758 results found
Del Vecchio A, Marconi Germer C, Kinfe TM, et al., 2023, The forces generated by agonist muscles during isometric contractions arise from motor unit synergies., J Neurosci
The purpose of our study was to identify the low-dimensional latent components, defined hereafter as motor unit modes, underlying the discharge rates of the motor units in two knee extensors (vastus medialis and lateralis, eight men) and two hand muscles (first dorsal interossei and thenars, seven men and one woman) during submaximal isometric contractions. Factor analysis identified two independent motor unit modes that captured most of the covariance of the motor unit discharge rates. We found divergent distributions of the motor unit modes for the hand and vastii muscles. On average, 75% of the motor units for the thenar muscles and first dorsal interosseus were strongly correlated with the module for the muscle in which they resided. In contrast, we found a continuous distribution of motor unit modes spanning the two vastii muscle modules. The proportion of the muscle-specific motor unit modes was 60% for vastus medialis and 45% for vastus lateralis. The other motor units were either correlated with both muscle modules (shared inputs) or belonged to the module for the other muscle (15% for vastus lateralis). Moreover, coherence of the discharge rates between motor unit pools was explained by the presence of shared synaptic inputs. In simulations with 480 integrate-and-fire neurons, we demonstrate that factor analysis identifies the motor unit modes with high levels of accuracy. Our results indicate that correlated discharge rates of motor units that comprise motor unit modes arise from at least two independent sources of common input among the motor neurons innervating synergistic muscles.Significance statement:It has been suggested that the nervous system controls synergistic muscles by projecting common synaptic inputs to the engaged motor neurons. In our study, we reduced the dimensionality of the output produced by pools of synergistic motor neurons innervating the hand and thigh muscles during isometric contractions. We found two neural modules, each repres
Casolo A, Maeo S, Balshaw TG, et al., 2023, Non-invasive estimation of muscle fibre size from high-density electromyography, The Journal of Physiology, ISSN: 0022-3751
Vujaklija I, IEEE Member, Ki Jung M, et al., 2023, Biomechanical analysis of body movements of myoelectric prosthesis users during standardized clinical tests, IEEE Transactions on Biomedical Engineering, Vol: 70, Pages: 789-799, ISSN: 0018-9294
Objective: The objective clinical evaluation of user's capabilities to handle their prosthesis is done using various tests which primarily focus on the task completion speed and do not explicitly account for the potential presence of compensatory motions. Given that the excessive body compensation is a common indicator of inadequate prosthesis control, tests which include subjective observations on the quality of performed motions have been introduced. However, these metrics are then influenced by the examiner's opinions, skills, and training making them harder to standardize across patient pools and compare across different prosthetic technologies. Here we aim to objectively quantify the severity of body compensations present in myoelectric prosthetic hand users and evaluate the extent to which traditional objective clinical scores are still able to capture them. Methods: We have instructed 9 below-elbow prosthesis users and 9 able-bodied participants to complete three established objective clinical tests: Box-and-Blocks-Test, Clothespin-Relocation-Test, and Southampton-Hand-Assessment-Procedure. During all tests, upper-body kinematics has been recorded. Results: While the analysis showed that there are some correlations between the achieved clinical scores and the individual body segment travel distances and average speeds, there were only weak correlations between the clinical scores and the observed ranges of motion. At the same time, the compensations were observed in all prosthesis users and, for the most part, they were substantial across the tests. Conclusion: The sole reliance on the currently available objective clinical assessment methods seems inadequate as the compensatory movements are prominent in prosthesis users and yet not sufficiently accounted for.
