Individual differences in the neural strategies to control the lateral and medial head of the quadriceps during a mechanically constrained task

Common synaptic inputs and persistent inward currents of vastus lateralis motor units are reduced in older male adults

Although muscle atrophy may partially account for age-related strength decline, it is further influenced by alterations of neural input to muscle. Persistent inward currents (PIC) and the level of common synaptic inputs to motoneurons influence neuromuscular function. However, these have not yet been described in the aged human quadriceps. High-density surface electromyography (HDsEMG) signals were collected from the vastus lateralis of 15 young (mean ± SD, 23 ± 5 y) and 15 older (67 ± 9 y) men during submaximal sustained and 20-s ramped contractions. HDsEMG signals were decomposed to identify individual motor unit discharges, from which PIC amplitude and intramuscular coherence were estimated. Older participants produced significantly lower knee extensor torque (p < 0.001) and poorer force tracking ability (p < 0.001) than young. Older participants also had lower PIC amplitude (p = 0.001) and coherence estimates in the alpha frequency band (p < 0.001) during ramp contractions when compared to young. Persistent inward currents and common synaptic inputs are lower in the vastus lateralis of older males when compared to young. These data highlight altered neural input to the clinically and functionally important quadriceps, further underpinning age-related loss of function which may occur independently of the loss of muscle mass.

Menstrual Cycle Associated Alteration of Vastus Lateralis Motor Unit Function

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Extracting Individual Muscle Drive and Activity From High-Density Surface Electromyography Signals Based on the Center of Gravity of Motor Unit

Neural interfacing has played an essential role in advancing our understanding of fundamental movement neurophysiology and the development of human-machine interface. However, direct neural interfaces from brain and nerve recording are currently limited in clinical areas for their invasiveness and high selectivity. Here, we applied the surface electromyogram (EMG) in studying the neural control of movement and proposed a new non-invasive way of extracting neural drive to individual muscles. Sixteen subjects performed isometric contractions to complete six hand tasks. High-density surface EMG signals (256 channels in total) recorded from the forearm muscles were decomposed into motor unit firing trains. The location of each decomposed motor unit was represented by its center of gravity and was put into clustering for distinct muscle regions. All the motor units in the same cluster served as a muscle-specific motor pool from which individual muscle drive could be extracted directly. Moreover, we cross-validated the self-clustered muscle regions by magnetic resonance imaging (MRI) recorded from the subjects' forearms. All motor units that fall within the MRI region are considered correctly clustered. We achieved a clustering accuracy of 95.72% ± 4.01% for all subjects. We provided a new framework for collecting experimental muscle-specific drives and generalized the way of surface electrode placement without prior knowledge of the targeting muscle architecture.

Adaptability of the load sharing between the longissimus and components of the multifidus muscle during isometric trunk extension in healthy individuals

PURPOSE

Redundancy of the musculoskeletal system implies multiple strategies are theoretically available to coordinate back extensor muscles. This study investigated whether coordination between back muscles during a tightly constrained isometric trunk extension task varies within and between individuals, and whether this changes following brief exposure to activation feedback of a muscle.

METHODS

Nine healthy participants performed three blocks of two repetitions of ramped isometric trunk extension in side-lying against resistance from 0-30% of maximum voluntary contraction over 30 s (force feedback). Between blocks, participants repeated contractions with visual feedback of electromyography (EMG) from either superficial (SM) or deep multifidus (DM), in two conditions; 'After SM' and 'After DM'. Intramuscular EMG was recorded from SM, DM, and longissimus (LG) simultaneously with shear wave elastography (SWE) from SM or DM.

RESULTS

In the 'Natural' condition (force feedback only), group data showed incremental increases in EMG with force, with minor changes in distribution of activation between muscles as force increased. SM was the most active muscle during the 'Natural' condition, but with DM most active in some participants. Individual data showed that coordination between muscles differed substantially between repetitions and individuals. Brief exposure to EMG feedback altered coordination. SWE showed individual variation, but findings differed from EMG.

CONCLUSION

This study revealed substantial variation in coordination between back extensor muscles within and between participants, and after exposure to feedback, in a tightly constrained task. Shear modulus revealed similar variation, but with an inconsistent relationship to EMG. These data highlight highly flexible control of back muscles.

Correlation networks of spinal motor neurons that innervate lower limb muscles during a multi-joint isometric task

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.

