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Our purpose was to compare the influence of motor unit activity in Flexor Digitorum Brevis (FDB) and Soleus (SOL) on force fluctuations during three forward-leaning tasks. Ground reaction forces and high-density EMG signals were collected from 19 males when leaning forward at 25%, 50%, and 75% of maximal forward leaning force. EMG amplitude increased with percent of leaning and was greater for SOL than FDB, but there were no differences in force fluctuations across tasks. Differences in motor unit activity indicated that the relative contribution of the two muscles to the control of balance varied across tasks as confirmed by the association between the fluctuations in neural drive [standard deviation of the filtered cumulative spike train (SD of fCST)] and force [coefficient of variation (CoV) for force]. Specifically, the correlation values were greater for FDB at the lower target forces. Correlation analyses revealed that synaptic noise (CoV for interspike interval) was weakly correlated with the CoV for force, whereas the variability in shared synaptic input (SD of fCST) was strongly correlated with the CoV for force. This finding suggests that the relative influence of the two muscles on the fluctuations in force during forward leaning varied with task requirements. [ABSTRACT FROM AUTHOR]

Recordings of electrical activity from muscles allow us to identify the activity of pools of spinal motor neurons that send the neural drive for muscle activation. Decoding motor unit and motor neuron activity from muscle recordings can be performed by high-density (HD) electrode systems, both non-invasively (surface, HD-sEMG) and invasively (intramuscular, HD-iEMG). HD-sEMG recordings are obtained by grids placed on the skin surface while HD-iEMG signals can be acquired by micro-electrode arrays. While it has been shown that HD-iEMG allows the accurate decoding of a larger number of motor units when compared to HD-sEMG, the dependence of motor unit yield on the parameters of the micro-electrode arrays is still unexplored. Here, we used recently developed HD-iEMG electrodes to record from hundreds of recording sites within the muscle. This allowed us to investigate the impact of electrode number, inter-electrode distance, and the number of muscle insertions on the ability to sample motor units within the muscle. Specifically, we recorded both HD-sEMG and HD-iEMG from the Tibialis Anterior muscle of two healthy subjects at various contraction intensities (10%, 30%, and 70% of maximum voluntary contraction, MVC). For the first time, we present intramuscular recordings with more than 140 electrodes inside a single muscle, achieved through multiple implants of high-density micro-electrode arrays. Through systematic offline analyses of these recordings, we tested different electrode configurations to identify optimal setups for accurately capturing motor unit activity. The results revealed that the density of electrodes in the micro-electrode arrays is the most critical factor for maximising the number of identified motor units and ensuring very high accuracy. Comparisons between intramuscular and surface recordings also confirmed that HD-iEMG consistently captures larger and more stable numbers of motor units across subjects and contraction levels. These results underscore the potential of HD-iEMG as a powerful tool for both clinical and research settings, particularly when precise motor unit decomposition is crucial.

Abstract Background Degeneration of the motoneuron and neuromuscular junction (NMJ) and loss of motor units (MUs) contribute to age‐related muscle wasting and weakness associated with sarcopenia. However, these features have not been comprehensively investigated in humans. This study aimed to compare neuromuscular system integrity and function at different stages of sarcopenia, with a particular focus on NMJ stability and MU properties. Methods We recruited 42 young individuals (Y) (aged 25.98 ± 4.6 years; 57% females) and 88 older individuals (aged 75.9 ± 4.7 years; 55% females). The older group underwent a sarcopenia screening according to the revised guidelines of the European Working Group on Sarcopenia in Older People 2. In all groups, knee extensor muscle force was evaluated by isometric dynamometry, muscle morphology by ultrasound and MU potential properties by intramuscular electromyography (iEMG). MU number estimate (iMUNE) and blood samples were obtained. Muscle biopsies were collected in a subgroup of 16 Y and 52 older participants. Results Thirty‐nine older individuals were non‐sarcopenic (NS), 31 pre‐sarcopenic (PS) and 18 sarcopenic (S). A gradual decrease in quadriceps force, cross‐sectional area and appendicular lean mass was observed across the different stages of sarcopenia (for all P

Background: High‐density surface electromyography (HD‐sEMG) has enabled non‐invasive analysis of motor unit (MU) activity and recruitment, but its application to swallowing‐related muscles is limited. Objective: We aimed to investigate the utility of HD‐sEMG for quantitatively evaluating the MU recruitment characteristics of the suprahyoid muscles during tongue elevation. Methods: We measured the sEMG activity of the suprahyoid muscles of healthy participants during tongue elevation using HD‐sEMG. Maximum voluntary contraction (MVC) was measured, followed by data collection during sustained and ramp‐up tasks to capture suprahyoid muscle activity. Changes in the temporal/spatial MU recruitment patterns within individual suprahyoid muscles were analysed. Results: This study enrolled 16 healthy young adults (mean age: 27.8 ± 5.3 years; eight males and eight females). Increasing muscle force corresponded to a decrease in modified entropy and correlation coefficient and an increase in the coefficient of variation. No significant differences were observed between male and female participants. Conclusion: The results of this study, consistent with those observed in other muscles, such as the vastus lateralis muscle, suggest that HD‐sEMG is a valuable and reliable tool for quantitatively evaluating MU recruitment in the suprahyoid muscles. This measurement technique holds promise for novel assessments of swallowing function. [ABSTRACT FROM AUTHOR]

Purpose: Despite its susceptibility to muscle fatigue, combined neuromuscular electrical stimulation (NMES) and blood flow restriction (BFR) are effective regimens for managing muscle atrophy when traditional resistance exercises are not feasible. This study investigated the potential of low-level laser therapy (LLLT) in reducing muscle fatigue after the application of combined NMES and BFR. Methods: Thirty-six healthy adults were divided into control and LLLT groups. The LLLT group received 60 J of 850-nm wavelength LLLT before a training program of combined NMES and BFR of the nondominant extensor carpi radialis longus (ECRL). The control group followed the same protocol but received sham laser therapy. Assessments included maximal voluntary contraction, ECRL mechanical properties, and isometric force tracking for wrist extension. Results: The LLLT group exhibited a smaller normalized difference in maximal voluntary contraction decrement (-4.01 ± 4.88%) than the control group (-23.85 ± 7.12%) (P < 0.001). The LLLT group demonstrated a smaller decrease in muscle stiffness of the ECRL compared with the control group, characterized by the smaller normalized changes in frequency (P = 0.002), stiffness (P = 0.002), and relaxation measures (P = 0.011) of mechanical oscillation waves. Unlike the control group, the LLLT group exhibited a smaller posttest increase in force fluctuations during force tracking (P = 0.014), linked to the predominant recruitment of low-threshold MU (P < 0.001) without fatigue-related increases in the discharge variability of high-threshold MU (P >0.05). Conclusions: LLLT preexposure reduces fatigue after combined NMES and BFR, preserving force generation, muscle stiffness, and force scaling. The functional benefits are achieved through fatigue-resistant activation strategies of motor unit recruitment and rate coding. [ABSTRACT FROM AUTHOR]

