Biology subjects

Del Vecchio, A.

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

At least 19 recordsLinked to original sources

bioRxiv2026

The Human Rectus Femoris Muscle Receives an Independent Common Synaptic Input During Isometric Leg Extensions

The distribution of common synaptic inputs across spinal motor neuron pools within and across synergist muscles reveals direct insight in the neural control of movement. We previously documented two dominant common inputs in the human vastus lateralis (VL) and medialis (VM) muscle during isometric leg extensions. Whether these inputs are also shared with rectus femoris (RF), a synergist muscle that contributes substantially to leg extension but is biarticular, remains unknown. We simultaneously recorded motor unit activity from VM, RF, and VL using multiple targeted intramuscular electromyographic sensors during isometric knee extension. Decomposed motor unit spike trains were analyzed using discharge characteristics, pairwise correlation, spectral coherence, explained variance, and factor analysis to characterize the structure of common synaptic input within and across muscles. Despite their shared mechanical output via a common patellar tendon, the three muscles exhibited distinct patterns of neural organization. RF consistently received a strong, low-dimensional common input that was largely independent of the drive to VM and VL, as evidenced by elevated within-muscle correlation and coherence, low between-muscle coupling, and an invariant dedicated latent factor across all participants. VM and VL shared a substantial proportion of common synaptic input, but the degree of coupling and the underlying factor structure varied across individuals, ranging from a single shared factor to largely independent muscle-specific inputs. These findings indicate that the quadriceps are organized in a muscle- and subject-specific manner, with RF receiving a dedicated independent input.

neuroscience↗

bioRxiv2026

Unilateral resistance training induces greater rate coding adaptations in high-threshold motor units during maximal voluntary contractions

Resistance training lasting a few weeks increases maximal force mainly through neural adaptations that enhance the drive from the nervous system to muscle. While these adaptations have been well documented at the motor unit (MU) level during submaximal force contractions, the mechanisms underlying force increases during maximal voluntary contractions are poorly understood. This is due to a classic technical limitation in tracking MUs longitudinally during maximal force tasks. Here, we solved this technical challenge, enabling the investigation of MU adaptations during MVCs in both the trained and untrained limbs following unilateral resistance training. High-density surface electromyography was recorded from the biceps brachii of both limbs before and after a 4-week unilateral resistance-training intervention, and the same MUs were longitudinally tracked across sessions during MVCs by concatenation of three MVC trials of [~]5-s each. Unilateral training increased maximal force in the trained limb (+16%) and induced strength transfer to the untrained limb (+8%). In both limbs, maximal contractions after training were characterized by greater EMG amplitude, faster muscle-fiber conduction velocity, and higher MU discharge rates, indicating enhanced neural drive to the motoneuron pool. These adaptations were strongly associated with improvements in maximal force (R2 > 0.7 for all). Importantly, longitudinal MU tracking revealed a non-uniform adaptation across the MU pool: MUs with higher baseline conduction velocity, indicative of higher recruitment threshold, exhibited the largest pre-post increases in discharge rate, whereas lower-threshold units showed smaller changes. Collectively, these findings demonstrate that gains in maximal force and their transfer to the untrained limb are primarily mediated by enhanced rate coding of higher-threshold MUs during MVCs.