Regional Hypertrophy: The Effect of Exercises at Long and Short Muscle Lengths in Recreationally Trained Women

The aim of the present study was to analyse the role of exercises' resistance profile in regional hypertrophy. Thirty-eight healthy women completed a 9-week resistance training program consisting of either 4 sets of 12 repetitions to volitional failure of inclined bicep curls (INC group) or preacher curls (PREA group), three times per week. Pre- and post-intervention muscle thickness was measured using B-mode ultrasound imaging with a linear-array transducer. Scan acquisition sites were determined by measuring 50%, 60% and 70% of the distance between the posterior crest of the acromion and the olecranon. Statistical significance was set at p < 0.05. No region of the INC group grew when comparing pre- to post-intervention. The 70% region of the PREA group grew significantly (muscle thickness increased from 2.7 ± 0.43 cm to 2.94 ± 0.44 cm). We found no growth differences between regions when analysing per group (p = 0.274), region (p = 0.571) or group*region (p = 0.367). Our results show that the distal region of the arm grows in response to the preacher curl that places the highest amount of strain in the range of motion in which the arm muscles are more elongated.

An exploration of the motor unit behaviour during the concentric and eccentric phases of a squat task performed at different speeds

Despite squatting being important in strength training and rehabilitation, few studies have investigated motor unit (MU) behaviour. This study explored the MU behaviour of vastus medialis (VM) and vastus lateralis (VL) during the concentric and eccentric phases of a squat exercise performed at two speeds. Twenty-two participants had surface dEMG sensors attached over VM and VL, and IMUs recorded thigh and shank angular velocities. Participants performed squats at 15 and 25 repetitions per minute in a randomised order, and EMG signals were decomposed into their MU action potential trains. A four factor (muscle × speed × contraction phase × sexes) mixed methods ANOVA revealed significant main effects for MU firing rates between speeds, between muscles and between sexes, but not contraction phases. Post hoc analysis showed significantly greater MU firing rates and amplitudes in VM. A significant interaction was seen between speed and the contraction phases. Further analysis revealed significantly greater firing rates during the concentric compared to the eccentric phases, and between speeds during the eccentric phase only. VM and VL respond differently during squatting depending on speed and contraction phase. These new insights in VM and VL MU behvaviour may be useful when designing training and rehabilitation protocols.

Activity distribution among the hamstring muscles during high-speed running: A descriptive multichannel surface EMG study

PURPOSE

This study assessed activity distribution among the hamstring muscles during high-speed running. The objective was to compare within and between muscle activity, relative contribution and hip and knee joint angles at peak muscle activity during high-speed running.

METHODS

Through multichannel electromyography, we measured muscle activity in male basketball players during high-speed running on a treadmill at 15 locations: five for biceps femoris long head, four for semitendinosus, and six for semimembranosus. Muscle activity was calculated for each location within each hamstring muscle individually for each percent of a stride cycle.

RESULTS

Twenty-nine non-injured basketball players were included (mean age: 17 ± 1 years; mass, 85 ± 9 kg; height, 193 ± 9 cm). Heterogeneous activity was found for all individual hamstring muscles across multiple events of the stride cycle. In the late-swing phase, muscle activity and relative contribution of the semimembranosus was significantly higher than of the semitendinosus. There was no significant difference in hip and knee joint angles at instant of peak muscle activity, assessed locally within individual hamstring muscles, as well as in general over the whole hamstring muscle.

CONCLUSION

Hamstring muscles were most active in the late-swing phase during high-speed running. In this phase, the semimembranosus was most active and the semitendinosus was least active. Within the biceps femoris long head, the most proximal region was significantly more active in the late-swing phase, compared to other muscle regions. For each muscle and location, peak muscle activity occurred at similar hip and knee joint angles.

Modulation of spinal circuits following phase-dependent electrical stimulation of afferent pathways

Objective.Peripheral electrical stimulation (PES) of afferent pathways is a tool commonly used to induce neural adaptations in some neural disorders such as pathological tremor or stroke. However, the neuromodulatory effects of stimulation interventions synchronized with physiological activity (closed-loop strategies) have been scarcely researched in the upper-limb. Here, the short-term spinal effects of a 20-minute stimulation protocol where afferent pathways were stimulated with a closed-loop strategy named selective and adaptive timely stimulation (SATS) were explored in 11 healthy subjects.Approach. SATS was applied to the radial nerve in-phase (INP) or out-of-phase (OOP) with respect to the muscle activity of the extensor carpi radialis (ECR). The neural adaptations at the spinal cord level were assessed for the flexor carpi radialis (FCR) by measuring disynaptic Group I inhibition, Ia presynaptic inhibition, Ib facilitation from the H-reflex and estimation of the neural drive before, immediately after, and 30 minutes after the intervention.Main results.SATS strategy delivered electrical stimulation synchronized with the real-time muscle activity measured, with an average delay of 17 ± 8 ms. SATS-INP induced increased disynaptic Group I inhibition (77 ± 23% of baseline conditioned FCR H-reflex), while SATS-OOP elicited the opposite effect (125 ± 46% of baseline conditioned FCR H-reflex). Some of the subjects maintained the changes after 30 minutes. No other significant changes were found for the rest of measurements.Significance.These results suggest that the short-term modulatory effects of phase-dependent PES occur at specific targeted spinal pathways for the wrist muscles in healthy individuals. Importantly, timely recruitment of afferent pathways synchronized with specific muscle activity is a fundamental principle that shall be considered when tailoring PES protocols to modulate specific neural circuits. (NCT number 04501133).