Movements are performed by motoneurons transforming synaptic inputs into an activation signal that controls muscle force. The control signal emerges from interactions between ionotropic and neuromodulatory inputs to motoneurons. Critically, these interactions vary across motoneuron pools and differ between muscles. To provide the most comprehensive framework to date of motor unit activity during isometric contractions, we identified the firing activity of extensive samples of motor units in the tibialis anterior (129 ± 44 per participant; n=8) and the vastus lateralis (130 ± 63 per participant; n=8) muscles during isometric contractions of up to 80% of maximal force. From this unique dataset, the rate coding of each motor unit was characterised as the relation between its instantaneous firing rate and the applied force, with the assumption that the linear increase in isometric force reflects a proportional increase in the net synaptic excitatory inputs received by the motoneuron. This relation was characterised with a natural logarithm function that comprised two stages. The initial stage was marked by a steep acceleration of firing rate, which was greater for low- than medium- and high-threshold motor units. The second stage comprised a linear increase in firing rate, which was greater for high- than medium- and low-threshold motor units. Changes in firing rate were largely non-linear during the ramp-up and ramp-down phases of the task, but with significant prolonged firing activity only evident for medium-threshold motor units. Contrary to what is usually assumed, our results demonstrate that the firing rate of each motor unit can follow a large variety of trends with force across the pool. From a neural control perspective, these findings indicate how motor unit pools use gain control to transform inputs with limited bandwidths into an intended muscle force.

Muscle force is modulated by sequential recruitment and firing rates of motor units (MUs). However, discrepancies exist in the literature regarding the relationship between MU firing rates and their recruitment, presenting two contrasting firing-recruitment schemes. The first firing scheme, known as "onion skin," exhibits low-threshold MUs firing faster than high-threshold MUs, forming separate layers akin to an onion. This contradicts the other firing scheme, known as "reverse onion skin" or "afterhyperpolarization (AHP)," with low-threshold MUs firing slower than high-threshold MUs. To study this apparent dichotomy, we used a high-fidelity computational model that prioritizes physiological fidelity and heterogeneity, allowing versatility in the recruitment of different motoneuron types. Our simulations indicate that these two schemes are not mutually exclusive but rather coexist. The likelihood of observing each scheme depends on factors such as the motoneuron pool activation level, synaptic input activation rates, and MU type. The onion skin scheme does not universally govern the encoding rates of MUs but tends to emerge in unsaturated motoneurons (cells firing < their fusion frequency that generates peak force), whereas the AHP scheme prevails in saturated MUs (cells firing at their fusion frequency), which is highly probable for slow (S)-type MUs. When unsaturated, fast fatigable (FF)-type MUs always show the onion skin scheme, whereas S-type MUs do not show either one. Fast fatigue-resistant (FR)-type MUs are generally similar but show weaker onion skin behaviors than FF-type MUs. Our results offer an explanation for the longstanding dichotomy regarding MU firing patterns, shedding light on the factors influencing the firing-recruitment schemes. NEW & NOTEWORTHY: The literature reports two contrasting schemes, namely the onion skin and the afterhyperpolarization (AHP) regarding the relationship between motor units (MUs) firing rates and recruitment order. Previous studies have examined these schemes phenomenologically, imposing one scheme on the firing-recruitment relationship. Here, we used a high-fidelity computational model that prioritizes biological fidelity and heterogeneity to investigate motoneuron firing schemes without bias toward either scheme. Our objective findings offer an explanation for the longstanding dichotomy on MU firing patterns. [ABSTRACT FROM AUTHOR]

To determine the effects of blood flow restriction (BFR) on the mean firing rate (MFR) and motor unit action potential amplitude (MUAPAMP) VS. recruitment threshold (RT) relationships during fatiguing isometric elbow flexions. Ten men (24.5 ± 4.0 years) performed isometric trapezoidal contractions at 50% maximum voluntary contraction to task failure with or without BFR, on 2 separate days. For BFR, a cuff was inflated to 60% of the pressure required for full brachial artery occlusion at rest. During both visits, surface electromyography was recorded from the biceps brachii of the dominant limb and the signal was decomposed. A paired-samples t test was used to determine the number of repetitions completed between BFR and CON. ANOVAS (repetition [first, last] × condition [BFR, CON]) were used to determine differences in MFR vs. RT and MUAPAMP VS. RT relationships. Subjects completed more repetitions during CON (12 ± 4) than BFR (9 ± 2; p = 0.012). There was no significant interaction (p > 0.05) between the slopes and y-intercepts during the repetition X condition interaction for MUAPAMP VS. MFR. However, there was a main effect of repetition for the slopes of the MUAPAMP VS. RT (p = 0.041) but not the y-intercept (p = 0.964). Post hoc analysis (collapsed across condition) indicated that the slopes of the MUAPAMP VS. RT during the first repetition was less than the last repetition (first: 0.022 ± 0.003 mv/%MVC; last: 0.028 ± 0.004 mv/%MVC; p = 0.041). Blood flow restriction resulted in the same amount of higher threshold MU recruitment in approximately 75% of the repetitions. Furthermore, there was no change in MFR for either condition, even when taken to task failure. Thus, BFR training may create similar MU responses with less total work completed than training without BFR. [ABSTRACT FROM AUTHOR]

Transspinal (or transcutaneous spinal cord) stimulation is a noninvasive, cost-effective, easily applied method with great potential as a therapeutic modality for recovering somatic and nonsomatic functions in upper motor neuron disorders. However, how transspinal stimulation affects motor neuron depolarization is poorly understood, limiting the development of effective transspinal stimulation protocols for rehabilitation. In this study, we characterized the responses of soleus α motor neurons to single-pulse transspinal stimulation using single-motor unit (SMU) discharges as a proxy given the 1:1 discharge activation between the motor neuron and the motor unit. Peristimulus time histogram, peristimulus frequencygram, and surface electromyography (sEMG) were used to characterize the postsynaptic potentials of soleus motor neurons. Transspinal stimulation produced short-latency excitatory postsynaptic potentials (EPSPs) followed by two distinct phases of inhibitory postsynaptic potentials (IPSPs) in most soleus motor neurons and only IPSPs in others. Transspinal stimulation generated double discharges at short interspike intervals in a few motor units. The short-latency EPSPs were likely mediated by muscle spindle group Ia and II afferents, and the IPSPs via excitation of group Ib afferents and recurrent collaterals of motor neurons leading to activation of diverse spinal inhibitory interneuronal circuits. Further studies are warranted to understand better how transspinal stimulation affects depolarization of α motor neurons over multiple spinal segments. This knowledge will be seminal for developing effective transspinal stimulation protocols in upper motor neuron lesions. NEW & NOTEWORTHY: Transspinal stimulation produces distinct actions on soleus motor neurons: an early short-latency excitation followed by two inhibitions or only inhibition and doublets. These results show how transspinal stimulation affects depolarization of soleus α motor neurons in healthy humans. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Biological experiments have confirmed that the locomotion system includes the nervous and musculoskeletal systems, and central pattern generator (CPG). The motor unit (MU) is the core part of the musculoskeletal system. Based on the biological experiments, it is confirmed that the CPG can generate and distribute the motor rhythms and patterns to different MUs through flexible weights, and the MUs feedback can affect the output of CPG. Then, the MU model, the CPG model, and their coupling model are investigated to explain the biological phenomena. Within this work, it was found that there is consistency between the shape of states generated by the three MUs in this work and the experimental results in previous studies. When the MUs correspond to the parts in limbs, and the CPG connects to the MUs via synapses, the locomotion pattern can be adjusted by CPG to use the variable synaptic weights. Besides, the model with fractional order (FO) has better efficiency than the model with integer order. Therefore, the model investigates the relationship between the CPG and the MU and provides a novel technique to introduce the FO coupling model for controlling the locomotion state. [ABSTRACT FROM AUTHOR]

