Biology subjects

Del Vecchio, A.

Publications and source records attributed to Del Vecchio, A..

29 records · Page 2Linked to original sources

bioRxiv2022

Mental fatigue impairs physical performance but not the neural drive to the muscle

Mental fatigue (MF) does not only affect cognitive but also physical performance. This study aimed to explore the effects of MF on muscle endurance, rate of perceived exertion (RPE), and motor units activity. Ten healthy males participated in a randomised crossover study. The subjects attended two identical experimental sessions separated by three days with the only difference of a cognitive task (incongruent Stroop task [ST]) and a control condition (watching a documentary). Perceived MF and motivation were measured for each session at baseline and after each cognitive task. Four contractions at 20% of maximal voluntary contraction (MVIC) were performed at baseline, after each cognitive and after muscle endurance task while measuring motor units by high-density surface electromyography. Muscle endurance until failure at 50% of MVIC was measured after each cognitive task and the RPE was measured right after failure. ST significantly increased MF (p = 0.001) reduced the motivation (p = 0.008) for the subsequent physical task and also impaired physical performance (p = 0.044). However, estimates of common synaptic inputs and motor unit discharge rates as well as RPE were not affected by MF (p> 0.11). In conclusion, MF impairs muscle endurance and motivation for the physical task but not the neural drive to the muscle at any frequency bands. Although it is physiologically possible for mentally fatigued subjects to generate an optimal neuromuscular function, the altered perception and motivation seems to limit physical performance. Our results suggest that the corticospinal pathways are not affected by MF.

physiology↗

bioRxiv2022

Sensing the Full Dynamics of the Human Hand with a Neural Interface and Deep Learning

Theories about the neural control of movement are largely based on movement-sensing devices that capture the dynamics of predefined anatomical landmarks. However, neuromuscular interfaces such as surface electromyography (sEMG) can potentially overcome the limitations of these technologies by directly sensing the motor commands transmitted to the muscles. This allows for the continuous, real-time prediction of kinematics and kinetics without being limited by the biological and physical constraints that affect motion-based technologies. In this work, we present a deep learning method that can decode and map the electrophysiological activity of the forearm muscles into movements of the human hand. We recorded the kinematics and kinetics of the human hand during a wide range of grasping and individual digit movements covering more than 20 degrees of freedom of the hand at slow (0.5 Hz) and fast (1.5 Hz) movement speeds in healthy participants. The input of the model consists of three-hundred EMG sensors placed only on the extrinsic hand muscles. We demonstrate that our neural network can accurately predict the kinematics and contact forces of the hand even during unseen movements and with simulated real-time resolution. By examining the latent space of the network, we find evidence that it has learned the underlying anatomical and neural features of the sEMG that drive all hand motor behaviours.

neuroscience↗

bioRxiv2022

Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units

ObjectiveHigh-density surface electromyography (HD-sEMG) allows the reliable identification of individual motor unit (MU) action potentials. Despite the accuracy in decomposition, there is a large variability in the number of identified MUs across individuals and exerted forces. Here we present a systematic investigation of the anatomical and neural factors that determine this variability. ApproachWe investigated factors of influence on HD-sEMG decomposition, such as synchronization of MU discharges, distribution of MU territories, muscle-electrode distance (MED - subcutaneous fat thickness), maximum anatomical cross-sectional area (ACSAmax), and fiber CSA. For this purpose, we recorded HD-sEMG signals, ultrasound, magnetic resonance imaging, and muscle biopsy of the biceps brachii muscle from two groups of participants - untrained-controls (UT=14) and strength-trained (>3 years of training, ST=16) - while they performed isometric ramp contractions with elbow flexors (at 15, 35, 50 and 70% maximum voluntary torque - MVT). We assessed the correlation between the number of accurately detected MUs by HD-sEMG decomposition and each measured parameter, for each target force level. Multiple regression analysis was then applied. Main resultsST subjects showed lower MED (UT: 4.8 {+/-} 1.4 vs. ST: 3.7 {+/-} 0.8 mm) associated to a greater number of identified motor units (UT: 21.3 {+/-} 10.2 vs. ST: 29.2 {+/-} 11.8 MUs/subject). Both groups showed a negative correlation between MED and the number of identified MUs at low forces (r= -0.6, p=0.002 at 15% MVT). Moreover, the number of identified MUs was positively correlated to the distribution of MU territories (r=0.56, p=0.01) and ACSAmax (r=0.48, p=0.03) at 15% MVT. By accounting for all anatomical parameters, we were able to partly predict the number of decomposed MUs at low but not at high forces. SignificanceOur results confirmed the influence of subcutaneous tissue on the quality of HD-sEMG signals and demonstrated that MU spatial distribution and ACSAmax are also relevant parameters of influence for current decomposition algorithms.