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 were0.983±0.006for leave-one-out across-sessions-and-muscles validation and0.989±0.002for leave-one-out across-participants validation. When trained with more than four datasets, the performance of deep CNN saturated at0.984±0.001for 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.

Differences between vastus medialis and lateralis excitation onsets are dependent on the relative distance of surface electrodes placement from the innervation zone location

Conflictual results between the onset of vastus medialis (VM) and vastus lateralis (VL) excitation may arise from methodological aspects related to the detection of surface electromyograms. In this study we used an array of surface electrodes to assess the effect of detection site, relative to the muscle innervation zone, on the difference between VM and VL excitation onsets. Ten healthy males performed moderate isometric knee extension at 40 % of their maximal voluntary isometric contraction. After the actual VM-VL onset was defined (estimated when action potentials were generated at the neuromuscular junctions of both muscles), we calculated the largest bias that the detection site may introduce in the VM-VL onset estimation. We also assessed whether the location often considered for positioning bipolar electrodes on each muscle leads to VM-VL onset estimations comparable to the actual VM-VL onset. Our main results revealed that a maximum absolute bias of 20.48 ms may be introduced in VM-VL onset estimations due to the electrodes' detection site. In addition, mean differences of ∼ 12 ms in VM-VL onset estimations were attributable to largest possible discrepancies in the paired position of channels with respect to the innervation zone for VL and VM. When considering the classical location for positioning the bipolar electrodes over these muscles, differences error was subtle (∼3.4 ms) when compared with the actual VM-VL onset. Nonetheless, when accounting for the effect of relative differences in electrode position between muscles is not possible, our results suggest that a systematic absolute error of ∼ 12 ms should be considered in future studies regarding VM-VL onset estimations, suggesting that onset differences lower than that might not be clinically relevant.

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

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

The role of the neural stimulus in regulating skeletal muscle hypertrophy

Resistance training is frequently performed with the goal of stimulating muscle hypertrophy. Due to the key roles motor unit recruitment and mechanical tension play to induce muscle growth, when programming, the manipulation of the training variables is oriented to provoke the correct stimulus. Although it is known that the nervous system is responsible for the control of motor units and active muscle force, muscle hypertrophy researchers and trainers tend to only focus on the adaptations of the musculotendinous unit and not in the nervous system behaviour. To better guide resistance exercise prescription for muscle hypertrophy and aiming to delve into the mechanisms that maximize this goal, this review provides evidence-based considerations for possible effects of neural behaviour on muscle growth when programming resistance training, and future neurophysiological measurement that should be tested when training to increase muscle mass. Combined information from the neural and muscular structures will allow to understand the exact adaptations of the muscle in response to a given input (neural drive to the muscle). Changes at different levels of the nervous system will affect the control of motor units and mechanical forces during resistance training, thus impacting the potential hypertrophic adaptations. Additionally, this article addresses how neural adaptations and fatigue accumulation that occur when resistance training may influence the hypertrophic response and propose neurophysiological assessments that may improve our understanding of resistance training variables that impact on muscular adaptations.

Determining concentric and eccentric force-velocity profiles during squatting

Purpose

The force–velocity relationship of muscular contraction has been extensively studied. However, previous research has focussed either on isolated muscle or single-joint movements, whereas human movement consists of multi-joint movements (e.g. squatting). Therefore, the purpose of this study was to investigate the force–velocity relationship of isovelocity squatting.

Methods

Fifteen male participants (24 ± 2 years, 79.8 ± 9.1 kg, 177.5 ± 6 cm) performed isovelocity squats on a novel motorised isovelocity device (Kineo Training System) at three concentric (0.25, 0.5, and 0.75 m s⁻¹) and three eccentric velocities (− 0.25, − 0.5, and − 0.75 m s⁻¹). Peak vertical ground reaction forces, that occurred during the isovelocity phase, were collected using dual force plates (2000 Hz) (Kistler, Switzerland).

Results

The group mean squat force–velocity profile conformed to the typical in vivo profile, with peak vertical ground reaction forces during eccentric squatting being 9.5 ± 19% greater than isometric (P = 0.037), and occurring between − 0.5 and − 0.75 m s⁻¹. However, large inter-participant variability was identified (0.84–1.62 × isometric force), with some participants being unable to produce eccentric forces greater than isometric. Sub-group analyses could not identify differences between individuals who could/could not produce eccentric forces above isometric, although those who could not tended to be taller.