Caillet AH, Avrillon S, Kundu A, et al., 2023, Larger and denser: an optimal design for surface grids of EMG electrodes to identify greater and more representative samples of motor units
<jats:title>Abstract</jats:title><jats:p>The spinal motor neurons are the only neural cells whose individual activity can be non-invasively identified using grids of electromyographic (EMG) electrodes and source separation methods, i.e., EMG decomposition. In this study, we combined computational and experimental approaches to assess how the design parameters of grids of electrodes influence the number and characteristics of the motor units identified. We first computed the percentage of unique motor unit action potentials that could be theoretically discriminated in a pool of 200 simulated motor units when recorded with grids of various sizes and interelectrode distances (IED). We then identified motor units from experimental EMG signals recorded in six participants with grids of various sizes (range: 2-36 cm<jats:sup>2</jats:sup>) and IED (range: 4-16 mm). Increasing both the density and the number of electrodes, as well as the size of the grids, increased the number of motor units that the EMG decomposition could theoretically discriminate, i.e., up to 82.5% of the simulated pool (range: 30.5-82.5%). Experimentally, the configuration with the largest number of electrodes and the shortest IED maximized the number of motor units identified (56 ± 14; range: 39-79) and the percentage of low-threshold motor units identified (29 ± 14%). Finally, we showed with a prototyped grid of 400 electrodes (IED: 2 mm) that the number of identified motor units plateaus beyond an IED of 2-4 mm. These results showed that larger and denser surface grids of electrodes help to identify a larger and more representative pool of motor units than currently reported in experimental studies.</jats:p><jats:sec><jats:title>Significance statement</jats:title><jats:p>Individual motor unit activities can be exactly identified by blind-source separation methods applied to multi-channel EMG signals recorded by grids of electr
Tereshenko V, Maierhofer U, Dotzauer DC, et al., 2023, Newly identified axon types of the facial nerve unveil supplemental neural pathways in the innervation of the face., J Adv Res, Vol: 44, Pages: 135-147
INTRODUCTION: Neuromuscular control of the facial expressions is provided exclusively via the facial nerve. Facial muscles are amongst the most finely tuned effectors in the human motor system, which coordinate facial expressions. In lower vertebrates, the extracranial facial nerve is a mixed nerve, while in mammals it is believed to be a pure motor nerve. However, this established notion does not agree with several clinical signs in health and disease. OBJECTIVES: To elucidate the facial nerve contribution to the facial muscles by investigating axonal composition of the human facial nerve. To reveal new innervation pathways of other axon types of the motor facial nerve. METHODS: Different axon types were distinguished using specific molecular markers (NF, ChAT, CGRP and TH). To elucidate the functional role of axon types of the facial nerve, we used selective elimination of other neuronal support from the trigeminal nerve. We used retrograde neuronal tracing, three-dimensional imaging of the facial muscles, and high-fidelity neurophysiological tests in animal model. RESULTS: The human facial nerve revealed a mixed population of only 85% motor axons. Rodent samples revealed a fiber composition of motor, afferents and, surprisingly, sympathetic axons. We confirmed the axon types by tracing the originating neurons in the CNS. The sympathetic fibers of the facial nerve terminated in facial muscles suggesting autonomic innervation. The afferent fibers originated in the facial skin, confirming the afferent signal conduction via the facial nerve. CONCLUSION: These findings reveal new innervation pathways via the facial nerve, support the sympathetic etiology of hemifacial spasm and elucidate clinical phenomena in facial nerve regeneration.
Nowak M, Vujaklija I, Sturma A, et al., 2023, Simultaneous and proportional real-time myocontrol of up to three degrees of freedom of the wrist and hand, IEEE Transactions on Biomedical Engineering, Vol: 70, Pages: 459-469, ISSN: 0018-9294
Achieving robust, intuitive, simultaneous and proportional control over multiple degrees of freedom (DOFs) is an outstanding challenge in the development of myoelectric prosthetic systems. Since the priority inmyoelectric prosthesis solutions is robustness and stability, their number of functions is usually limited. Objective: Here, we introduce a system for intuitive concurrent hand and wrist control, based on a robust feature-extraction protocol and machine-learning. Methods: Using the meanabsolute value of high-density EMG, we train a ridge-regressor (RR) on only the sustained portions of the single-DOF contractions and leverage the regressor’s inherent ability to provide simultaneous multi-DOF estimates. In this way, we robustly capture the amplitude information of the inputs while harnessing the power of the RR to extrapolate otherwise noisy and often overfitted estimations of dynamic portions of movements. Results: The real-time evaluation of the system on 13 able-bodied participants and an amputee shows that almost all single-DOF tasks could be reached (96% success rate), while at the same time users were able to complete most of the two-DOF (62%) and even some of the very challenging three-DOF tasks (37%). To further investigate the translational potential of the approach, we reduced the original 192-channel setup to a 16-channel configuration and the observed performance did not deteriorate. Notably, the amputee performed similarly well to the other participants, according to all considered metrics. Conclusion: This is the first real-time operated myocontrol system that consistently provides intuitive simultaneous and proportional control over 3-DOFs of wrist and hand, relying on only surface EMG signals from the orearm. Significance: Focusing on reduced complexity, a real-time test and the inclusion of an amputee in the study demonstrate the translational potential of the control system for future applications in prosthetic control.