bioengineering↗

bioRxiv2022

Reticulospinal drive increases maximal motoneuron output in humans

Maximal rate of force development in adult humans is determined by the maximal motoneuron output, however the origin of the underlying synaptic inputs remains unclear. Here, we tested a hypothesis that the maximal motoneuron output will increase in response to a startling cue, a stimulus that purportedly activates the pontomedullary reticular formation neurons that make mono- and disynaptic connections to motoneurons via fast-conducting axons. Twenty-two men were required to produce isometric knee extensor forces "as fast and as hard" as possible from rest to 75% of maximal voluntary force, in response to visual (VC), visual-auditory (VAC), or visual-startling cue (VSC). Motoneuron activity was estimated via decomposition of high-density surface electromyogram recordings over the vastus lateralis and medialis muscles. Reaction time was significantly shorter in response to VSC compared to VAC and VC (i.e., the StartReact effect). The VSC further elicited faster neuromechanical responses including a greater number of discharges per motor unit per second and greater maximal rate of force development, with no differences between VAC and VC. We provide evidence, for the first time, that the synaptic input to motoneurons increases in response to a startling cue, suggesting a contribution of subcortical pathways to maximal motoneuron output in humans, likely originating from the pontomedullary reticular formation.

physiology↗

bioRxiv2022

Common synaptic inputs are not distributed homogeneously among the motor neurons that innervate synergistic muscles

The force generated by the muscles involved in an action is produced by common synaptic inputs received by the engaged motor neurons. The purpose of our study was to identify the low-dimensional latent components, defined hereafter as neural modules, underlying the discharge rates of the motor units from two knee extensors (vastus medialis and lateralis) and two hand muscles (index and thumb muscles) during isometric contractions. The neural modules were extracted by factor analysis from the pooled motor units and no assumptions were made regarding the orthogonality of the modules or the association between the modules and each muscle. Factor analysis identified two independent neural modules that captured most of the covariance in the discharge rates of the motor units in the synergistic muscles. Although the neural modules were strongly correlated with the discharge rates of motor units in each of the synergistic pair of muscles, not all motor units in a muscle were correlated with the neural module for that muscle. The distribution of motor units across the pair of neural modules differed for each muscle: 80% of the motor units in first dorsal interosseous were more strongly correlated with the neural module for that muscle, whereas the proportion was 70%, 60%, and 45% for the thenar, vastus medialis, and vastus lateralis muscles. All other motor units either belonged to both modules or to the module for the other muscle (15% for vastus lateralis). Based on a simulation of 480 integrate-and-fire neurons receiving independent and common inputs, we demonstrate that factor analysis identifies the three neural modules with high levels of accuracy. Our results indicate that the correlated discharge rates of motor units arise from at least two sources of common synaptic input that are not distributed homogeneously among the motor neurons innervating synergistic muscles.

neuroscience↗

bioRxiv2022

Transcranial alternating current stimulation does not modulate corticospinal activity in humans

Transcranial alternating current stimulation (TACS) is commonly used to synchronise the output of a cortical area to other parts of the nervous system, but evidence for this based on brain recordings in humans is challenging. The brain transmits beta oscillations (~21Hz) to tonically contracted limb muscles linearly and through the fastest corticospinal pathways. Therefore, muscle activity may be used as a proxy measure for the level of beta entrainment in the corticospinal tract due to TACS over motor cortex. Here, we assessed if TACS is able to modulate the neural inputs to muscles, which would provide an indirect evidence for TACS-driven neural entrainment. In the first part of this study, we ran a series of simulations of motor neuron (MN) pools receiving inputs from corticospinal neurons with different levels of beta entrainment. Results indicated that MNs should be highly sensitive to changes in corticospinal beta activity. Then, we ran experiments on healthy human subjects (N=10) in which TACS (at 1mA) was delivered over the motor cortex at 21Hz (beta stimulation), or at 7Hz or 40Hz (control conditions) while the abductor digiti minimi (ADM) or the tibialis anterior muscle (TA) were tonically contracted. Muscle activity was measured using high-density electromyography, which allowed us to decompose the spiking activity of pools of motor units innervating the studied muscles. By analysing motor unit pool activity, we observed that none of the tested TACS conditions could consistently alter the spectral characteristics of the common neural inputs received by the muscles. These results suggest that 1mA-TACS over motor cortex given at frequencies in the beta band does not affect corticospinal beta entrainment. Highlights- TACS is commonly used to entrain the communication between brain regions - It is challenging to find direct evidence supporting TACS-driven neural entrainment - Simulations show that motor neurons are sensitive to corticospinal beta entrainment - Motor unit activity from human muscles does not support TACS-driven entrainment

neuroscience↗

bioRxiv2021

Interfacing Spinal Motor Units in Non-Human Primates Identifies a Principal Neural Component for Force Control Constrained by the Size Principle

