Cumulative Spike Train Research Articles

Achilles tendon morpho-mechanical parameters are related to triceps surae motor unit firing properties.

Recent studies combining high-density surface electromyography (HD-sEMG) and ultrasound imaging have yielded valuable insights into the relationship between motor unit activity and muscle contractile properties. However, limited evidence exists on the relationship between motor unit firing properties and tendon morpho-mechanical properties. This study aimed to determine the relationship between triceps surae motor unit firing properties and the morpho-mechanical properties of the Achilles tendon (AT). Motor unit firing properties [i.e. mean discharge rate (DR) and coefficient of variation of the interspike interval (COVisi)] and motor unit firing-torque relationships [cross-correlation between cumulative spike train (CST) and torque, and the delay between motor unit firing and torque production (neuromechanical delay)] of the medial gastrocnemius (MG), lateral gastrocnemius (LG), and soleus (SO) muscles were assessed using HD-sEMG during isometric plantarflexion contractions at 10% and 40% of maximal voluntary contraction (MVC). The morpho-mechanical properties of the AT (i.e. length, thickness, cross-sectional area, and resting stiffness) were determined using B-mode ultrasonography and shear-wave elastography. Multiple linear regression analysis showed that at 10% MVC, the DR of the triceps surae muscles explained 41.7% of the variance in resting AT stiffness. In addition, at 10% MVC, COVisi SO predicted 30.4% of the variance in AT length. At 40% MVC, COVisi MG and COVisi SO explained 48.7% of the variance in AT length. Motor unit-torque relationships were not associated with any morpho-mechanical parameter. This study provides novel evidence of a contraction intensity-dependent relationship between motor unit firing parameters of the triceps surae muscle and the morpho-mechanical properties of the AT. NEW & NOTEWORTHY By employing HD-sEMG, conventional B-mode ultrasonography, and shear-wave elastography, we showed that the resting stiffness of the Achilles tendon is related to mean discharge rate of triceps surae motor units during low-force isometric plantarflexion contractions, providing relevant information about the complex interaction between rate coding and the muscle-tendon unit.

Distinct Neural Drives along the Semitendinosus Muscle.

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 (MUs) in the two compartments at three knee-joint angles (0°: long length, 45°: intermediate length, and 90°: short length). Twenty men (21.4 ± 2.3 years) performed steady isometric contractions with the knee flexors at four target forces: 10%, 20%, 40%, and 60% of maximum voluntary contraction (MVC). High-density electromyography (EMG) signals were recorded to examine the MU discharge characteristics in the two compartments. Measurements included recruitment threshold (RT), mean discharge rate (MDR), coefficient of variation for interspike interval (CoV for ISI), and the standard deviation of filtered cumulative spike train (SD of fCST). Additionally, the within- and between-compartment association of the neural drive was calculated. Analysis of variance indicated that maximal force, absolute EMG amplitude during the MVCs, 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 RT and CoV for ISI were similar between compartments (P > 0.05) at each of the three knee-joint angles. However, MDR 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 (fCST) was relatively low. There were distinct differences in motor unit discharge characteristics between the proximal and 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 inform rehabilitation strategies.

Foot-dominance does not influence force variability during ankle dorsiflexion and foot adduction

ABSTRACT The aim of our study was to compare the force steadiness and the discharge characteristics of motor units in the tibialis anterior (TA) during ankle dorsiflexion and foot adduction produced by submaximal isometric contractions with the dominant and non-dominant foot. Fifteen young men performed maximal and submaximal contractions at five target forces with both legs, and motor unit activity in TA was recorded using high-density electromyography. Maximal force and the fluctuations in force during submaximal contractions were similar between the two legs (p > 0.05). Motor unit activity was characterized by measures of mean discharge rate (MDR), coefficient of variation for interspike interval (CoV for ISI), and standard deviation of the filtered cumulative spike train (SD of fCST). There were no statistically significant differences in motor unit activity between legs during ankle dorsiflexion. In contrast, the MDR and the CoV for ISI but not the SD of fCST, were greater for the non-dominant foot compared with the dominant foot during foot adduction. Nonetheless, these differences in motor unit activity were not sufficient to influence the force fluctuations during the submaximal contractions. These results indicate that control of the force produced by TA during the two actions was not influenced by limb dominance.