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

Motoneuron properties and their firing patterns undergo significant changes throughout development and in response to neuromodulators such as serotonin. Here, we examined the age‐related development of self‐sustained firing and general excitability of tibialis anterior motoneurons in a young development (7–17 years), young adult (18–28 years) and adult (32–53 years) group, as well as in a separate group of participants taking selective serotonin reuptake inhibitors (SSRIs, aged 11–28 years). Self‐sustained firing, as measured by ΔF, was larger in the young development (∼5.8 Hz, n = 20) compared to the young adult (∼4.9 Hz, n = 13) and adult (∼4.8 Hz, n = 8) groups, consistent with a developmental decrease in self‐sustained firing mediated by persistent inward currents (PIC). ΔF was also larger in participants taking SSRIs (∼6.5 Hz, n = 9) compared to their age‐matched controls (∼5.3 Hz, n = 26), consistent with increased levels of spinal serotonin facilitating the motoneuron PIC. Participants in the young development and SSRI groups also had higher firing rates and a steeper acceleration in initial firing rates (secondary ranges), consistent with the PIC producing a steeper acceleration in membrane depolarization at the onset of motoneuron firing. In summary, both the young development and SSRI groups exhibited increased intrinsic motoneuron excitability compared to the adults, which, in the young development group, was also associated with a larger unsteadiness in the dorsiflexion torque profiles. We propose several intrinsic and extrinsic factors that affect both motoneuron PICs and cell discharge which vary during development, with a time course similar to the changes in motoneuron firing behaviour observed in the present study. Key points: Neurons in the spinal cord that activate muscles in the limbs (motoneurons) undergo increases in excitability shortly after birth to help animals stand and walk.We examined whether the excitability of human ankle flexor motoneurons also continues to change from child to adulthood by recording the activity of the muscle fibres they innervate.Motoneurons in children and adolescents aged 7–17 years (young development group) had higher signatures of excitability that included faster firing rates and more self‐sustained activity compared to adults aged ≥18 years.Participants aged 11–28 years of age taking serotonin reuptake inhibitors had the highest measures of motoneuron excitability compared to their age‐matched controls.The young development group also had more unstable contractions, which might partly be related to the high excitability of the motoneurons. [ABSTRACT FROM AUTHOR]

To utilize surface electromyographics (sEMG) for control purposes, it is necessary to perform real-time estimation of the neural drive to the muscles, which involves real-time decomposition of the EMG signals. In this paper, we propose a Bidirectional Gate Recurrent Unit (Bi-GRU) network with attention to perform online decomposition of high-density sEMG signals. The model can give different levels of attention to different parts of the sEMG signal according to their importance using the attention mechanism. The output of gradient convolutional kernel compensation (gCKC) algorithm was used as the training label, and simulated and experimental sEMG data were divided into windows with 120 sample points for model training, the sampling rate of sEMG signal is 2048 Hz. We test different attention mechanisms and find out the ones that could bring the highest F1-score of the model. The simulated sEMG signal is synthesized from Fuglevand method (J. Neurophysiol., 1993). For the decomposition of 10 Motor Units (MUs), the network trained on simulated data achieved an average F1-score of 0.974 (range from 0.96 to 0.98), and the network trained on experimental data achieved an average F1-score of 0.876 (range from 0.82 to 0.97). The average decomposition time for each window was 28 ms (range from 25.6 ms to 30.5 ms), which falls within the lower bound of the human electromechanical delay. The experimental results show the feasibility of using Bi-GRU-Attention network for the real-time decomposition of Motor Units. Compared to the gCKC algorithm, which is considered the gold standard in the medical field, this model sacrifices a small amount of accuracy but significantly improves computational speed by eliminating the need for calculating the cross-correlation matrix and performing iterative computations. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative condition characterised by a progressive loss of motor neurons controlling voluntary muscle activity. The disease manifests through a variety of motor dysfunctions related to the extent of damage and loss of neurons at different anatomical locations. Despite extensive research, it remains unclear why some motor neurons are especially susceptible to the disease, while others are affected less or even spared. In this article, we review the neurobiological mechanisms, neurochemical profiles, and morpho-functional characteristics of various motor neuron groups and types of motor units implicated in their differential exposure to degeneration. We discuss specific cell-autonomous (intrinsic) and extrinsic factors influencing the vulnerability gradient of motor units and motor neuron types to ALS, with their impact on disease manifestation, course, and prognosis, as revealed in preclinical and clinical studies. We consider the outstanding challenges and emerging opportunities for interpreting the phenotypic and mechanistic variability of the disease to identify targets for clinical interventions. [ABSTRACT FROM AUTHOR]

Ultrasound (US) muscle image series can be used for peripheral human-machine interfacing based on global features, or even on the decomposition of US images into the contributions of individual motor units (MUs). With respect to state-of-the-art surface electromyography (sEMG), US provides higher spatial resolution and deeper penetration depth. However, the accuracy of current methods for direct US decomposition, even at low forces, is relatively poor. These methods are based on linear mathematical models of the contributions of MUs to US images. Here, we test the hypothesis of linearity by comparing the average velocity twitch profiles of MUs when varying the number of other concomitantly active units. We observe that the velocity twitch profile has a decreasing peak-to-peak amplitude when tracking the same target motor unit at progressively increasing contraction force levels, thus with an increasing number of concomitantly active units. This observation indicates non-linear factors in the generation model. Furthermore, we directly studied the impact of one MU on a neighboring MU, finding that the effect of one source on the other is not symmetrical and may be related to unit size. We conclude that a linear approximation is partly limiting the decomposition methods to decompose full velocity twitch trains from velocity images, highlighting the need for more advanced models and methods for US decomposition than those currently employed.