physiology↗

bioRxiv2026

Curated Residual Decomposition for Increased MU Yield from HD-sEMG

High-density surface electromyography (HD-sEMG) decomposition algorithms identify motor units (MUs) from non-invasive recordings, yet even gold-standard methods typically decompose only a subset of all physiologically active MUs and preferentially extract higher-amplitude units, leaving low-amplitude MUs underrepresented. We propose Curated Residual Decomposition (CRD): Through decomposition of the residual signal remaining from a manually edited initial decomposition, we identify additional, mainly lower amplitude MUs that were previously undetected due to action potential superposition and preferential convergence to larger MUs. We applied this approach to three datasets: concurrent HD-sEMG and HD-iEMG recordings from three muscles for two-source validation, and two publicly available datasets. Across all datasets, CRD substantially increased MU yield. In the two-source validation dataset, the first CRD iteration increased yield by 31-50% (FDI: 46.9%, TA: 49.8%, VL: 31.1%), with validation via intramuscular recordings confirming comparable identification accuracy of the CRD compared to the original MUs (RoA original: 0.994 {+/-} 0.005; RoA CRD: 0.992 {+/-} 0.009). In public datasets, yield increases ranged from 35-142% per muscle in the first iteration. Correspondingly, the explained signal power ratio increased, with the first iteration accounting for most gains. A second CRD iteration resulted in an additional, yet smaller yield increase (0-26.7%). Additionally identified MUs had smaller action potential amplitudes and lower recruitment thresholds, indicating the recovery of smaller, lower-threshold MUs. CRD reliably increased MU yield and explained signal power across diverse muscles, datasets, and decomposition implementations. The approach provides an optional, validated step for more complete decomposition results across the full recruitment range in offline analyses.

neuroscience↗

bioRxiv2026

Physiological and pathological motor unit phenotypes coexist within single motor pools after cervical SCI

Individuals with chronic cervical spinal cord injury (SCI) retain voluntary motor unit (MU) activation below the level of the lesion despite profound impairments in muscle relaxation, yet the MU-level mechanisms underlying this dissociation remain unclear. Here, we investigated MU recruitment and derecruitment dynamics using high-density surface EMG (HD-sEMG) and intramuscular EMG (iEMG), in functionally paralyzed muscles across open- and closed-loop tasks in four participants with chronic cervical SCI. Building on prior work that distinguished task-modulated from non-modulated MUs, we combined closed-loop MU feedback with targeted intramuscular implants to determine whether tonic units remain accessible to voluntary control and whether distinct firing phenotypes coexist within individual motor pools. Participants voluntarily recruited MUs and modulated discharge rates (45.2%), but a significant fraction (54.8%) of active MUs could not be derecruited during attempted relaxation. Quantitative analysis of 409 MUs revealed that derecruitment impairment spans a graded continuum rather than the binary distinction between modulated and non-modulated units reported previously. Three phenotypes, controllable (45.2%), modulated-tonic (42.8%), and tonic (12%), partition this spectrum based on derecruitment timing, discharge regularity, and firing persistence and coexist within the same motor pools, including within single muscle compartments sampled intramuscularly. Kaplan-Meier survival analysis confirmed graded derecruitment dynamics: controllable units ceased firing within 500 ms of rest onset, whereas most tonic units persisted throughout the observation window (log-rank{chi} 2= 164.10, P < 0.001). Tonic units displayed highly regular discharge consistent with intrinsic motoneuron excitation via persistent inward currents (PIC). Phenotypes were consistent across recording modalities and task contexts, and phenotype effects on derecruitment metrics exceeded movement-type effects by an order of magnitude. These findings identify impaired MU derecruitment as a core feature of spastic paralysis, driven by maladaptive motoneuron and spinal network properties that preserved descending drive cannot fully counteract. A proof-of-concept spike-train-level temporal filter selectively suppressed tonic firing while preserving voluntary modulation (>94% correlation retained), demonstrating a physiologically grounded strategy for improving neural interfacing after SCI.

neuroscience↗

bioRxiv2026

Automated Extraction and Meta-Analysis of a Century of Motor-Unit Research with NeuromechaniX