Effects of repetition of a car-driving pedal maneuver and neural output in older adults

Understanding the ability of older adults to control pedal position angle and investigating whether this ability can be enhanced through practice may contribute to the prevention of traffic accidents. This study aimed to investigate repetitive effects on variability of the pedal position and neural drive during car-pedal operation in older adults. Thirteen older and 11 young adults performed 105 (21 sets × 5 repetitions) pedal angle control tasks with plantar flexor contraction. High-density surface electromyograms were recorded of triceps surae muscles. A cumulative spike train as a neural drive was calculated using continuously active motor unit activities. The coefficient of variation of the angle was higher in older (1.47 ± 1.06 %) than young (0.41 ± 0.21 %) adults in the first sets, and improved to 0.67 ± 0.51 % in the final sets in older adults only. There was no significant difference in neural drive variability between older and young adults. Our results suggest that repetition improves angular steadiness in older adults. However, this effect could not be explained by neural output which is estimated from lower threshold motor units that are continuously active.

More Variability in Tibialis Anterior Function during the Adduction of the Foot than Dorsiflexion of the Ankle.

The aim of the study was to compare maximal force, force steadiness, and the discharge characteristics of motor units in the tibialis anterior (TA) muscle during submaximal isometric contractions for ankle dorsiflexion and adduction of the foot. Nineteen active young adults performed maximal and submaximal isometric dorsiflexion and adduction contractions at five target forces (5%, 10%, 20%, 40%, and 60% maximal voluntary contraction [MVC]). The activity of motor units in TA was recorded by high-density EMG. The maximal force was similar between dorsiflexion and adduction, despite EMG amplitude for TA being greater ( P < 0.05) during dorsiflexion than adduction. Τhe coefficient of variation (CV) for force (force steadiness) during dorsiflexion was always less ( P < 0.05) than during adduction, except of 5% MVC force. No differences were observed for mean discharge rate; however, the regression between the changes in discharge rate relative to the change of force was significant for dorsiflexion ( R2 = 0.25, P < 0.05) but not for adduction. Discharge variability, however, was usually less during dorsiflexion. The CV for interspike interval was less ( P < 0.05) at 10%, 20%, and 40% MVC but greater at 60% MVC during dorsiflexion than adduction. Similarly, the SD values of the filtered cumulative spike train of the motor units in TA were less ( P < 0.05) at 5%, 10%, 20%, and 40% MVC during dorsiflexion than adduction. Although the mean discharge rate of motor units in TA was similar during foot adduction and ankle dorsiflexion, discharge variability was less during dorsiflexion resulting in less accurate performance of the steady adduction contractions. The neural drive to bifunctional muscles differs during their accessory function, which must be considered for training and rehabilitation interventions.

Decoding Multi-DoF Movements Using a CST-Based Force Generation Model With Single-DoF Training.

Recent developments in dexterous myoelectric prosthetics have established a hardware base for human-machine interfaces. Although pattern recognition techniques have seen successful deployment in gesture classification, their applications remain largely confined to certain specific discrete gestures. Addressing complex daily tasks demands an immediate need for precise simultaneous and proportional control (SPC) for multiple degrees of freedom (DoFs) movements. In this paper, we introduce an SPC approach for multi-DoF wrist movements using the cumulative spike trains (CSTs) of motor unit pools, merely leveraging single-DoF training. The efficacy of our proposed approach was validated offline against existing methods respectively based on non-negative matrix factorization and motor unit spike trains, using experimental data. The experimental process includes both single-DoF (for training) and multi-DoF (for testing) movements. We evaluated the performance using Pearson correlation coefficient (R) and the normalized root mean square error (nRMSE). The results reveal that our method outperforms comparative approaches in force estimation for both testing datasets (3 and 4). On average, for dataset 3, R and nRMSE of the flexion/extension DoF (the pronation/supination DoF) are 0.923±0.037 (0.901±0.040) and 12.3±3.1% (12.9±2.2%); similarly, those of dataset 4 are 0.865±0.057 (0.837±0.053) and 14.9±2.9% (15.4±2.0%), respectively. The outcomes demonstrate the effectiveness of our method in simultaneous and proportional force estimation for multi-DoF wrist movements, showing a promising potential as a neural-machine interface for SPC of dexterous myoelectric prostheses.

Cumulative Spike Train Estimation for Muscle Excitation Assessment From Surface EMG Using Spatial Spike Detection.

