Flexible control of motor units: is the multidimensionality of motor unit manifolds a sufficient condition?

The Journal of Physiology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 18, 2025

Abstract Understanding flexibility in the neural control of movement requires identifying distribution common inputs to motor units. In this study, we identified large samples units from two lower limb muscles: vastus lateralis (VL; up 60 per participant) and gastrocnemius medialis (GM; 67 participant). First, applied a linear dimensionality reduction method assess manifolds underlying unit activity. We subsequently investigated under conditions: sinusoidal contractions with torque feedback, online visual feedback on firing rates. Overall, found that activity GM was effectively captured by single latent factor defining unidimensional manifold, whereas VL were better represented three factors multidimensional manifold. Despite difference dimensionality, recruitment muscles exhibited similarly low levels flexibility. Using spiking network model, tested hypothesis derived factorization does not solely represent descending cortical commands but is also influenced spinal circuitry. demonstrated heterogeneous units, or specific configurations recurrent inhibitory circuits, could produce This study clarifies an important debated issue, demonstrating while firings non‐compartmentalized muscle can lie CNS may still have limited capacity for flexible these image Key points To generate movement, distributes both excitatory The level remains topic debate significant implications smallest control. By combining experimental data silico models, sample be manifold; however, show very their recruitment. manifold directly reflect instead relate organization local circuits.

Language: Английский

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Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy

PLoS Computational Biology, Journal Year: 2023, Volume and Issue: 19(12), P. e1011606 - e1011606

Published: Dec. 7, 2023

The computational simulation of human voluntary muscle contraction is possible with EMG-driven Hill-type models whole muscles. Despite impactful applications in numerous fields, the neuromechanical information and physiological accuracy such provide remain limited because multiscale simplifications that limit comprehensive description internal dynamics during contraction. We addressed this limitation by developing a novel motoneuron-driven neuromuscular model, describes force-generating population individual motor units, each which was described actuator controlled dedicated experimentally derived motoneuronal control. In forward contraction, model transforms vector motoneuron spike trains decoded from high-density EMG signals into unit forces sum predicted force. control provides separate descriptions recruitment discharge decodes subject's intention. subject-specific, muscle-specific, includes an advanced activation dynamics, validated against experimental Accurate force predictions were obtained when neural controls representative activity complete pool. This achieved large dense grids electrodes medium-force contractions or methods physiologically estimate units not identified experimentally. advances state-of-the-art modelling, bringing together fields musculoskeletal finding human-machine interfacing research.

Language: Английский

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NeuroMechanics: Electrophysiological and computational methods to accurately estimate the neural drive to muscles in humans in vivo

Journal of Electromyography and Kinesiology, Journal Year: 2024, Volume and Issue: 76, P. 102873 - 102873

Published: March 7, 2024

Language: Английский

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Human motor unit discharge patterns reveal differences in neuromodulatory and inhibitory drive to motoneurons across contraction levels

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Oct. 17, 2023

ABSTRACT Transformation of motor commands via a unit (MU) into mechanical actions muscle fibres is non-linear function influenced by ionotropic excitatory/inhibitory and neuromodulatory inputs. Neuromodulatory inputs facilitate dendritic persistent inward currents on motoneurons, which introduce non-linearities in MU discharge patterns allowing estimation the structure commands. We investigated relative contribution neuromodulation pattern inhibition to human with increasing contraction force. In Experiment 1, we identified discharges tibialis anterior, vastus lateralis medialis during isometric triangular dorsiflexion knee extension contractions, respectively, up 70% maximal voluntary force (MVF). quantified onset-offset hysteresis (ΔF) performed quasi-geometric analyses quantify magnitude non-linearity, slopes acceleration rate attenuation regions. show that ΔF increased, whereas became more linear had lower at greater forces. 2 required participants dorsiflex MVF either matched duration or increase determine if these factors were confounding modulation across Though non-linearity duration, changes variables forces similar 1. The results suggest input are uniquely shaped support increases large proportion pool’s recruitment range three limb muscles.

