Publications
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Schrader B, Schrader J, Vaske B, et al., 2021, Football beats hypertension: results of the 3F (Fit&Fun with Football) study, JOURNAL OF HYPERTENSION, Vol: 39, Pages: 2290-2296, ISSN: 0263-6352
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- Citations: 2
Del Vecchio A, Castellini C, Beckerle P, 2021, Peripheral Neuroergonomics - An Elegant Way to Improve Human-Robot Interaction?, FRONTIERS IN NEUROROBOTICS, Vol: 15, ISSN: 1662-5218
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- Citations: 3
Germer CM, Farina D, Elias LA, et al., 2021, Surface EMG crosstalk quantified at the motor unit population level for muscles of the hand, thigh, and calf, Journal of Applied Physiology, Vol: 131, Pages: 808-820, ISSN: 1522-1601
Crosstalk is an important source of error in interpreting surface electromyography (EMG) signals. Here, we aimed at characterizing crosstalk for three groups of synergistic muscles by the identification of individual motor unit action potentials. Moreover, we explored whether spatial filtering (single and double differential) of the EMG signals influences the level of crosstalk. Three experiments were conducted. Participants (total twenty-five) performed isometric contractions at 10% of the maximal voluntary contraction (MVC) with digit muscles and knee extensors, and at 30% MVC with plantar flexors. High-density surface EMG signals were recorded and decomposed into motor unit spike trains. For each muscle, we quantified the crosstalk induced to neighboring muscles and the level of contamination by the nearby muscle activity. We also estimated the influence of crosstalk on the EMG power spectrum and intermuscular correlation. Most motor units (80%) generated significant crosstalk signals to neighboring muscle EMG in monopolar recording mode, but this proportion decreased with spatial filtering (50% and 42% for single and double differential, respectively). Crosstalk induced overestimations of intermuscular correlation and has a small effect on the EMG power spectrum, which indicates that crosstalk is not reduced with high-pass temporal filtering. Conversely, spatial filtering diminished the crosstalk magnitude and the overestimations of intermuscular correlation, confirming to be an effective and simple technique to reduce crosstalk. This paper presents a new method for the identification and quantification of crosstalk at the motor unit level and clarifies the influence of crosstalk on EMG interpretation for muscles with different anatomy.
Hug F, Avrillon S, Del Vecchio A, et al., 2021, Analysis of motor unit spike trains estimated from high-density surface electromyography is highly reliable across operators, Journal of Electromyography and Kinesiology, Vol: 58, Pages: 102548-102548, ISSN: 1050-6411
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.
Del Vecchio A, Casolo A, Dideriksen J, et al., 2021, Why humans are stronger but not faster after isometric strength training: specific neural, not muscular, motor unit adaptations
<jats:title>Abstract</jats:title><jats:p>While 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 during the rapid generation of force before and after four weeks 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. While strength training did not change motoneuron behaviour 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 behaviour following strength training and indicate that increases in the recruitment speed of motoneurons are required to evoke training-induced increases in RFD.</jats:p>
Skarabot J, Brownstein CG, Casolo A, et al., 2021, The knowns and unknowns of neural adaptations to resistance training, EUROPEAN JOURNAL OF APPLIED PHYSIOLOGY, Vol: 121, Pages: 675-685, ISSN: 1439-6319
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- Citations: 43
Ting JE, Vecchio AD, Sarma D, et al., 2021, Sensing and decoding the neural drive to paralyzed muscles during attempted movements of a person with tetraplegia using a sleeve array
<jats:title>Abstract</jats:title><jats:p>Motor neurons in the brain and spinal cord convey information about motor intent that can be extracted and interpreted to control assistive devices, such as computers, wheelchairs, and robotic manipulators. However, most methods for measuring the firing activity of single neurons rely on implanted microelectrodes. Although intracortical brain-computer interfaces (BCIs) have been shown to be safe and effective, the requirement for surgery poses a barrier to widespread use. Here, we demonstrate that a wearable sensor array can detect residual motor unit activity in paralyzed muscles after severe cervical spinal cord injury (SCI). Despite generating no observable hand movement, volitional recruitment of motor neurons below the level of injury was observed across attempted movements of individual fingers and overt wrist and elbow movements. Subgroups of motor units were coactive during flexion or extension phases of the task. Single digit movement intentions were classified offline from the EMG power (RMS) or motor unit firing rates with median classification accuracies >75% in both cases. Simulated online control of a virtual hand was performed with a binary classifier to test feasibility of real time extraction and decoding of motor units. The online decomposition algorithm extracted motor units in 1.2 ms, and the firing rates predicted the correct digit motion 88 ± 24% of the time. This study provides the first demonstration of a wearable interface for recording and decoding firing rates of motor neurons below the level of injury in a person with tetraplegia after motor complete SCI.