recruiting an increasing proportion of the motor pool. The estimation of MU filters from voluntary contractions and their application to elicited contractions resulted in high (>90%) precision and sensitivity of MU firings during MEPs. Subsequently, we conducted three experiments in humans. From HDsEMG recordings in first dorsal interosseous and tibialis anterior muscles, we demonstrated an increase in the number of identified MUs during MEPs evoked with increasing stimulation intensity, low variability in the MU firing latency and a proportion of MEP energy accounted for by decomposition similar to voluntary contractions. A negative relationship between the MU recruitment threshold and the number of identified MU firings was exhibited during the MEP recruitment curve, suggesting orderly MU recruitment. During isometric dorsiflexion we also showed a negative association between voluntary MU firing rate and the number of firings of the identified MUs during MEPs, suggesting a decrease in the probability of MU firing during MEPs with increased background MU firing rate. We demonstrate accurate identification of a large population of MU firings in a broad recruitment range in response to TMS via non-invasive HDsEMG recordings. KEY POINTS: Transcranial magnetic stimulation (TMS) of the scalp produces multiple descending volleys, exciting motor pools in a diffuse manner. The characteristics of a motor pool response to TMS have been previously investigated with intramuscular electromyography (EMG), but this is limited in its capacity to detect many motor units (MUs) that constitute a motor evoked potential (MEP) in response to TMS. By simulating synthetic signals with known MU firing patterns, and recording high-density EMG signals from two human muscles, we show the feasibility of identifying firings of many MUs that comprise a MEP. We demonstrate the identification of firings of a large population of MUs in the broad recruitment range, up to maximal MEP amplitude, with fewer required stimuli compared to intramuscular EMG recordings. The methodology demonstrates an emerging possibility to study responses to TMS on a level of individual MUs in a non-invasive manner.

Association between force fluctuation during isometric ankle abduction and variability of neural drive in peroneus muscles

Analyzing motor unit (MU) activities of peroneus muscles may reveal the causes of force control deficits of ankle eversion. This study aimed to examine peroneus muscles' MU discharge characteristics and associations between force fluctuation and variability of the neural drive in healthy participants. Thirty-one healthy males participated in this study. MU activities were identified from high-density surface electromyography of peroneus muscles during ankle eversion at 15 and 30% of maximal voluntary contraction (MVC). Participants increased the contraction level until reaching the target and held it for 15 s. The central 10 s of the hold phase were used for analysis. A cumulative spike train (CST) was calculated using MU firings. Variabilities of the force and CST are represented by the coefficient of variation (CoV). Spearman's rank correlation coefficient was used to assess the association between CoV of force and CoV of CST. For 15 and 30 % MVC trials, CoV of force was 1.86 ± 1.59 and 1.57 ± 1.26%, and CoV of CST was 5.01 ± 3.24 and 4.51 ± 2.78%, respectively. The correlation was significant at 15% (rho = 0.27, p < 0.001) and 30% (rho = 0.32, p < 0.001) MVC. Our findings suggest that in peroneus muscles, force fluctuation weakly to moderately correlates with neural drive variability.

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

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

The Neuromuscular Fatigue-Induced Loss of Muscle Force Control

Neuromuscular fatigue is characterised not only by a reduction in the capacity to generate maximal muscle force, but also in the ability to control submaximal muscle forces, i.e., to generate task-relevant and precise levels of force. This decreased ability to control force is quantified according to a greater magnitude and lower complexity (temporal structure) of force fluctuations, which are indicative of decreased force steadiness and adaptability, respectively. The "loss of force control" is affected by the type of muscle contraction used in the fatiguing exercise, potentially differing between typical laboratory tests of fatigue (e.g., isometric contractions) and the contractions typical of everyday and sporting movements (e.g., dynamic concentric and eccentric contractions), and can be attenuated through the use of ergogenic aids. The loss of force control appears to relate to a fatigue-induced increase in common synaptic input to muscle, though the extent to which various mechanisms (afferent feedback, neuromodulatory pathways, cortical/reticulospinal pathways) contribute to this remains to be determined. Importantly, this fatigue-induced loss of force control could have important implications for task performance, as force control is correlated with performance in a range of tasks that are associated with activities of daily living, occupational duties, and sporting performance.

Inter-muscular networks of synchronous muscle fiber activation

Skeletal muscles continuously coordinate to facilitate a wide range of movements. Muscle fiber composition and timing of activation account for distinct muscle functions and dynamics necessary to fine tune muscle coordination and generate movements. Here we address the fundamental question of how distinct muscle fiber types dynamically synchronize and integrate as a network across muscles with different functions. We uncover that physiological states are characterized by unique inter-muscular network of muscle fiber cross-frequency interactions with hierarchical organization of distinct sub-networks and modules, and a stratification profile of links strength specific for each state. We establish how this network reorganizes with transition from rest to exercise and fatigue-a complex process where network modules follow distinct phase-space trajectories reflecting their functional role in movements and adaptation to fatigue. This opens a new area of research, Network Physiology of Exercise, leading to novel network-based biomarkers of health, fitness and clinical conditions.

Handedness is associated with less common input to spinal motor neurons innervating different hand muscles

Whether the neural control of manual behaviours differs between the dominant and non-dominant hand is poorly understood. This study aimed to determine whether the level of common synaptic input to motor neurons innervating the same or different muscles differs between the dominant and the non-dominant hand. Seventeen participants performed two motor tasks with distinct mechanical requirements: an isometric pinch and an isometric rotation of a pinched dial. Each task was performed at 30% of maximum effort and was repeated with the dominant and non-dominant hand. Motor units were identified from two intrinsic (flexor digitorum interosseous and thenar) and one extrinsic muscle (flexor digitorum superficialis) from high-density surface electromyography recordings. Two complementary approaches were used to estimate common synaptic inputs. First, we calculated the coherence between groups of motor neurons from the same and from different muscles. Then, we estimated the common input for all pairs of motor neurons by correlating the low-frequency oscillations of their discharge rate. Both analyses led to the same conclusion, indicating less common synaptic input between motor neurons innervating different muscles in the dominant hand than in the non-dominant hand, which was only observed during the isometric rotation task. No between-side differences in common input were observed between motor neurons of the same muscle. This lower level of common input could confer higher flexibility in the recruitment of motor units, and therefore, in mechanical outputs. Whether this difference between the dominant and non-dominant arm is the cause or the consequence of handedness remains to be determined.

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.