The scientific literature on human motor units and electromyography (EMG) spans over a century (1925-2025), comprising research impossible to synthesize manually. We introduce NeuromechaniX, a domain-specific platform for automated extraction and meta-analysis of this literature. The core component, MUscraper, is a large language model pipeline that extracts approximately 200 structured metadata fields, organized into 17 major sections spanning participant demographics, EMG acquisition parameters, muscle identification, task protocols, decomposition methods, and motor-unit outcomes, from [~]2,000 publications on human limb muscles. This automated extraction transforms heterogeneous narrative reports into a standardized, queryable database at a scale not achievable through manual review. From this dataset, we analyzed motor-unit discharge rate across 208 studies examining seven muscles. Our analyses reveal that discharge rates differ significantly among muscles (p<0.001), with biceps brachii exhibiting the highest rates (15.9 pps), followed by first dorsal interosseous (13.7 pps) and tibialis anterior (13.5 pps), whereas gastrocnemius (11.3 pps), the vastii muscles (11.5 pps) and soleus show the lowest rates (9.9 pps). Sex-stratified analysis shows females exhibit higher discharge rates than males (14.5 vs 11.9 pps; Cohens d=0.38, p=0.018). In contrast, age-stratified analysis reveals non-significant differences between young and older adults (d=-0.24, p=0.072). Collectively, these results show that current views of human motor units are limited to a few muscles, with little data on females and older adults. The complete structured database is available through an open-access interactive platform (https://neuro-mechanix.com/metadata), enabling researchers to explore, filter, and download the extracted metadata. NeuromechaniX provides infrastructure for large-scale meta-research, identification of literature gaps, and hypothesis generation for the neuromechanics community.

physiology↗

bioRxiv2026

State- and Identity-Dependent Motor Neuron Excitability Shapes Cutaneous Long-Latency Reflexes

Neuromuscular reflexes elicited by sensory nerve stimulation provide valuable insights into neural motor control pathways. Analysis at the level of individual motor units (MUs) is feasible via electromyographic decomposition, but the factors shaping MU-specific reflex responses remain poorly understood. We investigated long-latency responses to cutaneous electrical stimulation in a large population of tibialis anterior MUs from nine healthy subjects during isometric ankle dorsiflexion at 10-30% of maximum voluntary contraction. Individual MU reflex responses differed markedly. Using 1000 stimulation pulses per trial, substantially more than the 150-300 typically reported in previous studies, provided more reliable estimates of cutaneous reflex characteristics. Across the motor pool, reflex magnitude increased with force level (p < 0.001) while excitation probability correlated significantly with MU recruitment threshold in 78% of subjects (p = 0.012). Furthermore, excitation probability increased systematically with contraction intensity (p < 0.001) for individually tracked MUs. Post-excitatory depression (PED) magnitude correlated significantly with excitation probability (r = 0.50, p < 0.001) of individual MUs. A targeted reflex-removal analysis, validated by MU simulations incorporating realistic excitation probabilities into ordinary firing patterns, reduced the PED by 84.2% in simulated data but only by 34.7% in recorded units. These findings suggest that the PED is a complex, hybrid phenomenon, resulting from synchronization-induced discharge resetting and additional independent inhibitory components. These findings demonstrate that MU-level reflex excitability to somatosensory input is influenced by state- and identity-dependent motor neuron characteristics, underscoring the importance of using sufficient stimulation pulses for reliable reflex measures and MU population analysis.

neuroscience↗

bioRxiv2026

A DNA foundation model predicts osteoporosis risk genes without proximity bias

Targets supported by human genetic associations are more than twice as likely to progress from clinical development to approval. Genome-wide association studies are the largest source of genetic evidence for disease risk but linking non-coding variants to effector genes remains a significant barrier to identifying causal targets. Current gene-mapping approaches suffer from proximity bias, largely ignoring distal genes. Here we introduce Rosalind, a DNA foundation model fine-tuned on human genetic variation from GTEx, that directly predicts variant-gene regulatory relationships from sequence without relying on nearest-gene heuristics. We demonstrate Rosalinds accuracy through extensive benchmarking, apply it to multiple complex traits to establish broad utility, and provide experimental validation in osteoporosis using a translational osteoblast assay. We demonstrate that genes distal to osteoporosis risk variants were significantly more likely to alter a bone formation phenotype than nearest genes. Together, these results highlight deep learning-based regulatory models as a general and scalable framework for translating novel genetic insights to drug discovery.