</jats:p><jats:sec><jats:title>Significance Statement</jats:title><jats:p>A wearable electrode array and machine learning methods were used to record and decode myoelectric signals and motor unit firing in paralyzed muscles of a person with motor complete tetraplegia. Motor unit action p
Hug F, Avrillon S, Del Vecchio A, et al., 2021, Analysis of motor unit spike trains estimated from high-density surface electromyography is highly reliable across operators
<jats:title>Abstract</jats:title><jats:p>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.</jats:p>
Hug F, Del Vecchio A, Avrillon S, et al., 2021, Muscles from the same muscle group do not necessarily share common drive: evidence from the human triceps surae., Journal of applied physiology (Bethesda, Md. : 1985), Vol: 130, Pages: 342-354, ISSN: 1522-1601
It has been proposed that movements are produced through groups of muscles, or motor modules, activated by common neural commands. However, the neural origin of motor modules is still debated. Here, we used complementary approaches to determine: 1) whether three muscles of the same muscle group [soleus, gastrocnemius medialis (GM), and gastrocnemius lateralis (GL)] are activated by a common neural drive, and 2) whether the neural drive to GM and GL could be differentially modified by altering the mechanical requirements of the task. Eighteen human participants performed an isometric standing heel raise and submaximal isometric plantarflexions (10%, 30%, and 50% of maximal effort). High-density surface electromyography recordings were decomposed into motor unit action potentials and coherence analysis was applied on the motor unit spike trains. We identified strong common drive to each muscle but minimal common drive between the muscles. Further, large between-muscle differences were observed during the isometric plantarflexions, such as a delayed recruitment time of GL compared with GM and soleus motor units and opposite time-dependent changes in the estimates of neural drive to muscles during the torque plateau. Finally, the feet position adopted during the heel-raise task (neutral vs. internally rotated) affected only the GL neural drive with no change for GM. These results provide conclusive evidence that not all anatomically defined synergist muscles are controlled by strong common neural drive. Independent drive to some muscles from the same muscle group may allow for more flexible control to comply with secondary goals such as joint stabilization.NEW & NOTEWORTHY In this study, we demonstrated that the three muscles composing the human triceps surae share minimal common drive during isometric contractions. Our results suggest that reducing the number of effectively controlled degrees of freedom may not always be the strategy used by the central nervous sys
Clarke AK, Atashzar SF, Vecchio AD, et al., 2021, Deep learning for robust decomposition of high-density surface EMG signals, IEEE Transactions on Biomedical Engineering, Vol: 68, Pages: 526-534, ISSN: 0018-9294
Blind source separation (BSS) algorithms, such as gradient convolution kernel compensation (gCKC), can efficiently and accurately decompose high-density surface electromyography (HD-sEMG) signals into constituent motor unit (MU) action potential trains. Once the separation matrix is blindly estimated on a signal interval, it is also possible to apply the same matrix to subsequent signal segments. Nonetheless, the trained separation matrices are sub-optimal in noisy conditions and require that incoming data undergo computationally expensive whitening. One unexplored alternative is to instead use the paired HD-sEMG signal and BSS output to train a model to predict MU activations within a supervised learning framework. A gated recurrent unit (GRU) network was trained to decompose both simulated and experimental unwhitened HD-sEMG signal using the output of the gCKC algorithm. The results on the experimental data were validated by comparison with the decomposition of concurrently recorded intramuscular EMG signals. The GRU network outperformed gCKC at low signal-to-noise ratios, proving superior performance in generalising to new data. Using 12 seconds of experimental data per recording, the GRU performed similarly to gCKC, at rates of agreement of 92.5% (84.5%-97.5%) and 94.9% (88.8%-100.0%) respectively for GRU and gCKC against matched intramuscular sources.
