Individual Motor Units Research Articles

Motor unit dysregulation following 15days of unilateral lower limb immobilisation.

Disuse atrophy, caused by situations of unloading such as limb immobilisation, causes a rapid yet diverging reduction in skeletal muscle function when compared to muscle mass. While mechanistic insight into the loss of mass is well studied, deterioration of muscle function with a focus towards the neural input to muscle remains underexplored. This study aimed to determine the role of motor unit adaptation in disuse-induced neuromuscular deficits. Ten young, healthy male volunteers underwent 15days of unilateral lower limb immobilisation with intramuscular electromyography (iEMG) bilaterally recorded from the vastus lateralis (VL) during knee extensor contractions normalised to maximal voluntary contraction (MVC), pre and post disuse. Muscle cross-sectional area was determined by ultrasound. Individual MUs were sampled and analysed for changes in motor unit (MU) discharge and MU potential (MUP) characteristics. VL CSA was reduced by approximately 15% which was exceeded by a two-fold decrease of 31% in muscle strength in the immobilised limb, with no change in either parameter in the non-immobilised limb. Parameters of MUP size were reduced by 11% to 24% with immobilisation, while neuromuscular junction (NMJ) transmission instability remained unchanged, and MU firing rate decreased by 8% to 11% at several contraction levels. All adaptations were observed in the immobilised limb only. These findings highlight impaired neural input following immobilisation reflected by suppressed MU firing rate which may underpin the disproportionate reductions of strength relative to muscle size. KEY POINTS: Muscle mass and function decline rapidly in situations of disuse such as bed rest and limb immobilisation. The reduction in muscle function commonly exceeds that of muscle mass, which may be associated with the dysregulation of neural input to muscle. We have used intramuscular electromyography to sample individual motor unit and near fibre potentials from the vastus lateralisfollowing 15days of unilateral limb immobilisation. Following disuse, the disproportionate loss of muscle strength when compared to size coincided with suppressed motor unit firing rate. These motor unit adaptations were observed at multiple contraction levels and in the immobilised limb only. Our findings demonstrate neural dysregulation as a key component of functional loss following muscle disuse in humans.

Differences in motor unit firing properties of the vastus lateralis muscle during postural and voluntary tasks.

The firing properties of the motor units are usually affected by the motor task. However, it has not been clarified whether the firing properties of the motor units of a specific muscle are different between postural and voluntary tasks. Therefore, this study investigated whether the recruitment and rate coding of the motor units differ between these two motor tasks. Thirteen healthy volunteers performed trapezoidal muscle contraction with a target value of 15% maximum electromyography (EMG) activity by voluntary left knee extension in the sitting position (voluntary task) and postural maintenance in the semi-squatting position (postural task) with a knee flexion angle of 30°. We obtained four channels of surface EMG activity during each task from left vastus lateralis muscle. We extracted the firing properties of individual motor units using the EMG decomposition algorithm. The recruitment threshold and motor unit action potential amplitude were significantly lower in the postural task than in the voluntary task, and conversely, the mean firing rate was significantly higher. These results were explained by the preferential recruitment of motor units with higher recruitment threshold and amplitude in the voluntary task, while motor units with lower recruitment threshold and higher firing rate were preferentially recruited in the postural task. Preferential activation of fatigue-resistant motor units in the postural task is a reasonable strategy as it allows for sustained postural maintenance. We provide the first evidence that motor unit firing properties are clearly different between postural and voluntary tasks, even at the same muscle activity level.

Acute changes in motor unit discharge property after concentric versus eccentric contraction exercise in knee extensor

This study aimed to investigate the motor unit firing property immediately after concentric or eccentric contraction exercise. Eighteen healthy men performed repetitive maximal isokinetic knee extension exercises with only concentric or eccentric contraction until they exerted less than 80% of the baseline strength. Before and after the fatiguing exercise, high-density surface electromyography of the vastus lateralis was recorded during submaximal ramp-up isometric contraction and individual motor units were identified. Only motor units that could be tracked before and after exercise were analyzed. Muscle cross-sectional area of the vastus lateralis was measured using ultrasound, and electrically evoked torque was recorded before and after the exercise. Sixty-five and fifty-three motor units were analyzed before and after the concentric and eccentric contractions, respectively. The results showed that motor units with moderate to high recruitment thresholds significantly decreased recruitment thresholds under both conditions, and the motor unit discharge rates significantly increased after concentric contraction compared to eccentric contraction. A greater muscle cross-sectional area was observed with concentric contraction. The evoked torque was significantly decreased under both conditions, but no difference between the conditions. These results suggest that fatiguing exercise with concentric contraction contributes to greater neural input to muscles and metabolic responses than eccentric contraction.