Estimating cumulative spike train (CST) of motor units (MUs) from surface electromyography (sEMG) is essential for the effective control of neural interfaces. However, the limited accuracy of existing estimation methods greatly hinders the further development of neural interface. This paper proposes a simple but effective approach for identifying CST based on spatial spike detection from high-density sEMG. Specifically, we use a spatial sliding window to detect spikes according to the spatial propagation characteristics of the motor unit action potential, focusing on the spikes of activated MUs in a local area rather than those of a specific MU. We validated the effectiveness of our proposed method through an experiment involving wrist flexion/extension and pronation/supination, comparing it with a recognized CST estimation method and an MU decomposition based method. The results demonstrated that the proposed method obtained higher accuracy on multi-DoF wrist torque estimation leveraging the estimated CST compared to the other three methods. On average, the correlation coefficient (R) and the normalized root mean square error (nRMSE) between the estimation results and recorded force were 0.96 0.03 and 10.1% 3.7%, respectively. Moreover, there was an extremely high interpretive extent between the CSTs of proposed method and the MU decomposition method. The outcomes reveal the superiority of the proposed method in identifying CSTs and can provide promising driven signals for neural interface.

Footedness but not dominance influences force steadiness during isometric dorsiflexion in young men

The aim of the study was to assess the potential influence of footedness and dominance on maximal force, force fluctuations and neural drive during dorsiflexion. Fifteen left-footed (LF) and fifteen right-footed (RF) young adults performed 2 maximal voluntary contractions (MVC) and 3 steady submaximal isometric contractions at five target forces (5, 10, 20, 40 and 60% MVC) with the dorsiflexors of both legs. High-density electromyography (EMG) was used to record the discharge characteristics of motor units (MUs) of Tibialis Anterior. MVC force and EMG amplitude (root mean square) were similar between the two legs and groups (p > 0.05). Force fluctuations (Coefficient of Variation, CoV for force), mean discharge rate of MUs, discharge variability (CoV of interspike interval), and variability in neural drive (standard deviation of filtered cumulative spike train) were greater (p < 0.05) and the input–output gain of the MUs (ΔDR/ΔF) was lower (p < 0.05) for the LF relative to the RF group. The differences in force fluctuations during steady contractions with the dorsiflexors were associated with footedness but not with dominance. They reflect greater variability in motor neuron output, as suggested by coefficient of variation for interspike interval (independent input) and the standard deviation of the smoothed discharge times (common input).

Sensorimotor integration is affected by acute whole-body vibration: a coherence study.

Introduction: Several whole-body vibration (WBV) effects on performance have been related to potential changes in the neural drive, motor unit firing rate, and sensorimotor integration. In the present paper, motor unit coherence analysis was performed to detect the source of neural modulation based on the frequency domain. Methods: Thirteen men [25 ± 2.1years; Body Mass Index (BMI) = 23.9 ± 1.3kgm2; maximal voluntary force (MVF): 324.36 ± 41.26N] performed sustained contractions of the Tibialis Anterior (TA) at 10%MVF before and after acute WBV. The vibrating stimulus was applied barefoot through a platform to target the TA. High-Density surface Electromyography (HDsEMG) was used to record the myoelectrical activity of TA to evaluate coherence from motor unit cumulative spike-trains (CSTs). Results: Mean coherence showed a significant decrease in the alpha and low-beta bandwidths (alpha: from 0.143 ± 0.129 to 0.132 ± 0.129, p = 0.035; low-beta: from 0.117 ± 0.039 to 0.086 ± 0.03, p = 0.0001), whereas no significant changes were found in the other ones (p > 0.05). The discharge rate (DR) and the Force Covariance (CovF%) were not significantly affected by acute WBV exposure (p > 0.05). Discussion: According to the significant effects found in alpha and low-beta bandwidths, which reflect sensorimotor integration parameters, accompanied by no differences in the DR and CovF%, the present results underlined that possible neural mechanisms at the base of the previously reported performance enhancements following acute WBV are likely based on sensorimotor integration rather than direct neural drive modulation.

Mental Tasks Modulate Motor-Units Above 10 Hz and are a Potential Control Signal for Movement Augmentation: a Preliminary Study.