Avrillon S, Del Vecchio A, Farina D, et al., 2021, Individual differences in the neural strategies to control the lateral and medial head of the quadriceps during a mechanically constrained task., Journal of applied physiology (Bethesda, Md. : 1985), Vol: 130, Pages: 269-281, ISSN: 1522-1601
The interindividual variability in the neural drive sent from the spinal cord to muscles is largely unknown, even during highly constrained motor tasks. Here, we investigated individual differences in the strength of neural drive received by the vastus lateralis (VL) and vastus medialis (VM) during an isometric task. We also assessed the proportion of common neural drive within and between these muscles. Twenty-two participants performed a series of submaximal isometric knee extensions at 25% of their peak torque. High-density surface electromyography recordings were decomposed into motor unit action potentials. Coherence analyses were applied on the motor unit spike trains to assess the degree of neural drive that was shared between motor neurons. Six participants were retested ∼20 mo after the first session. The distribution of the strength of neural drive between VL and VM varied between participants and was correlated with the distribution of normalized interference electromyography (EMG) signals (r > 0.56). The level of within- and between-muscle coherence varied across individuals, with a significant positive correlation between these two outcomes (VL: r = 0.48; VM: r = 0.58). We also observed a large interindividual variability in the proportion of muscle-specific drive, that is, the drive unique to each muscle (VL range: 6%-83%, VM range: 6%-86%). All the outcome measures were robust across sessions, providing evidence that the individual differences did not depend solely on the variability of the measures. Together, these results demonstrate that the neural strategies to control the VL and VM muscles widely vary across individuals, even during a constrained task.NEW & NOTEWORTHY We observed that the distribution of the strength of neural drive between the vastus lateralis and vastus medialis during a single-joint isometric task varied across participants. Also, we observed that the proportion of ne
Felici F, Del Vecchio A, 2020, Surface Electromyography: What Limits Its Use in Exercise and Sport Physiology?, FRONTIERS IN NEUROLOGY, Vol: 11, ISSN: 1664-2295
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- Citations: 20
Del Vecchio A, Sylos-Labini F, Mondi V, et al., 2020, Spinal motoneurons of the human newborn are highly synchronized during leg movements, SCIENCE ADVANCES, Vol: 6, ISSN: 2375-2548
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- Citations: 27
Nuccio S, Del Vecchio A, Casolo A, et al., 2020, Muscle fiber conduction velocity in the vastus lateralis and medialis muscles of soccer players after ACL reconstruction, Scandinavian Journal of Medicine and Science in Sports, Vol: 30, Pages: 1976-1984, ISSN: 0905-7188
The neural factors underlying the persistency of quadriceps weakness after anterior cruciate ligament reconstruction (ACLR) have been only partially explained. This study examined muscle fiber conduction velocity (MFCV) as an indirect parameter of motor unit recruitment strategies in the vastus lateralis (VL) and medialis (VM) muscles of soccer players with ACLR. High‐density surface electromyography (HDsEMG) was acquired from VL and VM in nine soccer players (22.7 ± 2.9 years; BMI: 22.08 ± 1.72 kg·m−2; 7.7 ± 2.2 months post‐surgery). Voluntary muscle force and the relative myoelectrical activity from the reconstructed and contralateral sides were recorded during linearly increasing isometric knee extension contractions up to 70% of maximal voluntary isometric force (MVIF). The relation of MFCV and force was examined by linear regression analysis at the individual subject level. The initial (intercept), peak (MFCV70), and rate of change (slope) of MFCV related to force were compared between limbs and muscles. The MVIF was lower in the reconstructed side than in the contralateral side (−%20.5; P < .05). MFCV intercept was similar among limbs and muscles (P > .05). MFCV70 and MFCV slope were lower in the reconstructed side compared to the contralateral for both VL (−28.5% and −10.1%, respectively; P < .001) and VM (−22.6% and −8.1%, respectively; P < .001). The slope of MFCV was lower in the VL than VM, but only in the reconstructed side (−12.4%; P < .001). These results suggest possible impairments in recruitment strategies of high‐threshold motor units (HTMUs) as well as deficits in sarcolemmal excitability, fiber diameter, and discharge rate of knee extensor muscles following ACLR.