genetics↗

bioRxiv2026

MyoGen: Unified Biophysical Modeling of Human Neuromotor Activity and Resulting Signals

Understanding human motor control requires integrating cortical and spinal cord activity, muscle mechanics, and electrophysiology, levels that are often studied separately. We present MyoGen, an open-source framework that unifies spinal circuitry, proprioceptive feedback, musculotendon dynamics, cortical activity, and multimodal electromyography (EMG) generation in a single, interoperable platform. Spinal motor neurons and the resulting motor unit (MU) action potentials represent the only neural cells that can be accessed at scale in humans. We used human MU ensembles to validate our model across a wide range of experimental conditions. Using data-driven optimization, we found that MyoGen produces MU population activity that closely matches experimental discharge-rate distributions and discharge variability across human muscles. Moreover, it generates decomposable surface and intramuscular EMG, reproduces beta-band modulation of descending drive and its nonlinear transformation into force, and implements complete sensorimotor loops. Dimensionality reduction of simulated agonist-antagonist EMG reveals low-dimensional control manifolds consistent with experimental recordings from both healthy and spinal cord injured individuals. MyoGen provides physiologically grounded, ground-truth data and integrates seamlessly with analysis pipelines, enabling systematic investigation of motor control principles, validation of signal-processing algorithms, and exploration of sensorimotor interactions that are experimentally inaccessible.

neuroscience↗

bioRxiv2025

Task-Dependent Motor Unit Recruitment and Rate Coding Reveal Redistribution of Neural Drive in the Human Hand

Although Henneman's size principle dictates an orderly small-to-large activation for a given common input, evidence suggests a certain level of flexibility in the recruitment of spinal motoneurons depending on task demands. Here, we investigate motor unit (MU) recruitment flexibility in the human first dorsal interosseus (FDI) muscle while controlling for overall muscle activation across two functionally distinct tasks using High-Density intramuscular EMG (HD-iEMG) electrode arrays. Six participants performed isometric index finger abduction where the FDI serves as the prime mover, and flexion with the FDI functioning as a synergist. Recruitment thresholds (RT) and recruitment orders (RO) were highly consistent within the same task, but differed significantly between abduction and flexion. Across participants, 45.3% of MUs showed changes in recruitment above the coefficient of repeatability across tasks compared to only 5.0% within tasks. The spatial distribution of muscle activation did not shift between tasks, confirming that the same muscle region was engaged in both. Changes in RT were accompanied by corresponding adaptations in discharge rate (DR), preserving the inverse RT-DR relationship. Intramuscular coherence analysis revealed no differences in the delta (1-5 Hz) or alpha (5-13 Hz) band, but beta band (13-30 Hz) coherence was significantly lower during flexion than abduction, indicating reduced common input synchronization in this frequency range when FDI serves as a synergist muscle. Together, these results indicate different distributions of net excitatory input to FDI MUs across different functional tasks, potentially involving a stronger contribution of spinal circuits during flexion, as suggested by the reduced intramuscular beta coherence. Moreover, the present findings also demonstrate that common synaptic input and not intrinsic motoneuron properties determines the inverse relation between MU RT and DR.

neuroscience↗

bioRxiv2025

PatchDNA: A Flexible and Biologically-Informed Alternative to Tokenization for DNA