Spinal motor neurons receive a wide range of input frequencies. However, only frequencies below ca. 10 Hz are directly translated into motor output. Frequency components above 10 Hz are filtered out by neural pathways and muscle dynamics. These higher frequency components may have an indirect effect on motor output, or may simply represent movement-independent oscillations that leak down from supraspinal areas such as the motor cortex. If movement-independent oscillations leak down from supraspinal areas, they could provide a potential control signal in movement augmentation applications. We analysed high-density electromyography (HD-EMG) signals from the tibialis anterior muscle while human subjects performed various mental tasks. The subjects performed an isometric dorsiflexion of the right foot at a low level of force while simultaneously (1) imagining a movement of the right foot, (2) imagining a movement of both hands, (3) performing a mathematical task, or (4) performing no additional task. We classified the channel-averaged HD-EMG signals and the cumulative spike train (CST) of motor-units using a filter bank and a linear classifier. We found that in some subjects, the mental task can be classified from the channel-averaged HD-EMG signals and the CST in oscillations above 10 Hz. Furthermore, we found that these oscillation modulations are incompatible with a systematic and task-dependent change in force level. Our preliminary findings from a limited number of subjects suggest that some mental task-induced oscillations from supraspinal areas leak down to spinal motor neurons and are discriminable via EMG or CST signals at the innervated muscle.

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 15s. The central 10s 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.

Alternating or Bilateral Exercise Training does not Influence Force Control during Single-Leg Submaximal Contractions with the Dorsiflexors.

The aim of the study was to assess the influence of habitual training history on force steadiness and the discharge characteristics of motor units in tibialis anterior during submaximal isometric contractions. Fifteen athletes whose training emphasized alternating actions (11 runners and 4 cyclists) and fifteen athletes who relied on bilateral actions with leg muscles (7 volleyball players, 8 weight-lifters) performed 2 maximal voluntary contractions (MVC) with the dorsiflexors, and 3 steady contractions at 8 target forces (2.5%, 5%, 10%, 20%, 30%, 40%, 50% and 60% MVC). The discharge characteristics of motor units in tibialis anterior were recorded using high-density electromyography grids. The MVC force and the absolute (standard deviation) and normalized (coefficient of variation) amplitudes of the force fluctuations at all target forces were similar between groups. The coefficient of variation for force decreased progressively from 2.5% to 20% MVC force, then it plateaued until 60% MVC force. Mean discharge rate of the motor units in tibialis anterior was similar at all target forces between groups. The variability in discharge times (coefficient of variation for interspike interval) and the variability in neural drive (coefficient of variation of filtered cumulative spike train) was also similar for the two groups. These results indicate that athletes who have trained with either alternating or bilateral actions with leg muscles has similar effects on maximal force, force control, and variability in the independent and common synaptic input during a single-limb isometric task with the dorsiflexors.

Toward a generalizable deep CNN for neural drive estimation across muscles and participants

Objective. High-density electromyography (HD-EMG) decomposition algorithms are used to identify individual motor unit (MU) spike trains, which collectively constitute the neural code of movements, to predict motor intent. This approach has advanced from offline to online decomposition, from isometric to dynamic contractions, leading to a wide range of neural-machine interface applications. However, current online methods need offline retraining when applied to the same muscle on a different day or to a different person, which limits their applications in a real-time neural-machine interface. We proposed a deep convolutional neural network (CNN) framework for neural drive estimation, which takes in frames of HD-EMG signals as input, extracts general spatiotemporal properties of MU action potentials, and outputs the number of spikes in each frame. The deep CNN can generalize its application without retraining to HD-EMG data recorded in separate sessions, muscles, or participants. Approach. We recorded HD-EMG signals from the vastus medialis and vastus lateralis muscles from five participants while they performed isometric contractions during two sessions separated by ∼20 months. We identified MU spike trains from HD-EMG signals using a convolutive blind source separation (BSS) method, and then used the cumulative spike train (CST) of these MUs and the HD-EMG signals to train and validate the deep CNN. Main results. On average, the correlation coefficients between CST from the BSS and that from deep CNN were for leave-one-out across-sessions-and-muscles validation and for leave-one-out across-participants validation. When trained with more than four datasets, the performance of deep CNN saturated at for cross validations across muscles, sessions, and participants. Significance. We can conclude that the deep CNN is generalizable across the aforementioned conditions without retraining. We could potentially generate a robust deep CNN to estimate neural drive to muscles for neural-machine interfaces.