Tanzarella S, Muceli S, Del Vecchio A, et al., 2020, Non-invasive analysis of motor neurons controlling the intrinsic and extrinsic muscles of the hand, Journal of Neural Engineering, Vol: 17, ISSN: 1741-2552
OBJECTIVE: We present a non-invasive framework for investigating efferent commands to 14 extrinsic and intrinsic hand muscles. We extend previous studies (limited to a few muscles) on common synaptic input among pools of motor neurons in a large number of muscles. APPROACH: Seven subjects performed sinusoidal isometric contractions to complete seven types of grasps, with each finger and with three combinations of fingers in opposition with the thumb. High-density surface EMG (HD-sEMG) signals (384 channels in total) recorded from the 14 muscles were decomposed into the constituent motor unit action potentials. This provided a non-invasive framework for the investigation of motor neuron discharge patterns, muscle coordination and efferent commands of the hand muscles during grasping. Moreover, during grasping tasks, it was possible to identify common neural information among pools of motor neurons innervating the investigated muscles. For this purpose, principal component analysis (PCA) was applied to the smoothed discharge rates of the decoded motor units. MAIN RESULTS: We found that the first principal component (PC1) of the ensemble of decoded motor neuron spike trains explained a variance of (53.8 ± 10.5) % and was positively correlated with force (R=0.67 ± 0.01 across all subjects and tasks). By grouping the pools of motor neurons from extrinsic or intrinsic muscles, the PC1 explained a proportion of variance of (57.3 ± 10.8) % and (57.9 ± 11.8) %, respectively, and was correlated with force with R=0.61 ± 0.13 and 0.64 ± 0.12, respectively. SIGNIFICANCE: These observations demonstrate a low dimensional control of motor neurons across multiple muscles that can be exploited for extracting control signals in neural interfacing. The proposed framework was designed for hand rehabilitation perspectives, such as post-stroke rehabilitation and hand-exoskeleton control.
Casolo A, Nuccio S, Bazzucchi I, et al., 2020, Reproducibility of muscle fibre conduction velocity during linearly increasing force contractions, JOURNAL OF ELECTROMYOGRAPHY AND KINESIOLOGY, Vol: 53, ISSN: 1050-6411
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- Citations: 5
Casolo A, Farina D, Falla D, et al., 2020, Strength training Increases conduction velocity of high-threshold motor units., Medicine and Science in Sports and Exercise, Vol: 52, Pages: 955-967, ISSN: 0195-9131
PURPOSE: Motor unit conduction velocity (MUCV) represents the propagation velocity of action potentials along the muscle fibres innervated by individual motor neurons and indirectly reflects the electrophysiological properties of the sarcolemma. In this study, we investigated the effect of a 4-week strength training intervention on the peripheral properties (MUCV and motor unit action potential amplitude, RMSMU) of populations of longitudinally tracked motor units (MUs). METHODS: The adjustments exhibited by 12 individuals who participated in the training (INT) were compared with 12 controls (CON). Strength training involved ballistic (4x10) and sustained (3x10) isometric ankle dorsi flexions. Measurement sessions involved the recordings of maximal voluntary isometric force (MViF) and submaximal isometric ramp contractions, while high-density surface EMG (HDsEMG) was recorded from the tibialis anterior. HDsEMG signals were decomposed into individual MU discharge timings and MUs were tracked across the intervention. RESULTS: MViF (+14.1%, P=0.003) and average MUCV (+3.00%, P=0.028) increased in the INT group, while normalized MUs recruitment threshold (RT) decreased (-14.9%, P=0.001). The slope (rate of change) of the regression between MUCV and MUs RT increased only in the INT group (+32.6%, P=0.028), indicating a progressive greater increase in MUCV for higher-threshold MUs. The intercept (initial value) of MUCV did not change following the intervention (P=0.568). The association between RMSMU and MUs RT was not altered by the training. CONCLUSION: The increase in the rate of change in MUCV as a function of MU recruitment threshold, but not the initial value of MUCV, suggests that short-term strength training elicits specific adaptations in the electrophysiological properties of the muscle fibre membrane in high-threshold motor units.