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 (ACSAmax), and fiber cross-sectional area. 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 MUs (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 ACSAmax (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 ACSAmax are also relevant parameters of influence for current decomposition algorithms.

High-performance Flexible Microelectrode Array with PEDOT:PSS Coated 3D Micro-cones for Electromyographic Recording.

High signal-to-noise ratio (SNR) electromyography (EMG) recordings are essential for identifying and analyzing single motor unit activity. While high-density electrodes allow for greater spatial resolution, the smaller electrode area translates to a higher impedance and lower SNR. In this study, we developed an implantable and flexible 3D microelectrode array (MEA) with low impedance that enables high-quality EMG recording. With polyimide micro-cones realized by standard photolithography process and PEDOT:PSS coating, this design can increase effective surface area by up to 250% and significantly improve electrical performance for electrode sites with various geometric surface areas, where the electrode impedance is at most improved by 99.3%. Acute EMG activity from mice was recorded by implanting the electrodes in vivo, and we were able to detect multiple individual motor units simultaneously and with high resolution ([Formula: see text]). The charge storage capacity was measured to be 34.2 mC/cm2, indicating suitability of the electrodes for stimulation applications as well.

Modelling intra-muscular contraction dynamics using in silico to in vivo domain translation

BackgroundAdvances in sports medicine, rehabilitation applications and diagnostics of neuromuscular disorders are based on the analysis of skeletal muscle contractions. Recently, medical imaging techniques have transformed the study of muscle contractions, by allowing identification of individual motor units’ activity, within the whole studied muscle. However, appropriate image-based simulation models, which would assist the continued development of these new imaging methods are missing. This is mainly due to a lack of models that describe the complex interaction between tissues within a muscle and its surroundings, e.g., muscle fibres, fascia, vasculature, bone, skin, and subcutaneous fat. Herein, we propose a new approach to overcome this limitation.MethodsIn this work, we propose to use deep learning to model the authentic intra-muscular skeletal muscle contraction pattern using domain-to-domain translation between in silico (simulated) and in vivo (experimental) image sequences of skeletal muscle contraction dynamics. For this purpose, the 3D cycle generative adversarial network (cycleGAN) models were evaluated on several hyperparameter settings and modifications. The results show that there were large differences between the spatial features of in silico and in vivo data, and that a model could be trained to generate authentic spatio-temporal features similar to those obtained from in vivo experimental data. In addition, we used difference maps between input and output of the trained model generator to study the translated characteristics of in vivo data.ResultsThis work provides a model to generate authentic intra-muscular skeletal muscle contraction dynamics that could be used to gain further and much needed physiological and pathological insights and assess and overcome limitations within the newly developed research field of neuromuscular imaging.

Decoding finger movement patterns from microscopic neural drive information based on deep learning

Recent development of surface electromyogram (sEMG) decomposition technique provides a good basis of decoding movements from individual motor unit (MU) activities that directly representing microscopic neural drives. How to interpret the function and contribution of each decomposed MU to macroscopic movements remains unclear. The objective of this study is to decode finger movement patterns by establishing a relationship between individual MU activities and movements. In this study, high-density sEMG (HD-sEMG) data were recorded by a 16 × 8 electrode array from finger extensor muscles of 10 subjects performing 10 finger movement patterns. The progressive FastICA peel-off algorithm was first applied to decompose the HD-sEMG data to obtain microscopic neural drives in terms of MU firing sequences and their corresponding action potential waveforms. Then, convolutional neural network was used for classification of the decomposed MUs by characterizing their spatial waveforms spanned over all channels of the array. On this basis, a fuzzy weighted decision strategy was designed to give a final decision of movement pattern recognition, where function of an individual MU was measured in the form of contributing into all movement patterns with different weights to solve the issue of MUs shared among multiple patterns due to muscle co-activation. The proposed method yielded an average accuracy approximating to 100%, and it outperformed other common MU-based methods or conventional myoelectric classification methods using macroscopic sEMG features (p < 0.05). The proposed method has a wide application prospect in the field of human-machine interaction and precise motor control.