Objective: Motor unit (MU) discharge timings encode human motor intentions to the finest degree. Whilst tapping into such information can bring significant gains to a range of applications, current approaches to MU decoding from surface signals do not scale well with the demands of dexterous human-machine interfacing (HMI). To optimize the forward estimation accuracy and time-efficiency of such systems, we propose the inclusion of task-wise initialization and MU subset selection. Methods: Offline analyses were conducted on data recorded from 11 non-disabled subjects. Task-wise decomposition was applied to identify MUs from high-density surface electromyography (HD-sEMG) pertaining to 18 wrist/forearm motor tasks. The activities of a selected subset of MUs were extracted from test data and used for forward estimation of intended motor tasks and joint kinematics. To that end, various combinations of subset selection and estimation algorithms (both regression and classification-based) were tested for a range of subset sizes. Results: The mutual information-based minimum Redundancy Maximum Relevance (mRMR-MI) criterion retained MUs with the highest predicative power. When the portion of tracked MUs was reduced down to 25%, the regression performance decreased only by 3% (R2=0.79) while classification accuracy dropped by 2.7% (accuracy = 74%) when kernel-based estimators were considered. Conclusion and Significance: Careful selection of tracked MUs can optimize the efficiency of MU-driven interfacing. In particular, prioritization of MUs exhibiting strong nonlinear relationships with target motions is best leveraged by kernel-based estimators. Hence, this frees resources for more robust and adaptive MU decoding techniques to be implemented in future.

Neural oscillatory activity in the beta band (13–30 Hz) is prominent in the brain and it is transmitted partly linearly to the spinal cord and muscles. Multiple views on the functional relevance of beta activity in the motor system have been proposed. Previous simulation work suggested that pools of spinal motoneurons (MNs) receiving a common beta input could demodulate this activity, transforming it into low‐frequency neural drive that could alter force production in muscles. This may suggest that common beta inputs to muscles have a direct role in force modulation. Here we report the experimental average levels and ranges of common beta activity in spinal MNs projecting to single muscles and use a computational model of a MN pool to test if the experimentally observed beta levels in MNs can influence force. When beta was modelled as a continuous activity, the amplitude needed to produce non‐negligible changes in force corresponded to beta representation in the MN pool that was far above the experimental observations. On the other hand, when beta activity was modelled as short‐lived events (i.e. bursts of beta activity separated by intervals without beta oscillations), this activity approximated levels that could cause small changes in force with estimated average common beta inputs to the MNs compatible with the experimental observations. Nonetheless, bursting beta is unlikely to be used for force control due to the temporal sparsity of this activity. It is therefore concluded that beta oscillations are unlikely to contribute to the voluntary modulation of force. Key points: It has been previously proposed that beta (13–30 Hz) common inputs to a motor neuron pool may have a non‐linear effect in voluntary force control.The needed strength of beta oscillations to modulate forces has not been analysed yet.Based on computer simulations, we show that sustained beta inputs to a spinal motoneuron pool at physiologically reported levels have minimal effect on force.Levels of sustained beta rhythmic activity that can cause a significant change in force are not compatible with experimental observations of intramuscular coherence in human skeletal muscles. [ABSTRACT FROM AUTHOR]

Movements are reportedly controlled through the combination of synergies that generate specific motor outputs by imposing an activation pattern on a group of muscles. To date, the smallest unit of analysis of these synergies has been the muscle through the measurement of its activation. However, the muscle is not the lowest neural level of movement control. In this human study (n = 10), we used a purely data‐driven method grounded on graph theory to extract networks of motor neurons based on their correlated activity during an isometric multi‐joint task. Specifically, high‐density surface electromyography recordings from six lower limb muscles were decomposed into motor neurons spiking activity. We analysed these activities by identifying their common low‐frequency components, from which networks of correlated activity to the motor neurons were derived and interpreted as networks of common synaptic inputs. The vast majority of the identified motor neurons shared common inputs with other motor neuron(s). In addition, groups of motor neurons were partly decoupled from their innervated muscle, such that motor neurons innervating the same muscle did not necessarily receive common inputs. Conversely, some motor neurons from different muscles‐including distant muscles‐received common inputs. The study supports the theory that movements are produced through the control of small numbers of groups of motor neurons via common inputs and that there is a partial mismatch between these groups of motor neurons and muscle anatomy. We provide a new neural framework for a deeper understanding of the structure of common inputs to motor neurons. Key points: A central and unresolved question is how spinal motor neurons are controlled to generate movement.We decoded the spiking activities of dozens of spinal motor neurons innervating six muscles during a multi‐joint task, and we used a purely data‐driven method grounded on graph theory to extract networks of motor neurons based on their correlated activity (considered as common input).The vast majority of the identified motor neurons shared common inputs with other motor neuron(s).Groups of motor neurons were partly decoupled from their innervated muscle, such that motor neurons innervating the same muscle did not necessarily receive common inputs. Conversely, some motor neurons from different muscles, including distant muscles, received common inputs.The study supports the theory that movement is produced through the control of groups of motor neurons via common inputs and that there is a partial mismatch between these groups of motor neurons and muscle anatomy. [ABSTRACT FROM AUTHOR]

Objective: Motor unit (MU) discharge timings encode human motor intentions to the finest degree. Whilst tapping into such information can bring significant gains to a range of applications, current approaches to MU decoding from surface signals do not scale well with the demands of dexterous human-machine interfacing (HMI). To optimize the forward estimation accuracy and time-efficiency of such systems, we propose the inclusion of task-wise initialization and MU subset selection. Methods: Offline analyses were conducted on data recorded from 11 non-disabled subjects. Task-wise decomposition was applied to identify MUs from high-density surface electromyography (HD-sEMG) pertaining to 18 wrist/forearm motor tasks. The activities of a selected subset of MUs were extracted from test data and used for forward estimation of intended motor tasks and joint kinematics. To that end, various combinations of subset selection and estimation algorithms (both regression and classification-based) were tested for a range of subset sizes. Results: The mutual information-based minimum Redundancy Maximum Relevance (mRMR-MI) criterion retained MUs with the highest predicative power. When the portion of tracked MUs was reduced down to 25%, the regression performance decreased only by 3% (R2=0.79) while classification accuracy dropped by 2.7% (accuracy = 74%) when kernel-based estimators were considered. Conclusion and Significance: Careful selection of tracked MUs can optimize the efficiency of MU-driven interfacing. In particular, prioritization of MUs exhibiting strong nonlinear relationships with target motions is best leveraged by kernel-based estimators. Hence, this frees resources for more robust and adaptive MU decoding techniques to be implemented in future. [ABSTRACT FROM AUTHOR]