Conclusions

These finding suggest that variability exists between participants in the ability to generate maximum eccentric forces during squatting, and the magnitude of eccentric increase above isometric cannot be predicted solely based on a concentric assessment. Therefore, an assessment of eccentric capabilities may be required prior to prescribing eccentric-specific resistance training.

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

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 1874 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 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.

Neural control of matched motor units during muscle shortening and lengthening at increasing velocities

Modulation of movement velocity is necessary during daily life tasks, work, and sports activities. However, assessing motor unit behavior during muscle shortening and lengthening at different velocities is challenging. High-density surface electromyography (HD-sEMG) is an established method to identify and track motor unit behavior in isometric contractions. Therefore, we used this methodology to unravel the behavior of the same motor units in dynamic contractions at low contraction velocities. Velocity-related changes in tibialis anterior motor unit behavior during concentric and eccentric contractions at 10% and 25% maximum voluntary isometric contraction were assessed by decomposing HD-sEMG signals recorded from the tibialis anterior muscle of eleven healthy participants at 5°/s, 10°/s, and 20°/s. Motor units extracted from the dynamic contractions were tracked across different velocities at the same load levels. On average, 14 motor units/participant were matched across different velocities, showing specific changes in discharge rate modulation. Specifically, increased velocity led to an increased rate of change in discharge rate (e.g., discharge rate slope, P = 0.025), recruitment and derecruitment discharge rates (P = 0.003 and P = 0.001), and decreased recruitment angles (P = 0.0001). Surprisingly, the application of the motor unit extraction filters calculated from 20°/s onto the recordings at 5°/s and 10°/s revealed that >92% of motor units recruited at the highest velocity were active on both lower velocities, indicating no additional recruitment of motor units. Our results suggest that motor unit rate coding rather than recruitment is responsible for controlling muscle shortening and lengthening contractions at increasing velocities against a constant load.NEW & NOTEWORTHY The control of movement velocity is accomplished by the modulation of the neural drive to muscle and its variation over time. In this study, we tracked motor units decomposed from HD-sEMG across shortening and lengthening contractions at increasing velocities in two submaximal load levels. We demonstrate that concentric and eccentric contractions of the tibialis anterior muscle at slow velocities are achieved by specific motor unit rate coding strategies rather than distinct recruitment schemes.

Perceptual-motor styles

Even for a stereotyped task, sensorimotor behavior is generally variable due to noise, redundancy, adaptability, learning or plasticity. The sources and significance of different kinds of behavioral variability have attracted considerable attention in recent years. However, the idea that part of this variability depends on unique individual strategies has been explored to a lesser extent. In particular, the notion of style recurs infrequently in the literature on sensorimotor behavior. In general use, style refers to a distinctive manner or custom of behaving oneself or of doing something, especially one that is typical of a person, group of people, place, context, or period. The application of the term to the domain of perceptual and motor phenomenology opens new perspectives on the nature of behavioral variability, perspectives that are complementary to those typically considered in the studies of sensorimotor variability. In particular, the concept of style may help toward the development of personalised physiology and medicine by providing markers of individual behaviour and response to different stimuli or treatments. Here, we cover some potential applications of the concept of perceptual-motor style to different areas of neuroscience, both in the healthy and the diseased. We prefer to be as general as possible in the types of applications we consider, even at the expense of running the risk of encompassing loosely related studies, given the relative novelty of the introduction of the term perceptual-motor style in neurosciences.

Analysis of motor unit spike trains estimated from high-density surface electromyography is highly reliable across operators

There is a growing interest in decomposing high-density surface electromyography (HDsEMG) into motor unit spike trains to improve knowledge on the neural control of muscle contraction. However, the reliability of decomposition approaches is sometimes questioned, especially because they require manual editing of the outputs. We aimed to assess the inter-operator reliability of the identification of motor unit spike trains. Eight operators with varying experience in HDsEMG decomposition were provided with the same data extracted using the convolutive kernel compensation method. They were asked to manually edit them following established procedures. Data included signals from three lower leg muscles and different submaximal intensities. After manual analysis, 126 ± 5 motor units were retained (range across operators: 119-134). A total of 3380 rate of agreement values were calculated (28 pairwise comparisons × 11 contractions/muscles × 4-28 motor units). The median rate of agreement value was 99.6%. Inter-operator reliability was excellent for both mean discharge rate and time at recruitment (intraclass correlation coefficient > 0.99). These results show that when provided with the same decomposed data and the same basic instructions, operators converge toward almost identical results. Our data have been made available so that they can be used for training new operators.