Roger Maro Enoka

This study introduces the Motor-unit Mode Network (MMNet), a deep variational autoencoder framework for extracting motor-unit modes, determining the number of modes for each participant, and quantifying motor-unit contributions to modes. MMNet combines convolutional and recurrent neural networks to capture nonlinear relations and temporal dependencies across motor units. High-density electromyography signals were recorded from the lateral gastrocnemius, medial gastrocnemius, and soleus of ten healthy participants during submaximal isometric contractions. The elbow point in the variance-explained curve was used to determine the optimal number of modes. Gradient-based attribution and mutual information analyses were performed to assess the physiological relevance of the modes. MMNet achieved greater reconstruction accuracy than the comparison methods and, on average, explained more than 90% of the variance with three modes. Mode number ranged from two to five across participants, most commonly three. Attribution analysis revealed shared motor-unit contributions to the extracted modes, and mutual information demonstrated significant coupling between the modes and the applied force (p = 0.003), with no significant differences among methods. These findings establish MMNet as a unified framework that leverages nonlinear temporal modeling to improve low-dimensional reconstruction, select the number of modes for each participant, and quantify motor-unit contributions through gradient-based attribution.

Discharge characteristics of motor units in the first dorsal interosseous (FDI) muscle differed during low-force isometric contractions applied in three different directions: abduction, flexion, or abduction + flexion (combined). Despite these differences, a single dominant mode explained at least 93% of the variance in discharge rates across all directions. These findings indicate the low-dimensional organization underlying motor-unit activity during low-force isometric contractions with the FDI muscle is preserved across directions despite differences in discharge characteristics.

The purpose of this review was to examine the extent to which variability in the cumulative set of action potentials sent from the spinal cord (neural drive) to limb muscles can explain the variance in performance of middle-aged and older adults on the NIH Toolbox measures of motor function. Neural-drive variability is attributable to two spinal mechanisms: low-frequency oscillations in the shared synaptic input onto alpha motor neurons and synaptic noise in the generation and transmission of action potentials by individual motor neurons. Evidence indicates that the coefficient of variation for force during submaximal contractions (a behavioral proxy for neural-drive variability) explains moderate amounts of the variance in performance scores on the tests for balance, dexterity, and endurance, whereas locomotion is associated with motor-unit discharge characteristics in calf muscles and handgrip strength seems to be related to the timing of motor-unit activity across forearm-hand muscles. These findings indicate that some of the variance in performance on a range of dynamic motor tasks can be explained by neural-drive variability during submaximal isometric contractions. Future work needs to expand the repertoire of tasks from which measures of neural-drive variability are derived, which may increase its explanatory power for the observed variance in performance scores of middle-aged and older adults on Toolbox measures of motor function.

The aim of the study was to compare motor‐unit discharge characteristics across regions of the hamstring muscles during hip‐extension and knee‐flexion. Fourteen healthy adults (2 females) performed isometric contractions with the hip extensors and knee flexors at 10% and 40% of maximal voluntary contraction (MVC) torque. High‐density surface electromyography was recorded from proximal and distal regions of biceps femoris and semitendinosus. Motor units were decomposed and tracked between tasks using a filter reapplication approach. The outcome measures included mean discharge rate (MDR), coefficient of variation for interspike interval (CoV _ISI ), and standard deviation of the filtered cumulative spike train (SD of fCST). Task differences in common synaptic input were assessed at 10% MVC using within‐muscle coherence derived from CSTs in the delta band. Maximal torque was ~24% higher in hip‐extension than knee‐flexion, accompanied by a ~31% increase in torque variability. Across all the identified motor units and those that were tracked, MDR (~5%–14%), CoV _ISI (~7%–11%) and SD of fCST (~10%–16%) were greater during hip‐extension, whereas delta‐band coherence was greater across muscles and regions during knee‐flexion ( p = 0.02– p < 0.001; d = 1.11–1.94). Moreover, proximal regions generally exhibited greater values for MDR (~11%) during knee‐flexion, whereas modulation was greater in distal regions during hip‐extension (~4%, p < 0.01). The neural‐drive variability was greater proximally than distally for both tasks (~16%, p = 0.01). The neural control of motor units differs between proximal and distal regions of the hamstrings during hip‐extension and knee‐flexion. Hamstring testing and exercise selection need to consider the task and the muscle region being examined.