Ultrasound (US) muscle image series can be used for peripheral human-machine interfacing based on global features, or even on the decomposition of US images into the contributions of individual motor units (MUs). With respect to state-of-the-art surface electromyography (sEMG), US provides higher spatial resolution and deeper penetration depth. However, the accuracy of current methods for direct US decomposition, even at low forces, is relatively poor. These methods are based on linear mathematical models of the contributions of MUs to US images. Here, we test the hypothesis of linearity by comparing the average velocity twitch profiles of MUs when varying the number of other concomitantly active units. We observe that the velocity twitch profile has a decreasing peak-to-peak amplitude when tracking the same target motor unit at progressively increasing contraction force levels, thus with an increasing number of concomitantly active units. This observation indicates non-linear factors in the generation model. Furthermore, we directly studied the impact of one MU on a neighboring MU, finding that the effect of one source on the other is not symmetrical and may be related to unit size. We conclude that a linear approximation is partly limiting the decomposition methods to decompose full velocity twitch trains from velocity images, highlighting the need for more advanced models and methods for US decomposition than those currently employed. [ABSTRACT FROM AUTHOR]

Visual feedback that reinforces accurate movements may motivate skill acquisition by promoting self-confidence. This study investigated neuromuscular adaptations to visuomotor training with visual feedback with virtual error reduction. Twentyeight young adults (24.6 ± 1.6 years) were assigned to error reduction (ER) (n = 14) and control (n = 14) groups to train on a bi-rhythmic force task. The ER group received visual feedback and the displayed errors were 50% of the real errors in size. The control group was trained with visual feedback with no reduction in errors. Training-related differences in task accuracy, force behaviors, and motor unit discharge were contrasted between the two groups. The tracking error of the control group progressively declined, whereas the tracking error of the ER group was not evidently reduced in the practice sessions. In the post-test, only the control group exhibited significant task improvements with smaller error size (p = .015) and force enhancement at the target frequencies (p = .001). The motor unit discharge of the control group was training-modulated, as indicated by a reduction of the mean inter-spike interval (p = .018) and smaller low-frequency discharge fluctuations (p = .017) with enhanced firing at the target frequencies of the force task (p = .002). In contrast, the ER group showed no training-related modulation of motor unit behaviors. In conclusion, for young adults, ER feedback does not induce neuromuscular adaptations to the trained visuomotor task, which is conceptually attributable to intrinsic error dead-zones. [ABSTRACT FROM AUTHOR]

Abstract Objective In this study, the aim was to compare the performance of four spatiotemporal decomposition algorithms (stICA, stJADE, stSOBI, and sPCA) and parameters for identifying single motor units in human skeletal muscle under voluntary isometric contractions in ultrafast ultrasound image sequences as an extension of a previous study. The performance was quantified using two measures: (1) the similarity of components’ temporal characteristics against gold standard needle electromyography recordings and (2) the agreement of detected sets of components between the different algorithms. Results We found that out of these four algorithms, no algorithm significantly improved the motor unit identification success compared to stICA using spatial information, which was the best together with stSOBI using either spatial or temporal information. Moreover, there was a strong agreement of detected sets of components between the different algorithms. However, stJADE (using temporal information) provided with complementary successful detections. These results suggest that the choice of decomposition algorithm is not critical, but there may be a methodological improvement potential to detect more motor units.

It has been shown that when humans lean in various directions, the central nervous system (CNS) recruits different motoneuron pools for task completion; common units that are active during different leaning directions, and unique units that are active in only one leaning direction. We used high-density surface electromyography (HD-sEMG) to examine if motor unit (MU) firing behavior was dependent on leaning direction, muscle (medial and lateral gastrocnemius; soleus), limits of stability, or whether a MU is considered common or unique. Fourteen healthy participants stood on a force platform and maintained their center of pressure in five different leaning directions. HD-sEMG recordings were decomposed into MU action potentials and the average firing rate (AFR), coefficient of variation (CoVISI), and firing intermittency were calculated on the MU spike trains. During the 30°-90° leaning directions both unique units and common units had higher firing rates (F = 31.31, P < 0.0001). However, the unique units achieved higher firing rates compared with the common units (mean estimate difference = 3.48 Hz, P < 0.0001). The CoVISI increased across directions for the unique units but not for the common units (F = 23.65, P < 0.0001). Finally, intermittent activation of MUs was dependent on the leaning direction (F = 11.15, P < 0.0001), with less intermittent activity occurring during diagonal and forward-leaning directions. These results provide evidence that the CNS can preferentially control separate motoneuron pools within the ankle plantarflexors during voluntary leaning tasks for the maintenance of standing balance. [ABSTRACT FROM AUTHOR]

Electrophysiological alterations of the neuromuscular junction (NMJ) and motor unit potential (MUP) with unloading are poorly studied. We aimed to investigate these aspects and the underlying molecular mechanisms with short‐term unloading and active recovery (AR). Eleven healthy males underwent a 10‐day unilateral lower limb suspension (ULLS) period, followed by 21‐day AR based on resistance exercise. Quadriceps femoris (QF) cross‐sectional area (CSA) and isometric maximum voluntary contraction (MVC) were evaluated. Intramuscular electromyographic recordings were obtained during 10% and 25% MVC isometric contractions from the vastus lateralis (VL). Biomarkers of NMJ molecular instability (serum c‐terminal agrin fragment, CAF), axonal damage (neurofilament light chain) and denervation status were assessed from blood samples and VL biopsies. NMJ and ion channel transcriptomic profiles were investigated by RNA‐sequencing. QF CSA and MVC decreased with ULLS. Increased CAF and altered NMJ transcriptome with unloading suggested the emergence of NMJ molecular instability, which was not associated with impaired NMJ transmission stability. Instead, increased MUP complexity and decreased motor unit firing rates were found after ULLS. Downregulation of ion channel gene expression was found together with increased neurofilament light chain concentration and partial denervation. The AR period restored most of these neuromuscular alterations. In conclusion, the human NMJ is destabilized at the molecular level but shows functional resilience to a 10‐day unloading period at least at relatively low contraction intensities. However, MUP properties are altered by ULLS, possibly due to alterations in ion channel dynamics and initial axonal damage and denervation. These changes are fully reversed by 21 days of AR. Key points: We used integrative electrophysiological and molecular approaches to comprehensively investigate changes in neuromuscular integrity and function after a 10‐day unilateral lower limb suspension (ULLS), followed by 21 days of active recovery in young healthy men, with a particular focus on neuromuscular junction (NMJ) and motor unit potential (MUP) properties alterations.After 10‐day ULLS, we found significant NMJ molecular alterations in the absence of NMJ transmission stability impairment. These findings suggest that the human NMJ is functionally resilient against insults and stresses induced by short‐term disuse at least at relatively low contraction intensities, at which low‐threshold, slow‐type motor units are recruited.Intramuscular electromyography analysis revealed that unloading caused increased MUP complexity and decreased motor unit firing rates, and these alterations could be related to the observed changes in skeletal muscle ion channel pool and initial and partial signs of fibre denervation and axonal damage.The active recovery period restored these neuromuscular changes. [ABSTRACT FROM AUTHOR]