AO_SCPLOWBSTRACTC_SCPLOWDNA language models are emerging as powerful tools for representing genomic sequences, with recent progress driven by self-supervised learning. However, performance on downstream tasks is sensitive to tokenization strategies reflecting the complex encodings in DNA, where both regulatory elements and single-nucleotide changes can be functionally significant. Yet existing models are fixed to their initial tokenization strategy; single-nucleotide encodings result in long sequences that challenge transformer architectures, while fixed multi-nucleotide schemes like byte pair encoding struggle with character level modeling. Drawing inspiration from the Byte Latent Transformers combining of bytes into patches, we propose that patching provides a competitive and more efficient alternative to tokenization for DNA sequences. Furthermore, patching eliminates the need for a fixed vocabulary, which offers unique advantages to DNA. Leveraging this, we propose a biologically informed strategy, using evolutionary conservation scores as a guide for patch boundaries. By prioritizing conserved regions, our approach directs computational resources to the most functionally relevant parts of the DNA sequence. We show that models up to an order of magnitude smaller surpass current state-of-the-art performance in existing DNA benchmarks. Importantly, our approach provides the flexibility to change patching without retraining, overcoming a fundamental limitation of current tokenization methods.

genomics↗

bioRxiv2025

Voluntary Dissociation of Motor Unit Activity in the Vastii Muscles

The CNS coordinates movement through consistent activation patterns across muscles and motor units, suggesting the presence of a relatively fixed and high-dimensional number of neural constraints on voluntary actions. In the human quadriceps, the vastus medialis (VM) and vastus lateralis (VL) control the knee extensor torque and are considered a synergistic pair largely activated by shared neural inputs. However, some evidence suggests that these muscles, or even subregions within them, can be controlled independently. In this study, we investigated whether humans can dissociate neural input to VM and VL during isometric contractions. Ten participants received real-time feedback from multiple intramuscular EMG electrodes that targeted different regions of the VM and VL while attempting to activate each muscle or sub-regions selectively. We found that nine out of ten subjects were able to clearly separate VM and VL activity based on the intramuscular EMG feedback. However, motor unit decomposition from the intramuscular EMGs revealed that selective recruitment of a unique set of motor units was possible only within the proximal region of VM. In contrast, VL and distal VM showed highly correlated activation, indicating tight functional coupling. Correlation analyses confirmed that the proximal VM exhibited distinct activation profiles compared with both distal VM and VL, supporting the existence of compartmentalized control within VM. These findings demonstrate that it is possible to dissociate the activation of motor units within this synergistic muscle group during low-force isometric contractions.

neuroscience↗

bioRxiv2025

Neural determinants of the increase in muscle strength and force steadiness of the untrained limb following a 4-week unilateral training