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.

Modulations in motor unit discharge are related to changes in fascicle length during isometric contractions.

The integration of electromyography (EMG) and ultrasound imaging has provided important information about the mechanisms of muscle activation and contraction. Unfortunately, conventional bipolar EMG does not allow an accurate assessment of the interplay between the neural drive received by muscles, changes in fascicle length and torque. We aimed to assess the relationship between modulations in tibialis anterior muscle (TA) motor unit (MU) discharge, fascicle length, and dorsiflexion torque using ultrasound-transparent high-density EMG electrodes. EMG and ultrasound images were recorded simultaneously from TA using a 32-electrode silicon matrix while performing isometric dorsiflexion contractions at two ankle joint positions (0° or 30° plantar flexion) and torques (20% or 40% of maximum). EMG signals were decomposed into MUs and changes in fascicle length were assessed with a fascicle-tracking algorithm. MU firings were converted into a cumulative spike train (CST) that was cross-correlated with torque (CST-torque) and fascicle length (CST-length). High cross-correlations were found for CST-length (0.60, range: 0.31-0.85) and CST-torque (0.71, range: 0.31-0.88). Cross-correlation delays revealed that the delay between CST-fascicle length (∼75 ms) was smaller than CST-torque (∼150 ms, P < 0.001). These delays affected MU recruitment and de-recruitment thresholds since the fascicle length at which MUs were recruited and de-recruited was similar but MU recruitment-de-recruitment torque varied. This study demonstrates that changes in TA fascicle length are related to modulations in MU firing and dorsiflexion torque. These relationships allow assessment of the interplay between neural drive, muscle contraction and torque, enabling the time required to convert neural activity into movement to be quantified.NEW & NOTEWORTHY By employing ultrasound-transparent high-density EMG electrodes, we show that modulations in tibialis anterior muscle motor unit discharge rate were related to both changes in fascicle length and resultant torque. These relationships permitted the quantification of the relative delays between fluctuations in neural drive, muscle contraction, and transfer of torque via the tendon during sustained isometric dorsiflexion contractions, providing information on the conversion of neural activity into muscle force during a contraction.

Leg Dominance Does Not Influence Maximal Force, Force Steadiness, or Motor Unit Discharge Characteristics.

The aim of our study was to compare maximal force, force steadiness, and discharge characteristics of motor units in tibialis anterior during contractions with the dorsiflexors of the dominant and nondominant legs at low-to-moderate target forces and three ankle angles. Twenty young adults performed maximal and submaximal isometric contractions (5%, 10%, 20%, 40%, and 60% of maximal voluntary contraction (MVC)) with the dorsiflexors of the dominant and nondominant legs at three ankle angles (75°, short length; 90°, intermediate length; 105°, long length). High-density EMG signals from the tibialis anterior muscle of each leg were recorded. Maximal force (average dominant, 182.9 ± 64.5 N; nondominant, 179.0 ± 58.8 N) and the fluctuations in force, quantified as absolute (SD) and normalized amplitudes (coefficient of variation (CoV)), were similar between the two legs across the three ankle angles (average CoV for dominant, 1.5% ± 1.0%; nondominant, 1.7% ± 1.3%). The CoV for force for both legs decreased from 5% to 20% MVC force, and then it plateaued at 40% and 60% MVC force. EMG amplitude, mean discharge rate of motor units, discharge variability (interspike interval), and the variability in neural drive (filtered cumulative spike train) were similar between the two legs across the submaximal contractions. MVC force and force steadiness were similar across ankle angles and target forces between the dominant and nondominant legs. The attributes that underlie the self-reported identification of a dominant leg were not associated with the force capacity or the control of force for the dorsiflexor muscles, at least during isometric contractions.

Association between effective neural drive to the triceps surae and fluctuations in plantar-flexion torque during submaximal isometric contractions.