Language: Английский

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Motor unit sampling from intramuscular micro-electrode array recordings

IEEE Transactions on Neural Systems and Rehabilitation Engineering, Journal Year: 2025, Volume and Issue: 33, P. 620 - 629

Published: Jan. 1, 2025

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

Language: Английский

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Intrinsic properties of spinal motoneurons degrade ankle torque control in humans

The Journal of Physiology, Journal Year: 2025, Volume and Issue: unknown

Published: March 28, 2025

Motoneurons are the final common pathway for all motor commands and possess intrinsic electrical properties that must be tuned to control muscle across full range of behaviours. Neuromodulatory input from brainstem is probably essential adapting motoneuron match this diversity tasks. A primary mechanism adaptation, dendritic persistent inward currents (PICs) in motoneurons by monoaminergic systems, generates both amplification prolongation synaptic inputs. While essential, there an inherent tension between prolongation. Although PICs allows quick recruitment acceleration discharge, deactivated derecruit upon movement cessation. In contrast, during stabilizing or postural tasks, PIC-induced inputs critical sustained discharge. Here, we designed two tasks challenged inhibitory PICs, generating unduly PIC increases variability human torque control. This included a paradigm combining discrete task with another involving length-induced changes balance excitatory available controlling PICs. We show introduces difficulties ankle these further degraded at shorter lengths when greatest. These results highlight necessity showcase issues introduced constrained. Our findings suggest that, like sensory errors systems. not due problems perception movement-related but embedded stage output. has many implications relevant clinical conditions (e.g. chronic stroke) where pathological shifts monoamines may amplify errors. KEY POINTS: All processed via spinal motoneurons, whose adapted neuromodulatory input. The effects (i.e. currents; PICs) tightly regulated allow large repertoire restrict ability substantial reduce precision output humans. systems may, speculatively, shed light on contributing factors cramps.

Language: Английский

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Matching dynamically varying forces with multi-motor-unit muscle models: a simulation study

Royal Society Open Science, Journal Year: 2025, Volume and Issue: 12(4)

Published: April 1, 2025

Human muscles exhibit great versatility, not only generating forces for demanding athleticism, but also fine motor tasks. While standard musculoskeletal models may reproduce this they often lack multiple units (MUs) and rate-coded control. To investigate how these features affect a muscle’s ability to generate desired force profiles, we performed simulations with nine alternative MU pool two cases: (i) tibialis anterior muscle an isometric trapezoidal profile, (ii) generic shoulder reaching movement whilst undergoing predetermined length changes. We implemented control strategies, pure feedforward combined feedforward-feedback, each parameterized using elementary The results suggest that the characteristics of pools have relatively little impact on pools’ overall match across all tasks, although performances individual tasks varied. Feedback improved performance nearly physiologically more relevant types were responsive feedback particularly during reaching. well in conditions tested, highlight need consider functional given vast repertoire dynamic by muscles.

Language: Английский

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A multi-label deep residual shrinkage network for high-density surface electromyography decomposition in real-time

Journal of NeuroEngineering and Rehabilitation, Journal Year: 2025, Volume and Issue: 22(1)

Published: May 8, 2025

The swift and accurate identification of motor unit spike trains (MUSTs) from surface electromyography (sEMG) is essential for enabling real-time control in neural interfaces. However, the existing sEMG decomposition methods, including blind source separation (BSS) deep learning, have not yet achieved satisfactory performance, due to high latency or low accuracy. This study introduces a novel high-density (HD-sEMG) algorithm named ML-DRSNet, which combines multi-label learning with residual shrinkage network (DRSNet) improve accuracy reduce latency. ML-DRSNet was evaluated on public dataset corresponding MUSTs extracted via convolutional BSS algorithm. An improved (ML-DCNN) also compared against conventional multi-task DCNN (MT-DCNN). These networks were trained tested various window sizes step sizes. With shortest size (20 data points) (10 points), significantly outperformed both ML-DCNN (0.86 ± 0.18 vs. 0.71 0.24, P < 0.001) MT-DCNN 0.66 0.16, precision. Moreover, demonstrated notably lower (15.15 ms) (69.36 (76.96 ms), reduced relative BSS-based methods. proposed algorithms substantially enhance performance decomposing MUSTs, establishing technical foundation neuro-information-driven intention recognition disease assessment.

Language: Английский

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Influence of spatio-temporal filtering on hand kinematics estimation from high-density EMG signals

Journal of Neural Engineering, Journal Year: 2024, Volume and Issue: 21(2), P. 026014 - 026014

Published: March 15, 2024

Surface electromyography (sEMG) is a non-invasive technique that records the electrical signals generated by muscles through electrodes placed on skin. sEMG state-of-the-art method used to control active upper limb prostheses because of association between its amplitude and neural drive sent from spinal cord muscles. However, accurately estimating kinematics freely moving human hand using extrinsic remains challenge. Deep learning has been recently successfully applied this problem mapping raw into kinematics. Nonetheless, optimal number EMG type pre-processing would maximize performance have not investigated yet.

Language: Английский

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Wearable sensing for understanding and influencing human movement in ecological contexts

Current Opinion in Biomedical Engineering, Journal Year: 2023, Volume and Issue: 28, P. 100492 - 100492

Published: July 25, 2023

Language: Английский

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