Del Vecchio A, Negro F, Holobar A, et al., 2020, Direct translation of findings in isolated animal preparations to <i>in vivo</i> human motoneuron behaviour is challenging, JOURNAL OF PHYSIOLOGY-LONDON, Vol: 598, Pages: 1111-1112, ISSN: 0022-3751
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- Citations: 1
Germer CM, Del Vecchio A, Negro F, et al., 2020, Neurophysiological correlates of force control improvement induced by sinusoidal vibrotactile stimulation, Journal of Neural Engineering, Vol: 17, Pages: 1-14, ISSN: 1741-2552
Objective. An optimal level of vibrotactile stimulation has been shown to improve sensorimotor control in healthy and diseased individuals. However, the underlying neurophysiological mechanisms behind the enhanced motor performance caused by vibrotactile stimulation are yet to be fully understood. Therefore, here we aim to evaluate the effect of a cutaneous vibration on the firing behavior of motor units in a condition of improved force steadiness. Approach. Participants performed a visuomotor task, which consisted of low-intensity isometric contractions of the first dorsal interosseous (FDI) muscle, while sinusoidal (175 Hz) vibrotactile stimuli with different intensities were applied to the index finger. High-density surface electromyogram was recorded from the FDI muscle, and a decomposition algorithm was used to extract the motor unit spike trains. Additionally, computer simulations were performed using a multiscale neuromuscular model to provide a potential explanation for the experimental findings. Main results. Experimental outcomes showed that an optimal level of vibration significantly improved force steadiness (estimated as the coefficient of variation of force). The decreased force variability was accompanied by a reduction in the variability of the smoothed cumulative spike train (as an estimation of the neural drive to the muscle), and the proportion of common inputs to the FDI motor nucleus. However, the interspike interval variability did not change significantly with the vibration. A mathematical approach, together with computer simulation results suggested that vibrotactile stimulation would reduce the variance of the common synaptic input to the motor neuron pool, thereby decreasing the low frequency fluctuations of the neural drive to the muscle and force steadiness. Significance. Our results demonstrate that the decreased variability in common input accounts for the enhancement in force control induced by vibrotactile stimulation.
Dideriksen JL, Del Vecchio A, Farina D, 2020, Neural and muscular determinants of maximal rate of force development, Journal of Neurophysiology, Vol: 123, Pages: 149-157, ISSN: 0022-3077
The ability to produce rapid forces requires quick motor unit recruitment, high motor unit discharge rates, and fast motor unit force twitches. The relative importance of these parameters for maximum rate of force development (RFD), however, is poorly understood. In this study, we systematically investigated these relationships using a computational model of motor unit pool activity and force. Across simulations, neural and muscular properties were systematically varied in experimentally observed ranges. Motor units were recruited over an interval starting from contraction onset (range: 22–233 ms). Upon recruitment, discharge rates declined from an initial rate (range: 89–212 pulses per second), with varying likelihood of doublet (interspike interval of 3 ms; range: 0–50%). Finally, muscular adaptations were modeled by changing average twitch contraction time (range: 42–78 ms). Spectral analysis showed that the effective neural drive to the simulated muscle had smaller bandwidths than the average motor unit twitch, indicating that the bandwidth of the motor output, and thus the capacity for explosive force, was limited mainly by neural properties. The simulated RFD increased by 1,050 ± 281% maximal voluntary contraction force per second from the longest to the shortest recruitment interval. This effect was more than fourfold higher than the effect of increasing the initial discharge rate, more than fivefold higher than the effect of increasing the chance of doublets, and more than sixfold higher than the effect of decreasing twitch contraction times. The simulated results suggest that the physiological variation of the rate by which motor units are recruited during ballistic contractions is the main determinant for the variability in RFD across individuals.