Effects of hand muscle function and dominance on intra-muscle synergies.

The goal of the study was to explore the effects of hand dominance and muscle function (prime mover vs. supporting muscle) on recently discovered intra-muscle synergies as potential windows into their neural origin. Healthy right-handed subjects performed accurate cyclical force production tasks while pressing with the middle phalanges and distal phalanges of the fingers of the dominant and non-dominant hand. Surface electromyography was used to identify individual motor unit action potentials in two muscles, flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC). Stable motor unit groups (MU-modes) were defined in each muscle and in both muscles together. The composition of the MU-modes allowed linking them to the reciprocal and co-activation command. Force-stabilizing synergies were quantified in each hand and during force production at both sites using the framework of the uncontrolled manifold hypothesis. Force-stabilizing synergies were seen in the spaces of MU-modes from FDS and EDC separately, but not of MU-modes defined for both muscles together. Synergy indices were similar for both hands and both sites of force application. In contrast, force-stabilizing synergies in the space of finger forces were present in the non-dominant hand and absent in the dominant hand. The data suggest existence of distributed mechanisms of synergic control. Finger force synergies are likely to reflect functioning of subcortical loops involving the basal ganglia and cerebellum, while MU-mode synergies are likely to reflect spinal circuitry. Studies of both force-based and motor-unit-based synergies may be clinically valuable for distinguishing effects of spinal and supraspinal disorders.

Consensus for experimental design in electromyography (CEDE) project: High-density surface electromyography matrix

High-density surface electromyography (HDsEMG) can be used to measure the spatial distribution of electrical muscle activity over the skin. As this distribution is associated with the generation and propagation of muscle fiber action potentials, HDsEMG is processed to extract information on regional muscle activation, muscle fiber characteristics and behaviour of individual motor units. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, summarizes recommendations on the use of HDsEMG in experimental studies. For each application, recommendations are included regarding electrode montage, electrode type and configuration, electrode location and orientation, data analysis, and interpretation. Cautions and reporting standards are also included. The steps of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers when collecting, reporting, and interpreting HDsEMG data. It is hoped that this document will be used to generate new empirical evidence to improve how HDsEMG is used in research and in clinical applications.

Evaluation of decomposition parameters for high-density surface electromyogram using fast independent component analysis algorithm

The surface electromyogram (sEMG) signal reveals the electrical neuromuscular activities and offers theoretical and clinical information. Recently, exploring motoneuron discharge events at the microscopic level through decomposition has been proposed as a promising analysis approach, which can surpass traditional global sEMG-based analysis method in some aspects. However, computational efficiency is an essential issue when discharge events of individual motor unit are decomposed using blind source separation algorithms. Therefore, choosing proper parameters of decomposition algorithms for different research purposes is important. Accordingly, we have systematically investigated the influences between computation time and decomposition performance for fast independent component analysis (FastICA)-based sEMG decomposition algorithm under different value selections of five decomposition parameters, namely the percentage of eliminated channels, extension factor, the number of decomposition iteration loops, the number of maximum inner loops in each iteration and sampling frequency. We employed high-density sEMG signals from 14 intact subjects during muscle contractions of four-digit extension and flexion at different force levels (20% and 50% maximum voluntary contraction) and a public dataset for sEMG decomposition. According to obtained results, we offer four preference suggestions (less computation time, more motor units, higher accuracy and trade-off). Results show that the trade-off values with consideration of decomposition performance and computation time are recommended as 25% of channels with minimal root mean square, extension factor of 4, 200 iteration loop numbers of decomposition, 20 maximum inner loop numbers and 2048 sampling frequency. Overall, this paper provides a guide for researchers to determine proper decomposition parameters for sEMG decomposition-related works.

Neuromuscular recruitment strategies of the vastus lateralis according to sex.