Objective: The purpose of this study was to compare the influence of biological maturity status and training experience on motor performance in young athletes of different sport disciplines. Methods: Youth athletes (n = 84, 23 females) from five different sports (basketball, volleyball, track and field, wrestling, and badminton) participated in this study. Jump height was measured for the squat jump (SJ) and countermovement jump (CMJ). Peak torque during maximal voluntary contractions (MVCs) and torque steadiness at 20% MVC were assessed during plantar flexion (PF) and dorsiflexion (DF). Postural control was assessed with the one-leg test for both the right and left legs. K-means clustered analysis categorized participants into groups of low and high performers. Results: High performers had greater training experience than low performers for the SJ (p < 0.05), with no difference in maturity status (p > 0.05). Similarly, high performers had greater training experience (p < 0.05) than low performers for the CMJ, with no difference in maturity status (p > 0.05). High performers were more mature than low performers for MVC torque of DF (p < 0.001) and PF (p < 0.001), with no group differences in training experience (DF: p > 0.05; PF: p > 0.05). Maturity status for torque steadiness differed only for DF (p < 0.001), whereas there was no difference for PF (p > 0.05). There were no differences in either maturity status or training experience for one-leg-stance time (p > 0.05). Conclusions: These findings suggest that maturity status and training experience are linked to performance, although their relative roles differ across tasks. These findings reflect an interaction between biological maturity, training background and sports performance in youth athletes.

The scientific literature on human motor units and electromyography (EMG) spans over a century (1925-2025), comprising research impossible to synthesize manually. We introduce NeuromechaniX, a domain-specific platform for automated extraction and meta-analysis of this literature. The core component, MUscraper, is a large language model pipeline that extracts approximately 200 structured metadata fields, organized into 17 major sections spanning participant demographics, EMG acquisition parameters, muscle identification, task protocols, decomposition methods, and motor-unit outcomes, from ∼2,000 publications on human limb muscles. This automated extraction transforms heterogeneous narrative reports into a standardized, queryable database at a scale not achievable through manual review. From this dataset, we analyzed motor-unit discharge rate across 208 studies examining seven muscles. Our analyses reveal that discharge rates differ significantly among muscles (p<0.001), with biceps brachii exhibiting the highest rates (15.9 pps), followed by first dorsal interosseous (13.7 pps) and tibialis anterior (13.5 pps), whereas gastrocnemius (11.3 pps), the vastii muscles (11.5 pps) and soleus show the lowest rates (9.9 pps). Sex-stratified analysis shows females exhibit higher discharge rates than males (14.5 vs 11.9 pps; Cohen’s d=0.38, p=0.018). In contrast, age-stratified analysis reveals non-significant differences between young and older adults (d=-0.24, p=0.072). Collectively, these results show that current views of human motor units are limited to a few muscles, with little data on females and older adults. The complete structured database is available through an open-access interactive platform ( https://neuro-mechanix.com/metadata ), enabling researchers to explore, filter, and download the extracted metadata. NeuromechaniX provides infrastructure for large-scale meta-research, identification of literature gaps, and hypothesis generation for the neuromechanics community.

Purpose : The present study explored the age-related influence of foot placement on balance control during quiet standing in tandem stance. Although tandem stance is widely used to assess postural control, foot dominance is rarely standardized in balance testing, even though it may influence stability outcomes. This study addressed this gap by examining whether dominant-foot placement affects postural control across the adult lifespan. Methods : One-hundred participants (53 women) were separated into five age groups: 21–30, 31–40, 41–50, 51–60, and 61–75 years. They stood upright on a force plate with the dominant foot placed either in the front or back in two visual conditions (eyes open vs. eyes closed). Postural control was assessed by measuring center-of-pressure displacement. Results : Analysis of variances indicated that center-of-pressure displacement increased across age groups ( p < .01). For both visual conditions (eyes open or closed) and across all age groups, center-of-pressure displacement was reduced when the dominant foot was placed at the back during tandem stance ( p < .05). Conclusion : This finding underscores the importance of considering foot dominance when assessing postural control during tandem stance. Standardizing foot placement relative to dominance may enhance the reliability and comparability of balance assessments across studies and age groups.

Although load compliance influences the discharge characteristics of the same motor units in first dorsal interosseus (FDI) during submaximal isometric contractions, most of the variance in discharge rate across conditions is explained by a single neural module (motor unit mode). Moreover, the first motor unit mode for the tracked motor units was more correlated with fluctuations in force (force task) or acceleration (position task) than was the cumulative spike train.

The findings of this study suggest that the force produced by the tibialis anterior muscle during submaximal isometric contractions is controlled by two anatomically distinct motor unit modes. Moreover, factor and coherence analyses indicated that motor units in proximal and distal regions of the muscle received independent shared synaptic inputs. These results challenge the assumption of a uniform neural drive to the tibialis anterior muscle during submaximal isometric contractions.