Motor units convert the last neural code of movement into muscle forces. The classic view of motor unit control is that the CNS sends common synaptic inputs to motoneuron pools and that motoneurons respond in an orderly fashion dictated by the size principle. This view, however, is in contrast with the large number of dimensions observed in motor cortex, which may allow individual and flexible control of motor units. Evidence for flexible control of motor units may be obtained by tracking motor units longitudinally during tasks with some level of behavioral variability. Here we identified and tracked populations of motor units in the brachioradialis muscle of two macaque monkeys during 10 sessions spanning >1 month with a broad range of rate of force development (1.8–38.6 N · m · s-1). We found a very stable recruitment order and discharge characteristics of the motor units over sessions and contraction trials. The small deviations from orderly recruitment were fully predicted by the motor unit recruitment intervals, so that small shifts in recruitment thresholds happened only during contractions at a high rate of force development. Moreover, we also found that one component explained more than ;50% of the motor unit discharge rate variance, and that the remaining components represented a time-shifted version of the first. In conclusion, our results show that the recruitment of motoneurons is determined by the interplay of the size principle and common input and that this recruitment scheme is not violated over time or by the speed of the contractions. [ABSTRACT FROM AUTHOR]

The "split-hand syndrome" is a common clinical sign in amyotrophic lateral sclerosis (ALS), being characterized by more severe atrophy of the hand muscles on the radial side of the hand compared to the ulnar side. We aimed to investigate possible physiological differences between relevant hand muscles using low-intensity F-wave stimulation to assess spinal motoneuron excitability. We recruited 36 healthy volunteers. F-waves were recorded from the abductor pollicis brevis (APB), first dorsal interosseous (FDI) and abductor digiti minimi (ADM), using 20 supramaximal stimuli followed by 20 stimuli at a low-intensity required to obtain M-waves with 10 % amplitude of maximal CMAP. We evaluated the following F-wave parameters: F-M latency, chronodispersion, persistence, amplitude, F/CMAP amplitude ratio and number of F-wave repeaters (with low-intensity). In 10 subjects, low-intensity stimulation F-waves were compared after 20 and 50 stimuli in each muscle. Low-intensity stimulation resulted in lower F-wave amplitude and persistence and higher F/CMAP amplitude ratios. There were no significant differences in F-wave latencies and chronodispersion. When comparing the three muscles, we found higher F-wave persistence and F/CMAP amplitude ratios when recording over the ADM and APB compared to the FDI. We also found a higher number of F-wave repeaters in the ADM with low-intensity stimulation. Results from 20 to 50 low-intensity stimuli were similar. A small number of low-intensity stimuli is appropriate to study F-wave latencies and chronodispersion. We found differences in some physiological properties of the ADM spinal motoneuron pool compared to other hand muscles. [ABSTRACT FROM AUTHOR]

Objective: In this study, the aim was to compare the performance of four spatiotemporal decomposition algorithms (stICA, stJADE, stSOBI, and sPCA) and parameters for identifying single motor units in human skeletal muscle under voluntary isometric contractions in ultrafast ultrasound image sequences as an extension of a previous study. The performance was quantified using two measures: (1) the similarity of components' temporal characteristics against gold standard needle electromyography recordings and (2) the agreement of detected sets of components between the different algorithms. Results: We found that out of these four algorithms, no algorithm significantly improved the motor unit identification success compared to stICA using spatial information, which was the best together with stSOBI using either spatial or temporal information. Moreover, there was a strong agreement of detected sets of components between the different algorithms. However, stJADE (using temporal information) provided with complementary successful detections. These results suggest that the choice of decomposition algorithm is not critical, but there may be a methodological improvement potential to detect more motor units. [ABSTRACT FROM AUTHOR]

β Oscillations (13-30 Hz) are ubiquitous in the human motor nervous system. Yet, their origins and roles are unknown. Traditionally, β activity has been treated as a stationary signal. However, recent studies observed that cortical β occurs in "bursting events," which are transmitted to muscles. This short-lived nature of β events makes it possible to study the main mechanism of b activity found in the muscles in relation to cortical β. Here, we assessed whether muscle β activity mainly results from cortical projections. We ran two experiments in healthy humans of both sexes (N=15 and N= 13, respectively) to characterize β activity at the cortical and motor unit (MU) levels during isometric contractions of the tibialis anterior muscle. We found that β rhythms observed at the cortical and MU levels are indeed in bursts. These bursts appeared to be time-locked and had comparable average durations (40-80 ms) and rates (approximately three to four bursts per second). To further confirm that cortical and MU β have the same source, we used a novel operant conditioning framework to allow subjects to volitionally modulate MU β. We showed that volitional modulation of β activity at the MU level was possible with minimal subject learning and was paralleled by similar changes in cortical β activity. These results support the hypothesis that MU β mainly results from cortical projections. Moreover, they demonstrate the possibility to decode cortical β activity from MU recordings, with a potential translation to future neural interfaces that use peripheral information to identify and modulate activity in the central nervous system. [ABSTRACT FROM AUTHOR]

Concepts about motor unit recruitment are important learning contents in exercise physiology and biomechanics classes that are usually taught theoretically. In the last few years, great advances have occurred in the decomposition of surface electromyography, allowing the learning of theoretical contents in an experimental way. In this tutorial paper, we have described the decomposition of surface electromyography methodological aspects and examples to teach motor unit recruitment concepts in exercise physiology and biomechanics practical lessons. This work has the aim to facilitate physiology and biomechanics academics to introduce this technique in practical classes. [ABSTRACT FROM AUTHOR]

Drafting in swimming is a tactic in which an athlete (drafter) swims in the wave of another athlete (leader). Our aim was to compare the effects of this tactic on the drafter, as far as muscle fatigue, muscle activity, and swimming efficiency are concerned. Fifteen drafters performed three 200 m front crawl trials at a controlled submaximal pace in three configurations: Behind Drafting (BD), Lateral Drafting (LD), and Free Swimming (FS). Muscle fatigue, muscle activity, and swimming efficiency were obtained by surface electromyography (EMG) and video analysis from flexor carpi radialis, triceps brachii, latissimus dorsi, and rectus femoris muscles. The outcome measures were: time slope of Mean Frequency (MNF), for muscle fatigue; time slope of Root Mean Square (RMS), for muscle activity; and Stroke Index (SI) for swimming efficiency. Negative variations of MNF were 5.1 ± 1.7%, 6.6 ± 4.1%, and 11.1 ± 2.7% in BD, LD, and FS, respectively. Statistical significance was found for all cases except for the rectus femoris. Positive variations of RMS were 3.4 ± 1.2%, 4.7 ± 2.7%, and 7.8 ± 4.6% in BD, LD, and FS, respectively. Statistical significance was found only for the slopes of latissimus dorsi in FS and LD. The largest mean in SI was measured in the BD (2.01 m2/s), while the smallest was measured in the FS (1.86 m2/s). BD was found to be the best swimming configuration, in terms of lower muscle fatigue and higher swimming efficiency. Also, LD resulted to be advantageous with respect to FS. [ABSTRACT FROM AUTHOR]