AimDespite males typically exhibiting greater muscle strength and fatigability than females, it remains unclear if there are sex‐based differences in neuromuscular recruitment strategies e.g. recruitment and modulation of motor unit firing rate (MU FR) at normalized forces and during progressive increases in force.MethodsThe study includes 29 healthy male and 31 healthy female participants (18‐35 years). Intramuscular electromyography (iEMG) was used to record individual motor unit potentials (MUPs) and near‐fibre MUPs from the vastus lateralis (VL) during 10% and 25% maximum isometric voluntary contractions (MVC), and spike‐triggered averaging was used to obtain motor unit number estimates (MUNE) of the VL.ResultsMales exhibited greater muscle strength (P < .001) and size (P < .001) than females, with no difference in force steadiness at 10% or 25% MVC. Females had 8.4% and 6.5% higher FR at 10% and 25% MVC, respectively (both P < .03), while the MUP area was 33% smaller in females at 10% MVC (P < .02) and 26% smaller at 25% MVC (P = .062). However, both sexes showed similar increases in MU size and FR when moving from low‐ to mid‐level contractions. There were no sex differences in any near‐fibre MUP parameters or in MUNE.ConclusionIn the vastus lateralis, females produce muscle force via different neuromuscular recruitment strategies to males which is characterized by smaller MUs discharging at higher rates. However, similar strategies are employed to increase force production from low‐ to mid‐level contractions. These findings of similar proportional increases between sexes support the use of mixed sex cohorts in studies of this nature.

Monosynaptic facilitation mediated by group Ia afferents from deltoid to biceps brachii motoneurons in humans.

Effects of low-threshold afferents from the anterior (DA), middle (DM) and posterior parts of the deltoid (DP) on the excitability of biceps brachii (BB) motoneurons in humans were studied. We evaluated the effects on individual motor units and motoneuron pool using a post-stimulus time-histogram (PSTH) and an electromyogram-averaging (EMG-A) methods, respectively, in 11 healthy human subjects. Electrical conditioning stimulation was delivered to the axillary nerve branch innervating DA (DA nerve), DM (DM nerve) and DP (DP nerve) with the intensity below the motor threshold. In the PSTH study, stimulation to the DA, DM and DP nerves produced a significant peak (facilitation) in 26/40 (65%), 28/47 (59%) and 0/32 (0%) of BB motor units, respectively. Since the central latency of the facilitation from the DA and DM nerves was 0.1 ± 0.3 and 0.1 ± 0.2ms (mean ± S.D.) longer than that of the homonymous monosynaptic Ia facilitation of BB, respectively, the facilitation thus being compatible with monosynaptic path. In the EMG-A study, stimulation to the DA and DM nerves produced a significant peak (facilitation) for the BB motoneuron pool in all the subjects, whereas stimulation to the DP nerve produced no effect on BB. The facilitation diminished by vibration stimulation, and the suppression lasted for 30-40min after removal of the vibration. Therefore, group Ia afferents should be responsible for the facilitation. These findings suggest that monosynaptic facilitation mediated by group Ia afferents from the DA and DM nerves to BB motoneurons exists in humans.

Inter-Person Differences in Isometric Coactivations of Triceps Surae and Tibialis Anterior Decrease in Young, but Not in Older Adults After 14 Days of Bed Rest

We examined activation patterns of the gastrocnemius medialis (GM), gastrocnemius lateralis (GL), soleus (SO), and tibialis anterior (TA) muscles in eight older (58.4 ± 3.3 years) and seven young (23.1 ± 2.9 years) participants, before and after 14 days of horizontal bed rest. Visual feedback on the exerted muscle torque was provided to the participants. The discharge patterns of individual motor units (MUs) were studied in three repetitions of isometric plantar flexion at 30 and 60% of Maximum Voluntary Contraction (MVC), before, and 1 day after the 14-day bed rest, respectively. In the GL and GM muscles, the older participants demonstrated higher MU discharge rates than the young, regardless of the contraction level, both before and after the bed rest. In the TA and SO muscles, the differences between the older and young participants were less consistent. Detailed analysis revealed person-specific changes in the MU discharge rates after the bed rest. To quantify the coactivation patterns we calculated the correlation coefficients between the cumulative spike trains of identified MUs from each muscle, and measured the root mean square difference of the correlation coefficients between the trials of the same session (intra-session variability) and between different sessions (inter-session variability) in each participant (intra-person comparison) and across participants (inter-person comparison). In the intra-person comparison, the inter-session variability was higher than the intra-session variability, either before or after the bed rest. At 60% MVC torque, the young demonstrated higher inter-person variability of coactivation than the older participants, but this variability decreased significantly after the bed rest. In older participants, inter-person variability was consistently lower at 60% than at 30% MVC torque. In young participants, inter-person variability became lower at 60% than at 30% MVC torque only after the bed rest. Precaution is required when analyzing the MU discharge and coactivation patterns, as individual persons demonstrate individual adaptations to aging or bed rest.