Motor units convert the last neural code of movement into muscle forces. The classic view of motor unit control is that the central nervous system 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 the performance of tasks with some level of behavioural variability. Here we identified and tracked populations of motor units in the brachioradialis muscle of two macaque monkeys during ten sessions spanning over one month during high force isometric contractions with a broad range of rate of force development (1.8 - 38.6 N{middle dot}m{middle dot}s-1). During the same sessions we recorded intramuscular EMG signals from 16 arm muscles of both limbs and elicited the full recruitment through neural stimulation of the median and deep radial nerves. 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 observed between motor units with close recruitment thresholds, and only during 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 could be described as a time-shifted version of the first, as it could be predicted from the interplay between the size principle of recruitment and one common input. In conclusion, our results show that motoneurons recruitment is determined by the interplay of the size principle and common input and that this recruitment scheme is not violated over time nor by the speed of the contractions.

neuroscience↗

bioRxiv2021

Functional connectivity networks of common synaptic inputs to motor neurons reveal neural spinal synergies during a multi-joint 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 has been the muscle. In this human study, we decoded the spiking activities of spinal motor neurons innervating six lower limb muscles during an isometric multi-joint task. We identified their common low-frequency components, from which networks of common synaptic inputs to the motor neurons were derived. 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. Our results provide evidence of a synergistic control of a multi-joint motor task at the spinal motor-neuron level. TeaserThe generation of movement involves the activation of many spinal motor neurons from multiple muscles. A central and unresolved question is how these motor neurons are controlled to allow flexibility for adaptation to various mechanical constraints. Since the computational load of controlling each motor neuron independently would be extremely large, the central nervous system presumably adopts dimensionality reduction. We identified networks of functional connectivity between spinal motor neurons based on the common synaptic inputs they receive during a multi-joint task. Our findings revealed functional groupings of motor neurons in a low dimensional space. These groups did not necessarily overlap with the muscle anatomy. We provide a new neural framework for a deeper understanding of movement control in health and disease.

neuroscience↗

bioRxiv2021

Why humans are stronger but not faster after isometric strength training: specific neural, not muscular, motor unit adaptations

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.

neuroscience↗

bioRxiv2021

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 x 11 contractions/muscles x 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.

neuroscience↗

bioRxiv2020

Only the fastest corticospinal fibers contribute to beta corticomuscular coherence

A common way to study human corticospinal transmission is with transcranial magnetic stimulation. However, this 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. A possible alternative to overcome this limitation is to study the corticospinal transmission of endogenously generated brain activity. Here we study the transmission speeds of cortical beta rhythms travelling to the muscles during steady contractions. To do this, we introduce new methods to improve delay estimates in the corticomuscular transmission of beta rhythms, and which we validate both in simulations and experimentally. Applying these approaches to experimental data from humans, we show that corticomuscular beta transmission delays are only 1-2ms longer than expected from the fastest corticospinal pathway. Simulations using realistic distributions of the conduction velocities for descending axons projecting to lower motoneurons suggest two scenarios that can explain these results: either a very small fraction of only the fastest corticospinal axons selectively transmit beta activity, or else the entire pool does. The implications that these two scenarios have for our understanding of corticomuscular interactions are discussed in the final part of this manuscript. SIGNIFICANCEWe present and validate an improved methodology to measure the delay in the transmission of cortical beta activity to tonically active muscles. The estimated corticomuscular beta transmission delays which this yields are remarkably similar to those expected from transmission in the fastest corticospinal axons. A simulation of beta transmission along a pool of corticospinal axons using a realistic distribution of fiber diameters suggests two possible mechanisms by which fast corticomuscular transmission is achieved: either a very small fraction of descending axons transmits beta activity to the muscles or, alternatively, the entire population does and natural cancellation of slow channels occurs due to the distribution of axon diameters in the corticospinal tract.

neuroscience↗