Enhanced untrained muscle strength and force steadiness following unilateral resistance training (i.e., cross-education) is typically attributed to neural responses. However, the mechanisms of these adaptations for spinal motoneurons remain unexplored. Therefore, we examined maximal-voluntary-force (MVF), steady-force variability (CovF), and longitudinally tracked motor unit adaptations in 10 individuals completing a 4-week unilateral strength intervention compared to 9 controls. High-density surface electromyography was recorded from the biceps brachii during steady (10%MVF) and trapezoidal (35%MVF) contractions. The relative proportion of common synaptic input (CSI) to motoneurons and its variability (CSI-V) were estimated using coherence and spectral analysis. Indirect estimates of persistent inward currents using firing rate hysteresis ({Delta}F) and motor unit recruitment thresholds (MURT) were assessed during the ramp forces (35%MVF). MVF increased in both the trained (+14%, p<0.001) and untrained limbs (+6%, p=0.004), and CovF decreased in both limbs (p<0.001). Greater CSI was observed on both sides (p<0.01), concomitant with reduced CSI-V (p<0.01). {Delta}F increased exclusively in the trained limbs (+1.61{+/-}0.71 pps; p<0.001), and both sides exhibited lower MURT (p<0.001). In trained limbs, MVF gains were strongly associated with changes in CSI, MURT, and {Delta}F (R{superscript 2}>0.70, p<0.01), while the contralateral muscle MVF increase was associated exclusively with CSI and MURT (R{superscript 2}>0.65, p<0.01). In both limbs, lower CovF was strongly associated with reduced CSI-V (R{superscript 2}>0.70, p<0.01). Our findings suggest that enhanced untrained muscle force and steadiness are mediated by increased relative strength of shared synaptic input with respect to independent noise and decreased variability of this shared input, with gains in trained muscle MVF being associated with {Delta}F. Key pointsO_LIUnilateral resistance training improves strength and force steadiness in the contralateral untrained limb, suggesting neural adaptations without directly overloading the muscle. C_LIO_LIDespite established force-related modifications, the specific neural mechanisms mediating these functional responses remain largely unknown. C_LIO_LI4-week unilateral training intervention enhanced muscle strength and force steadiness in the untrained limbs of 10 individuals, alongside a greater proportion of shared synaptic input, reduced variance in common input, and lower motor unit recruitment thresholds. C_LIO_LIWe demonstrate that the neural mechanisms underlying improved strength and force control in muscles without mechanical overloading are associated with a higher relative shared input among motoneurons and reduced variance in these common input components. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=148 SRC="FIGDIR/small/645159v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1a9e7feorg.highwire.dtl.DTLVardef@1bdd9a6org.highwire.dtl.DTLVardef@11c5ba0org.highwire.dtl.DTLVardef@c39a42_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOC_FLOATNO unilateral training intervention reduced the variance in common synaptic input (CSI-V), which was associated with decreased variability in force steadiness (CovF) in both the trained and contralateral untrained limbs. On the exercised side, the increase in maximal voluntary force (MVF) was accompanied by a higher proportion of common synaptic input (CSI), a lower motor unit recruitment threshold (RT), enhanced persistent inward current (PIC) amplitude, and increased neural drive. In contrast, the contralateral untrained limb exhibited higher shared synaptic input and a lower RT but with unaltered PIC amplitude and neural drive ({leftrightharpoons}). Overall, these adaptations resulted in a 14% increase in MVF in the exercised limb and a 6% increase in the untrained limb. C_FIG

physiology↗

bioRxiv2024

NeuroNella: A Robust Unsupervised Algorithm for Identification of Neural Activity from Multielectrode Arrays

We introduce NeuroNella, an automated algorithm developed for the identification of neuronal activity from multichannel electrode arrays. In evaluations conducted on recordings from implanted probes in the nervous system of rodents and primates, the algorithm demonstrated remarkable accuracy, showcasing an error rate of less than 1% compared to ground-truth patch clamp signals. Notably, the proposed algorithm handles large datasets efficiently without the necessity of a GPU system. The results highlighted the algorithms efficacy in detecting sources in a wide amplitude range and its adaptability in accommodating minor probe shifts. Moreover, the high robustness exhibited by the algorithm in decomposing recordings lasting up to 30 minutes underscores its potential for enabling longitudinal studies and prolonged recording sessions, thus opening new avenues for future brain/machine interface applications.

neuroscience↗

bioRxiv2023

Mechanical Hand Synergies during Dynamic Hand Movements are Mostly Controlled in a Non-Synergistic Way by Spinal Motor Neurons