Circulating testosterone and dehydroepiandrosterone are associated with individual motor unit features in untrained and highly active older men

Long-term exercise training has been considered as an effective strategy to counteract age-related hormonal declines and minimise muscle atrophy. However, human data relating circulating hormone levels with motor nerve function are scant. The aims of the study were to explore associations between circulating sex hormone levels and motor unit (MU) characteristics in older men, including masters athletes competing in endurance and power events. Forty-three older men (mean ± SD age: 69.9 ± 4.6 years) were studied based on competitive status. The serum concentrations of dehydroepiandrosterone (DHEA), total testosterone (T) and estradiol were quantified using liquid chromatography mass spectrometry. Intramuscular electromyographic signals were recorded from vastus lateralis (VL) during 25% of maximum voluntary isometric contractions and processed to extract MU firing rate (FR), and motor unit potential (MUP) features. After adjusting for athletic status, MU FR was positively associated with DHEA levels (p = 0.019). Higher testosterone and estradiol were associated with lower MUP complexity; these relationships remained significant after adjusting for athletic status (p = 0.006 and p = 0.019, respectively). Circulating DHEA was positively associated with MU firing rate in these older men. Higher testosterone levels were associated with reduced MUP complexity, indicating reduced electrophysiological temporal dispersion, which is related to decreased differences in conduction times along axonal branches and/or MU fibres. Although evident in males only, this work highlights the potential of hormone administration as a therapeutic interventional strategy specifically targeting human motor units in older age.

Skilled independent control of individual motor units via a non-invasive neuromuscular–machine interface

Objective. Brain–machine interfaces (BMIs) have the potential to augment human functions and restore independence in people with disabilities, yet a compromise between non-invasiveness and performance limits their relevance. Approach. Here, we hypothesized that a non-invasive neuromuscular–machine interface providing real-time neurofeedback of individual motor units within a muscle could enable independent motor unit control to an extent suitable for high-performance BMI applications. Main results. Over 6 days of training, eight participants progressively learned to skillfully and independently control three biceps brachii motor units to complete a 2D center-out task. We show that neurofeedback enabled motor unit activity that largely violated recruitment constraints observed during ramp-and-hold isometric contractions thought to limit individual motor unit controllability. Finally, participants demonstrated the suitability of individual motor units for powering general applications through a spelling task. Significance. These results illustrate the flexibility of the sensorimotor system and highlight individual motor units as a promising source of control for BMI applications.

Decoding muscle force from individual motor unit activities using a twitch force model and hybrid neural networks

A deep learning method involving hybrid neural networks incorporated with a physiological twitch force model is presented for decoding muscle force from individual motor unit (MU) activities. A series of MU action potential (MUAP) trains were obtained using a progressive FastICA peel-off algorithm through high-density surface electromyogram (HD-sEMG) decomposition. The twitch force model was adopted to transform MUAP trains into twitch force sequences. The hybrid convolutional neural networks (CNNs) consisting of a spatial attention model (SA-CNN) and a bidirectional gated recurrent unit (Bi-GRU) were fed by the twitch force sequences to predict the muscle force. The performance of the proposed method was evaluated in predicting the thumb abduction force using both simulated data and experimental HD-sEMG recordings from abductor pollicis brevis muscles of ten subjects. The simulation approach assisted our method design in confirming a simplified relationship between MUAP amplitude and force contribution of each MU. When processing experimental data, the root mean square deviation (RMSD) values between the predicted and the actual forces were 6.57% ± 1.26% and 7.18% ± 0.96% under the user-specific testing scheme and the user-independent testing scheme, respectively. The proposed method outperformed other common sEMG amplitude-based or MU-based methods with significantly decreased RMSD values (p < 0.001). These findings indicate the advance of mining spatial information from individual MU activities using deep neural networks in decoding the muscle force. This study provides a useful tool for muscle force estimation, with wide applications in biomechanics and sports rehabilitation.

Reciprocal and coactivation commands at the level of individual motor units in an extrinsic finger flexor-extensor muscle pair.