Drafting in swimming is a tactic in which an athlete (drafter) swims in the wave of another athlete (leader). Our aim was to compare the effects of this tactic on the drafter, as far as muscle fatigue, muscle activity, and swimming efficiency are concerned. Fifteen drafters performed three 200 m front crawl trials at a controlled submaximal pace in three configurations: Behind Drafting (BD), Lateral Drafting (LD), and Free Swimming (FS). Muscle fatigue, muscle activity, and swimming efficiency were obtained by surface electromyography (EMG) and video analysis from flexor carpi radialis, triceps brachii, latissimus dorsi, and rectus femoris muscles. The outcome measures were: time slope of Mean Frequency (MNF), for muscle fatigue; time slope of Root Mean Square (RMS), for muscle activity; and Stroke Index (SI) for swimming efficiency. Negative variations of MNF were 5.1 ± 1.7%, 6.6 ± 4.1%, and 11.1 ± 2.7% in BD, LD, and FS, respectively. Statistical significance was found for all cases except for the rectus femoris. Positive variations of RMS were 3.4 ± 1.2%, 4.7 ± 2.7%, and 7.8 ± 4.6% in BD, LD, and FS, respectively. Statistical significance was found only for the slopes of latissimus dorsi in FS and LD. The largest mean in SI was measured in the BD (2.01 m2/s), while the smallest was measured in the FS (1.86 m2/s). BD was found to be the best swimming configuration, in terms of lower muscle fatigue and higher swimming efficiency. Also, LD resulted to be advantageous with respect to FS.

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.

This study aimed to determine whether neural drive is redistributed between muscles during a fatiguing isometric contraction, and if so, whether the initial level of common synaptic input between these muscles constrains this redistribution. We studied two muscle groups: triceps surae (14 participants) and quadriceps (15 participants). Participants performed a series of submaximal isometric contractions and a torque-matched contraction maintained until task failure. We used high-density surface electromyography to identify the behavior of 1,874 motor units from the soleus, gastrocnemius medialis (GM), gastrocnemius lateralis (GL), rectus femoris, vastus lateralis (VL), and vastus medialis (VM). We assessed the level of common drive between muscles in the absence of fatigue using a coherence analysis. We also assessed the redistribution of neural drive between muscles during the fatiguing contraction through the correlation between their cumulative spike trains (index of neural drive). The level of common drive between VL and VM was significantly higher than that observed for the other muscle pairs, including GL-GM. The level of common drive increased during the fatiguing contraction, but the differences between muscle pairs persisted. We also observed a strong positive correlation of neural drive between VL and VM during the fatiguing contraction (r = 0.82). This was not observed for the other muscle pairs, including GL-GM, which exhibited differential changes in neural drive. These results suggest that less common synaptic input between muscles allows for more flexible coordination strategies during a fatiguing task, i.e., differential changes in neural drive across muscles. The role of this flexibility on performance remains to be elucidated. NEW & NOTEWORTHY Redundancy of the neuromuscular system theoretically allows for a redistribution of the neural drive across muscles (i.e., between-muscle compensation) during a fatiguing contraction. Our results suggest that a high level of common input between muscles (e.g., vastus lateralis and medialis) represents a neural constraint making it less likely to redistribute the neural drive across these muscles. In this way, redistribution was only observed across muscles that share little common synaptic input (e.g., gastrocnemius lateralis and medialis). [ABSTRACT FROM AUTHOR]

The central pattern generator (CPG) is a key neural-circuit component of the locomotion control system. Recently, numerous molecular and genetic approaches have been proposed for investigating the CPG mechanisms. The rhythm in the CPG locomotor circuits comes from the activity in the ipsilateral excitatory neurons whose output is controlled by inter-neuron inhibitory connections. Conventional models for simulating the CPG mechanism are complex Hodgkin-Huxley-type models. Inspired by biological investigations and the continuous-time Matsuoka model, we propose new integral-order and fractional-order CPG models, which consider time delays and synaptic interfaces. The phase diagrams exhibit limit cycles and periodic solutions, in agreement with the CPG biological characteristics. As well, the fractional-order model shows state transitions with order variations. In addition, we investigate the relationship between the CPG and the motor units through the construction of integral-order and fractional-order coupling models. Simulations of these coupling models show that the states generated by the three motor units are in accordance with the experimentally-obtained states in previous studies. The proposed models reveal that the CPG can regulate limb locomotion patterns through connection weights and synaptic interfaces. Moreover, in comparison to the integral-order models, the fractional-order ones appear to be more effective, and hence more suitable for describing the dynamics of the CPG biological system. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Although maximal force increases following short-term isometric strength training, the rate of force development (RFD) may remain relatively unaffected. The underlying neural and muscular mechanisms during rapid contractions after strength training are largely unknown. Since strength training increases the neural drive to muscles, it may be hypothesized that there are distinct neural or muscular adaptations determining the change in RFD independently of an increase in maximal force. Therefore, we examined motor unit population data acquired from surface electromyography during the rapid generation of force before and after 4 wk of strength training. We observed that strength training did not change the RFD because it did not influence the number of motor units recruited per second or their initial discharge rate during rapid contractions. Although strength training did not change motoneuron behavior in the force increase phase of rapid contractions, it increased the discharge rate of motoneurons (by ~4 spikes/s) when reaching the plateau phase (~150 ms) of the rapid contractions, determining an increase in maximal force production. Computer simulations with a motor unit model that included neural and muscular properties, closely matched the experimental observations and demonstrated that the lack of change in RFD following training is primarily mediated by an unchanged maximal recruitment speed of motoneurons. These results demonstrate that maximal force and contraction speed are determined by different adaptations in motoneuron behavior following strength training and indicate that increases in the recruitment speed of motoneurons are required to evoke training-induced increases in RFD. [ABSTRACT FROM AUTHOR]

Abstract Background Current myoelectric control algorithms for active prostheses map time- and frequency-domain features of the interference EMG signal into prosthesis commands. With this approach, only a fraction of the available information content of the EMG is used and the resulting control fails to satisfy the majority of users. In this study, we predict joint angles of the three degrees of freedom of the wrist from motor unit discharge timings identified by decomposition of high-density surface EMG. Methods We recorded wrist kinematics and high-density surface EMG signals from six able-bodied individuals and one patient with limb deficiency while they performed movements of three degrees of freedom of the wrist at three different speeds. We compared the performance of linear regression to predict the observed individual wrist joint angles from, either traditional time domain features of the interference EMG or from motor unit discharge timings (which we termed neural features) obtained by EMG decomposition. In addition, we propose and test a simple model-based dimensionality reduction, based on the physiological notion that the discharge timings of motor units are partly correlated. Results The regression approach using neural features outperformed regression on classic global EMG features (average R 2 for neural features 0.77 and 0.64, for able-bodied subjects and patients, respectively; for time-domain features 0.70 and 0.52). Conclusions These results indicate that the use of neural information extracted from EMG decomposition can advance man-machine interfacing for prosthesis control.