Del Vecchio A, Germer CM, Elias LA, et al., 2019, The human central nervous system transmits common synaptic inputs to distinct motor neuron pools during non-synergistic digit actions, The Journal of Physiology, Vol: 597, Pages: 5935-5948, ISSN: 0022-3751
KEY POINTS: Neural connectivity between distinct motor neuronal modules in the spinal cord is classically studied through electrical stimulation or multi-muscle EMG recordings. We quantified the strength of correlation in the activity of two distinct populations of motor neurons innervating the thenar and first dorsal interosseous muscles during tasks that required the two hand muscles to exert matched or un-matched forces in different directions. We show that when the two hand muscles are concurrently activated, synaptic input to the two motor neuron pools is shared across all frequency bandwidths (representing cortical and spinal input) associated with force control. The observed connectivity indicates that motor neuron pools receive common input even when digit actions do not belong to a common behavioural repertoire. ABSTRACT: Neural connectivity between distinct motor neuronal modules in the spinal cord is classically studied through electrical stimulation or multi-muscle EMG recordings. Here we quantify the strength of correlation in the activity of two distinct populations of motor neurons innervating the thenar and first dorsal interosseous muscles in humans during voluntary contractions. To remove confounds associated with previous studies, we used a task that required the two hand muscles to exert matched or un-matched forces in different directions. Despite the force production task consisting of uncommon digit force coordination patterns, we found that synaptic input to motor neurons is shared across all frequency bands, reflecting cortical and spinal inputs associated with force control. The coherence between discharge timings of the two pools of motor neurons was significant at the delta (0-5 Hz), alpha (5-15 Hz) and beta (15-35 Hz) bands (P < 0.05). These results suggest that correlated input to motor neurons of two hand muscles can occur even during tasks not belonging to a common behavioural repertoire and despite lack of
Del Vecchio A, Farina D, 2019, Interfacing the neural output of the spinal cord: robust and reliable longitudinal identification of motor neurons in humans, Journal of Neural Engineering, Vol: 17, Pages: 1-11, ISSN: 1741-2552
Objective. Non-invasive electromyographic techniques can detect action potentials from muscle units with high spatial dimensionality. These technologies allow the decoding of large samples of motor units by using high-density grids of electrodes that are placed on the skin overlying contracting muscles and therefore provide a non-invasive representation of the human spinal cord output. Approach. From a sample of >1200 decoded motor neurons, we show that motor neuron activity can be identified in humans in the full muscle recruitment range with high accuracy. Main results. After showing the validity of decomposition with novel test parameters, we demonstrate that the same motor neurons can be tracked over a period of one-month, which allows for the longitudinal analysis of individual human neural cells. Significance. These results show the potential of an accurate and reliable assessment of large populations of motor neurons in physiological investigations. We discuss the potential of this non-invasive neural interfacing technology for the study of the neural determinants of movement and man-machine interfacing.