We explored the synergic organization of motor units in extrinsic finger muscles, flexor digitorum superficialis (FDS), and extensor digitorum communis (EDC). Healthy subjects produced accurate cyclical force by pressing with the middle phalanges of one of the three fingers (Index, Middle, and Ring) and all three together. Two wireless sensor arrays were used to record and identify motor unit action potentials in FDS and EDC. Stable motor unit groups were identified within each muscle and across both muscles. Analysis of motor units combined over the two muscles showed one of the first two motor unit groups with consistently opposite signs of the loading factors for the FDS and EDC motor units, and the other group with consistently same signs of the loading factors for the two muscles. We interpret the two motor unit groups as reflections of the reciprocal and co-activation commands within the theory of control with spatial referent coordinates. Force changes within the cycle were primarily associated with the modulation of the co-activation motor unit group. Analysis of inter-cycle variance within the spaces of motor unit groups defined for FDS and EDC separately showed force-stabilizing synergies across both single-finger and three-finger tasks. In contrast, analysis within the motor unit groups defined across both muscles failed to show force-stabilizing synergies. We interpret these results as a reflection of the trade-off across levels within a hierarchical control system.

Identification of Motor Unit Twitch Properties in the Intact Human In Vivo.

Restoring natural motor function in neurologically injured individuals is challenging, largely due to the lack of personalization in current neurorehabilitation technologies. Signal-driven neuro-musculoskeletal models may offer a novel paradigm for devising novel closed-loop rehabilitation strategies according to an individual's physiology. However, current modelling techniques are constrained to bipolar electromyography (EMG), thereby lacking the resolution necessary to extract the activity of individual motor units (MUs) in vivo. In this work, we decoded MU spike trains from high-density (HD)-EMG to obtain relevant neural properties across multiple isometric plantar-dorsiflexion tasks. Then, we sampled MU statistical distributions and used them to reproduce MU specific activation profiles. Results showed bimodal distributions which may correspond to slow and fast MU populations. The estimated activation profiles showed a high degree of similarity to the reference torque (R2>0.8) across the recorded muscles. This suggests that the estimation of MU twitch properties is a crucial step for the translation of neural information into muscle force.Clinical Relevance- This work has multiple implications for understanding the underlying mechanism of motor impairment and for developing closed-loop strategies for modulating alpha motor circuitries in neurologically injured individuals.

What's all the hype with fibre type? Selective single fibre adaptations with lifelong endurance exercise.

What's all the hype with fibre type? Selective single fibre adaptations with lifelong endurance exercise.

Changes in neural drive to calf muscles during steady submaximal contractions after repeated static stretches

Repeated static-stretching interventions consistently increase the range of motion about a joint and decrease total joint stiffness, but findings on the changes in muscle and connective-tissue properties are mixed. The influence of these stretch-induced changes on muscle function at submaximal forces is unknown. To address this gap in knowledge, the changes in neural drive to the plantar flexor muscles after a static-stretch intervention were estimated. Neural drive to the plantar flexor muscles during a low-force contraction increased after repeated static stretches. These findings suggest that adjustments in motor unit activity are necessary at low forces to accommodate reductions in the force-generating and transmission capabilities of the muscle-tendon unit after repeated static stretches of the calf muscles. Static stretching decreases stiffness about a joint, but its influence on muscle-tendon unit function and muscle activation is unclear. We investigated the influence of three static stretches on changes in neural drive to the plantar flexor muscles, both after a stretch intervention and after a set of maximal voluntary contractions (MVCs). Estimates of neural drive were obtained during submaximal isometric contractions by decomposing high-density electromyographic signals into the activity of individual motor units from medial gastrocnemius, lateral gastrocnemius and soleus. Motor units were matched across contractions and an estimate of neural drive to the plantar flexors was calculated by normalizing the cumulative spike train to the number of active motor units (normalized neural drive). Mean discharge rate increased after the stretch intervention during the 10% MVC task for all recorded motor units and those matched across conditions (all, P=0.0046; matched only, P=0.002), recruitment threshold decreased for motor units matched across contractions (P=0.022), and discharge rate at recruitment was elevated (P=0.004). Similarly, the estimate of normalized neural drive was significantly greater after the stretch intervention at 10% MVC torque (P=0.029), but not at 35% MVC torque. The adjustments in motor unit activity required to complete the 10% MVC task after stretch may have been partially attenuated by a set of plantar flexor MVCs. The increase in neural drive required to produce low plantar-flexion torques after repeated static stretches of the calf muscles suggests stretch-induced changes in muscle and connective tissue properties.