Precise control of spinal motor neurons is crucial for voluntary hand and digit movements. However, the specific mechanisms by which motor unit ensembles govern dynamic synergistic and individual digit tasks remain poorly understood. We recorded synchronized 3D hand kinematics and high-density surface EMG (HD-sEMG) data from extrinsic hand muscles of twelve participants during 13 dynamic hand and digit movement tasks, consisting of single-digit flexion/extension and mechanically synergistic grasping tasks. We extracted single motor unit (MU) activity and identified identical MUs across tasks. We extracted 7.8 {+/-} 1.8 MUs per task and participant and found 182 out of 554 total MUs active during multiple movements. Analysis of the MU discharge patterns revealed two groups of motor units that were categorized into prime mover MUs, showing strong correlation between firing rate modulation and digit kinematics, and postural MUs with little modulated activity. We found these motor units could switch between the two modes, showing either postural or movement encoding activation depending on the task. However, MUs acted as prime mover only for one specific digit. We further observed highly task specific recruitment of prime mover MUs. Across participants, we found only 9 {+/-} 8.2 % of prime mover MUs active during a grasp task and any single digit task involved in the grasp motion. We draw three conclusions: (1) Single digits are controlled by distinct groups of MUs. (2) Unexpectedly, mechanically synergistic grasp movements are mostly controlled in a non-synergistic way by distinct groups of MUs. 3) Multiple manifolds construct the movement of the human hand, and each motor unit can flexibly switch between postural and dynamic modes. Significance StatementWe investigated the neural control of motor unit ensembles during single-digit and synergistic grasping tasks in dynamic conditions. We found that motor units exhibited strong movement-correlated activity only for one specific digit. We further observed highly task specific recruitment of motor units during mechanically synergistic grasp movements, showing that on a motor unit level, mechanically synergistic movements are controlled in a non-synergistic way. The findings extend the knowledge of motor unit recruitment strategies in natural movements and have strong implications in the field of neurorehabilitation and control of assistive devices.

neuroscience↗

bioRxiv2023

The short-term acquisition of a skill learning task unveils the neural filtering of shared synaptic input to spinal motor neurons

The acquisition of a motor skill involves adaptations of spinal and supraspinal pathways to alpha motoneurons. In this study, we estimated the shared synaptic contributions of these pathways to understand the neural mechanisms underlying the short-term acquisition of a new force-matching task. High-density surface electromyography (HDsEMG) was acquired from the first dorsal interosseous (FDI; 7 males and 6 females) and tibialis anterior (TA; 7 males and 4 females) during 15 trials of an isometric force-matching task. For two selected trials (pre- and post-skill acquisition), we decomposed the HDsEMG into motor unit spike trains, tracked motor units between trials, and calculated the mean discharge rate and the coefficient of variation of inter-spike interval (CoVISI). We also quantified the post/pre ratio of motor units coherence within delta, alpha, and beta bands. Improvements in force-matching were accompanied by a significant increase in the mean discharge rate and a decrease in CoVISI for both muscles. Moreover, the area under the curve within alpha band decreased by [~]22% and [~]13% for the TA and FDI muscles, respectively, with no changes in the delta or beta bands. These reductions correlated significantly with increased coupling between force/neural drive and target oscillations. These results suggest that the short-term acquisition of a new force-matching skill is mediated by the attenuation of tremor oscillations in the shared synaptic inputs. In other words, the central nervous system acts as a matched filter to modulate the synaptic weights of shared inputs and suppress neural components unrelated to the specific task. Supported by simulations, a plausible mechanism behind these alpha band reductions may involve spinal interneurons phase-cancelling descending oscillations.

neuroscience↗

bioRxiv2022

Low-frequency motor cortex EEG predicts four levels of rate of change of force during ankle dorsiflexion

The movement-related cortical potential (MRCP) is a low-frequency component of the electroencephalography (EEG) signal recorded from the motor cortex and its neighboring cortical areas. Since the MRCP encodes motor intention and execution, it may be utilized as an interface between patients and neurorehabilitation technologies. This study investigates the EEG signal recorded from the Cz electrode to discriminate between four levels of rate of force development (RFD) of the tibialis anterior muscle. For classification, three feature sets were evaluated to describe the EEG traces. These were (i) MRCP morphological characteristics in the{delta} -band such as amplitude and timing, (ii) MRCP statistical characteristics in the{delta} -band such as mean, standard deviation, and kurtosis, and (iii) wideband time-frequency features in the 0.5-90 Hz range. Using a support vector machine for classification, the four levels of RFD were classified with a mean (SD) accuracy of 82% (7%) accuracy when using the time-frequency feature space, and with an accuracy of 75% (12%) when using the MRCP statistical characteristics. It was also observed that some of the key features from the statistical and morphological sets responded monotonically to the intensity of the RFD. Examples are slope and standard deviation in the (0, 1)s window for the statistical, and min1 and minn for the morphological sets. This monotonical response of features explains the observed performance of the{delta} -band MRCP and corresponding high discriminative power. Results from temporal analysis considering the pre-movement phase ((-3, 0)s) and three windows of the post-movement phase ((0, 1)s, (1, 2)s, and (2, 3)s)) suggest that the complete MRCP waveform represents high information content regarding the planning, execution, duration, and ending of the isometric dorsiflexion task using the tibialis anterior muscle. Results shed light on the role of{delta} -band in translating to motor command, with potential applications in neural engineering systems.