Felici F, Bazzucchi I, Casolo A, et al., 2019, The relative strength of common synaptic input to motor neurons is not a determinant of the maximal rate of force development in humans, Publisher: WILEY, Pages: 25-26, ISSN: 1748-1708
Del Vecchio A, Falla D, Felici F, et al., 2019, The relative strength of common synaptic input to motor neurons is not a determinant of the maximal rate of force development in humans, JOURNAL OF APPLIED PHYSIOLOGY, Vol: 127, Pages: 205-214, ISSN: 8750-7587
Del Vecchio A, Negro F, Holobar A, et al., 2019, You are as fast as your motor neurons: speed of recruitment and maximal discharge of motor neurons determine the maximal rate of force development in humans, The Journal of Physiology, Vol: 597, Pages: 2445-2456, ISSN: 1469-7793
KEY POINTS: We propose and validate a method for accurately identifying the activity of populations of motor neurons during contractions at maximal rate of force development in humans. The behaviour of the motor neuron pool during rapid voluntary contractions in humans is presented. We show with this approach that the motor neuron recruitment speed and maximal motor unit discharge rate largely explains the individual ability in generating rapid force contractions. The results also indicate that the synaptic inputs received by the motor neurons before force is generated dictate human potential to generate force rapidly. This is the first characterization of the discharge behaviour of a representative sample of human motor neurons during rapid contractions. ABSTRACT: During rapid contractions, motor neurons are recruited in a short burst and begin to discharge at high frequencies (up to >200 Hz). In the present study, we investigated the behaviour of relatively large populations of motor neurons during rapid (explosive) contractions in humans, applying a new approach to accurately identify motor neuron activity simultaneous to measuring the rate of force development. The activity of spinal motor neurons was assessed by high-density electromyographic decomposition from the tibialis anterior muscle of 20 men during isometric explosive contractions. The speed of motor neuron recruitment and the instantaneous motor unit discharge rate were analysed as a function of the impulse (the time-force integral) and the maximal rate of force development. The peak of motor unit discharge rate occurred before force generation and discharge rates decreased thereafter. The maximal motor unit discharge rate was associated with the explosive force variables, at the whole population level (r2 = 0.71 ± 0.12; P < 0.001). Moreover, the peak motor unit discharge and maximal rate of force variables were correlated with an estimate of the suprasp
Del Vecchio A, Casola A, Negro F, et al., 2019, The increase in muscle force after 4 weeks of strength training is mediated by adaptations in motor unit recruitment and rate coding, The Journal of Physiology, Vol: 597, Pages: 1873-1887, ISSN: 1469-7793
The strength of a muscle typically begins to increase after only a few sessions of strength training. This increase is usually attributed to changes in the neural drive to muscle as a result of adaptations at the cortical or spinal level. We investigated the change in the discharge characteristics of large populations of longitudinally tracked motor units in tibialis anterior before and after 4 weeks of strength training the ankle‐dorsiflexor muscles with isometric contractions. The adaptations exhibited by 14 individuals were compared with 14 control subjects. High‐density electromyogram grids with 128 electrodes recorded the myoelectric activity during isometric ramp contractions to the target forces of 35%, 50% and 70% of maximal voluntary force. The motor unit recruitment and derecruitment thresholds, discharge rate, interspike intervals and estimates of synaptic inputs to motor neurons were assessed. The normalized recruitment‐threshold forces of the motor units were decreased after strength training (P < 0.05). Moreover, discharge rate increased by 3.3 ± 2.5 pps (average across subjects and motor units) during the plateau phase of the submaximal isometric contractions (P < 0.001). Discharge rates at recruitment and derecruitment were not modified by training (P < 0.05). The association between force and motor unit discharge rate during the ramp‐phase of the contractions was also not altered by training (P < 0.05). These results demonstrate for the first time that the increase in muscle force after 4 weeks of strength training is the result of an increase in motor neuron output from the spinal cord to the muscle.
Tanzarella S, Muceli S, Del Vecchio A, et al., 2019, A high-density surface EMG framework for the study of motor neurons controlling the intrinsic and extrinsic muscles of the hand, 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), Pages: 2307-2310, ISSN: 1557-170X
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- Citations: 2
Ting J, Del Vecchio A, Friedenberg D, et al., 2019, A wearable neural interface for detecting and decoding attempted hand movements in a person with tetraplegia, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEE, Pages: 1930-1933, ISSN: 1557-170X
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- Citations: 10
Ubeda A, Del Vecchio A, Vujaklija I, et al., 2019, Analysis of Intramuscular Motor Unit Coherence in the Tibialis Anterior Muscle as a Tool for the Assessment of Robot-Assisted Rehabilitation, Editors: Masia, Micera, Akay, Pons, Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 231-235, ISBN: 978-3-030-01844-3
Liew BXW, Del Vecchio A, Falla D, 2018, The influence of musculoskeletal pain disorders on muscle synergies-A systematic review, PLOS ONE, Vol: 13, ISSN: 1932-6203
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- Citations: 16
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