A hallmark of intelligent behavior is that we can separate intention from action. To understand the mechanism that gates the flow of information between motor planning and execution, we compared the activity of frontal eye field neurons with motor unit activity from neck muscles in the presence of an intervening delay period in which spatial information regarding the target was available to plan a response. Although spatially specific delay period activity was present in the activity of frontal eye field neurons, it was absent in motor unit activity. Nonetheless, motor unit activity was correlated with the time it took to initiate saccades. Interestingly, we observed a heterogeneity of responses among motor units, such that only units with smaller amplitudes showed a clear modulation during the delay period. These small amplitude motor units also had higher spontaneous activity compared with the units which showed modulation only during the movement epoch. Taken together, our results suggest the activity of smaller motor units convey temporal information and explains how the delay period primes muscle activity leading to faster reaction times. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate whether regional modulation of the ankle plantarflexors during standing was related to the recruitment of motor units associated with force direction. Fourteen participants performed a multi-directional leaning task in standing. Participants stood on a force platform and maintained their center of pressure in five different target directions. Motor unit firings were extracted by decomposition of high-density surface electromyograms recorded from the ankle plantarflexor muscles. The motor unit barycentre, defined as the weighted mean of the maximal average rectified values across columns and rows, was used to evaluate the medio-lateral and proximo-distal changes in the surface representation of single motor units across different leaning target directions. Using a motor unit tracking analysis, groups of motor units were identified as being common or unique across the target directions. The leaning directions had an effect on the spatial representations of motor units in the medial gastrocnemius and soleus (p < 0.05), but not in the lateral gastrocnemius (p > 0.05). Motor unit action potentials were represented in the medial and proximal aspects of the muscles during forward vs. lateral leans. Further analysis determined that the common motor units were found in similar spatial locations across the target directions, whereas newly recruited unique motor units were found in different spatial locations according to target direction (p < 0.05). The central nervous system may possess the ability to activate different groups of motor units according to task demands to meet the force-direction requirements of the leaning task. [ABSTRACT FROM AUTHOR]

Human corticospinal transmission is commonly studied using brain stimulation. However, this approach is biased to activity in the fastest conducting axons. It is unclear whether conclusions obtained in this context are representative of volitional activity in mild-to-moderate contractions. An alternative to overcome this limitation may be to study the corticospinal transmission of endogenously generated brain activity. Here, we investigate in humans (N=19; of either sex), the transmission speeds of cortical β rhythms (~20 Hz) traveling to arm (first dorsal interosseous) and leg (tibialis anterior; TA) muscles during tonic mild contractions. For this purpose, we propose two improvements for the estimation of corticomuscular β transmission delays. First, we show that the cumulant density (cross-covariance) is more accurate than the commonly-used directed coherence to estimate transmission delays in bidirectional systems transmitting band-limited signals. Second, we show that when spiking motor unit activity is used instead of interference electromyography, corticomuscular transmission delay estimates are unaffected by the shapes of the motor unit action potentials (MUAPs). Applying these improvements, we show that descending corticomuscular β transmission is only 1-2 ms slower than expected from the fastest corticospinal pathways. In the last part of our work, we show results from simulations using estimated distributions of the conduction velocities for descending axons projecting to lower motoneurons (from macaque histologic measurements) to suggest two scenarios that can explain fast corticomuscular transmission: either only the fastest corticospinal axons selectively transmit β activity, or else the entire pool does. The implications of these two scenarios for our understanding of corticomuscular interactions are discussed. [ABSTRACT FROM AUTHOR]

Objective . Developing neural decoders robust to non-stationary conditions is essential to ensure their long-term accuracy and stability. This is particularly important when decoding the neural drive to muscles during dynamic contractions, which pose significant challenges for stationary decoders. Approach . We propose a novel adaptive electromyography (EMG) decomposition algorithm that builds on blind source separation methods by leveraging the Kullback-Leibler divergence and kurtosis of the signals as metrics for online learning. The proposed approach provides a theoretical framework to tune the adaptation hyperparameters and compensate for non-stationarities in the mixing matrix, such as due to dynamic contractions, and to identify the underlying motor neuron (MN) discharges. The adaptation is performed in real-time (∼22 ms of computational time per 100 ms batches). Main results . The hyperparameters of the proposed adaptation captured anatomical differences between recording locations (forearm vs wrist) and generalised across subjects. Once optimised, the proposed adaptation algorithm significantly improved all decomposition performance metrics with respect to the absence of adaptation in a wide range of motion of the wrist (80 ∘ ). The rate of agreement, sensitivity, and precision were⩾90%in⩾80%of the cases in both simulated and experimentally recorded data, according to a two-source validation approach. Significance . The findings demonstrate the suitability of the proposed online learning metrics and hyperparameter optimisation to compensate the induced modulation and accurately decode MN discharges in dynamic conditions. Moreover, the study proposes an experimental validation method for EMG decomposition in dynamic tasks., (Creative Commons Attribution license.)

Selective survival of small motor nerve fibers and their neuromuscular contacts in the SOD1G93A transgenic mouse model of amyotrophic lateral sclerosis (ALS) suggests that smaller regenerated nerve fibers are more able to sustain reformed nerve-muscle connections as functionally intact motor units (MUs). The sciatic nerve was crushed unilaterally in SOD1G93A transgenic mice at 40 days of age and contractile forces of reinnervated muscles and their MUs were recorded at 90 days in order to determine the capacities of the nerves to regenerate and to form and retain functional neuromuscular connections. Reduced MU numbers in fast-twitch tibialis anterior, extensor digitorum longus and medial gastrocnemius muscles and the lesser reductions in slow-twitch soleus muscle of SOD1G93A transgenic mice were reversed in reinnervated muscles: there were more reinnervated MUs and their contractile forces and the muscle forces and weights increased. In line with the contrasting ability of only small not large nerve fibers to sprout to form enlarged MUs in the SOD1G93A transgenic mouse, the smaller regenerating nerve fibers formed enlarged MUs that were better able to survive. Because nerve fibers with and without muscle contacts were severed by the sciatic nerve crush injury, the conditioning lesion is untenable as the explanation for improved maintenance of reinnervated neuromuscular junctions. Elevated neurotrophic factor expression in axotomized motoneurons and/or denervated Schwann cells and the synapse withdrawal from axotomized motoneurons are other factors that, in addition to reduced size of nerve fibers reinnervating muscles, may account for increased survival and size of reinnervated MUs in ALS.