bioengineering↗

bioRxiv2022

Non-invasive muscle biopsy: estimation of muscle fibre size from a neuromuscular interface

Because of the biophysical relation between muscle fibre diameter and the propagation velocity of action potentials along the muscle fibres, motor unit conduction velocity (MUCV) could be a non-invasive index of muscle fibre size in humans. However, the relation between MUCV and fibre size has been only assessed indirectly in animal models and in human patients with invasive intramuscular EMG recordings, or it has been mathematically derived from computer simulations. By combining advanced non-invasive techniques to record motor unit activity in vivo, i.e., high-density surface EMG, with the gold standard technique for muscle tissue sampling, i.e., muscle biopsy, here we investigated the relation between the conduction velocity of populations of motor units identified from the biceps brachii muscle, and muscle fibre diameter. Moreover, we demonstrate the possibility to predict muscle fibre diameter (R2 = 0.66) and cross-sectional area (R2 = 0.65) from conduction velocity estimates with low systematic bias (~2% and ~4% respectively) and a relatively low margin of individual error (~8% and ~16%, respectively). The proposed neuromuscular interface opens new perspectives in the use of high-density EMG as a non-invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling. The non-invasive nature of high-density surface EMG for the assessment of muscle fibre size may be useful in studies monitoring child development, aging, space and exercise physiology. SIGNIFICANCE STATEMENTOur study explored the relation between the conduction velocity of populations of motor units and muscle fibre size in healthy humans. Our results provide in vivo evidence that a high-density surface EMG-derived physiological parameter, i.e. motor unit conduction velocity, can be adopted to estimate muscle fibre size, without the need of surgical biopsy sampling. Here we propose a neuromuscular interface that opens new perspectives not only in the study of neuromuscular disorders, but also in other fields where the non-invasive and painless determination of muscle fibre and motor unit size becomes a priority, such as in aging, space and exercise physiology.

physiology↗

bioRxiv2022

Accurate measurement of inhibition and excitation in human motor pools during sensory stimulation

Surface electromyography (sEMG) is a pivotal approach in clinical and basic neurophysiology, allowing us to extract the summed activity of motor units in a given muscle. Due to the bipolar nature of the motor unit action potential, the sEMG is a non-linear representation of their underlying motor unit activity and therefore affected by signal cancellation. It is not clear how this cancellation influences evoked responses in sEMG. The aim of our study was to characterise how representative an evoked sEMG response was to the firing behaviour of the underlying motor pool. To do this, we first simulated a population of motor units (and their action potentials) that responded to a stimulus with a change in firing probability. Their activity was summed then rectified to generate a simulated sEMG signal or was rectified and then summed, to generate a sEMG signal with no cancellation. By comparing the two responses to that of the underlying pool we would then compare for discrepancies. We repeated this process but by using the responses of tibialis anterior motor units to weak tibial nerve stimulation. We find that both for the simulated and experimental data the response measured through the sEMG is almost always an underestimate of the evoked response in the underlying motor pool. This is the case for both inhibitory and excitatory evoked responses. The magnitude of the inaccuracy depends on the size of the evoked response, but it cannot be accounted solely by signal cancellation, suggesting other factors may also contribute.

neuroscience↗