What is the central question of this study? What is the association between the fluctuations in various estimates of effective neural drive to the triceps surae muscles and fluctuations in net plantar-flexion torque during steady submaximal contractions? What is the main finding and its importance? The fluctuations in estimates of effective neural drive to the triceps surae were moderately correlated with fluctuations in net torque at light and moderate plantar-flexion torques. Significant variability was observed in the association between neural drive and torque across participants, trials, short epochs of individual contractions and varying motor unit number. The influence of effective neural drive on low-frequency fluctuations in torque during steady contractions can be estimated from the cumulative spike train (CST) or first principal component (FPC) of smoothed motor unit discharge rates obtained with high-density electromyography. However, the association between these estimates of total neural drive to synergist muscles and the fluctuations in net torque has not been investigated. We exposed the variability and compared the correlations between estimates of effective neural drive to the triceps surae muscles and fluctuations in plantar-flexion torque during steady contractions at 10% and 35% of maximal voluntary contraction (MVC) torque. Both neural drive estimates were moderately correlated with torque (CST, 0.55±0.14; FPC, 0.58±0.16) and highly correlated with one another (0.81±0.1) during the 30-s steady contractions. There was substantial variability in cross-correlation values across participants, trials, and the 1- and 5-s epochs of single contractions. Moreover, epoch duration significantly influenced cross-correlation values. Motor unit number was weakly associated with cross-correlation strength at 35% MVC (marginal R2 0.09-0.11; all P<2.2×10-5 ), but not at 10% MVC (all P>0.37). Approximately, one-fifth of the variance in the coefficient of variation (CV) for torque was explained by CV for the CST estimate of the neural drive (P=6.6×10-13 , R2 =0.21). Estimates of total neural drive to the synergistic triceps surae muscles obtained by pooling motor unit discharge times were moderately correlated with fluctuations in net plantar-flexion torque.

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.

A Deep CNN Framework for Neural Drive Estimation From HD-EMG Across Contraction Intensities and Joint Angles.

Previous studies have demonstrated promising results in estimating the neural drive to muscles, the net output of all motoneurons that innervate the muscle, using high-density electromyography (HD-EMG) for the purpose of interfacing with assistive technologies. Despite the high estimation accuracy, current methods based on neural networks need to be trained with specific motor unit action potential (MUAP) shapes updated for each condition (i.e., varying muscle contraction intensities or joint angles). This preliminary step dramatically limits the potential generalization of these algorithms across tasks. We propose a novel approach to estimate the neural drive using a deep convolutional neural network (CNN), which can identify the cumulative spike train (CST) through general features of MUAPs from a pool of motor units. We recorded HD-EMG signals from the gastrocnemius medialis muscle under three isometric contraction scenarios: 1) trapezoidal contraction tasks with different intensities, 2) contraction tasks with a trapezoidal or sinusoidal torque target, and 3) trapezoidal contraction tasks at different ankle angles. We applied a convolutive blind source separation (BSS) method to decompose HD-EMG signals to CST and segmented both signals into windows to train and validate the deep CNN. Then, we optimized the structure of the deep CNN and validated its generalizability across contraction tasks within each scenario. With the optimal configuration for the HD-EMG data window (overlap of 20 data points and window length of 40 data points), the deep CNN estimated the CST close to that from BSS, with a correlation coefficient higher than 0.96 and normalized root-mean-square-error lower than 7% with respect to the BSS (golden standard) within each scenario. The proposed deep CNN framework can utilize data from different contraction tasks (e.g., different intensities), learn general features of MUAP variants, and estimate the neural drive for other contraction tasks. With the proposed deep CNN, we could potentially build a neural-drive-based human-machine interface that is generalizable to different contraction tasks without retraining.

Influence of central and peripheral motor unit properties on isometric muscle force entropy: A computer simulation study

Approximate entropy of isometric force is a popular measure to characterize behavioral changes across muscle contraction conditions. The degree to which force entropy characterizes the randomness of the motor control strategy, however, is not known. In this study, we used a computational model to investigate the correlation between approximate entropy of the synaptic input to a motor neuron pool, the neural drive to muscle (cumulative spike train; CST), and the force. This comparison was made across several simulation conditions, that included different synaptic command signal bandwidths, motor neuron pool sizes, and muscle contractile properties. The results indicated that although force entropy to some degree reflects the entropy of the synaptic command to motor neurons, it is biased by changes in motor unit properties. As a consequence, there was a low correlation between approximate entropy of force and the motor neuron input signal across all simulation conditions (r2 = 0.13). Therefore, force entropy should only be used to compare motor control strategies across conditions where motor neuron properties can be assumed to be maintained. Instead, we recommend that the entropy of the descending motor commands should be estimated from CSTs comprising spike trains of multiple motor units.