Martinez-Valdes E, Enoka RM, Holobar A, et al., 2023, Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix., J Electromyogr Kinesiol, Vol: 68
The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials generated by an alpha motor neuron and those received by the innervated muscle fibers. Such a powerful assessment has been conventionally performed with invasive electrodes (i.e., intramuscular electromyography (EMG)), however, recent advances in signal processing techniques have enabled the identification of single motor unit (SMU) activity in high-density surface electromyography (HDsEMG) recordings. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, provides recommendations for the recording and analysis of SMU activity with both invasive (needle and fine-wire EMG) and non-invasive (HDsEMG) SMU identification methods, summarizing their advantages and disadvantages when used during different testing conditions. Recommendations for the analysis and reporting of discharge rate and peripheral (i.e., muscle fiber conduction velocity) SMU properties are also provided. The results of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers to collect, report, and interpret SMU data in the context of both research and clinical applications.
Free DB, Syndergaard I, Pigg AC, et al., 2023, Essential Tremor accentuates the pattern of tremor-band coherence between upper-limb muscles., J Neurophysiol, Vol: 129, Pages: 524-540
Although Essential Tremor is one of the most common movement disorders, current treatment options are relatively limited. Peripheral tremor suppression methods have shown potential, but we do not currently know which muscles are most responsible for patients' tremor, making it difficult to optimize suppression methods. The purpose of this study was to quantify the relationships between the tremorogenic activity in muscles throughout the upper limb. Muscle activity was recorded from the 15 major superficial upper-limb muscles in 24 subjects with Essential Tremor while they held various postures or made upper-limb movements. We calculated the coherence in the tremor band (4-12 Hz) between the activity of all muscle pairs and the time-varying phase difference between sufficiently coherent muscle pairs. Overall, the observed pattern somewhat mirrored functional relationships: agonistic muscle pairs were most coherent and in phase, whereas antagonist and unrelated muscle pairs exhibited less coherence and were either consistently in phase, consistently antiphase, consistently out of phase (unrelated pairs only), or else inconsistent. Patients exhibited significantly more coherence than control subjects (p<0.001) in the vast majority of muscle pairs (95 out of 105). Furthermore, differences between patients and controls were most pronounced among agonists; thus, the coherence pattern existing in control subjects was accentuated in patients with ET. We conclude that tremor-band activity is broadly distributed among the muscles of the upper limb, challenging efforts to determine which muscles are most responsible for a patient's tremor.
Pascual-Valdunciel A, Lopo-Martínez V, Beltrán-Carrero AJ, et al., 2023, Classification of kinematic and electromyographic signals associated with pathological tremor using machine and deep learning., Entropy (Basel, Switzerland), Vol: 25, Pages: 1-13, ISSN: 1099-4300
Peripheral Electrical Stimulation (PES) of afferent pathways has received increased interest as a solution to reduce pathological tremors with minimal side effects. Closed-loop PES systems might present some advantages in reducing tremors, but further developments are required in order to reliably detect pathological tremors to accurately enable the stimulation only if a tremor is present. This study explores different machine learning (K-Nearest Neighbors, Random Forest and Support Vector Machines) and deep learning (Long Short-Term Memory neural networks) models in order to provide a binary (Tremor; No Tremor) classification of kinematic (angle displacement) and electromyography (EMG) signals recorded from patients diagnosed with essential tremors and healthy subjects. Three types of signal sequences without any feature extraction were used as inputs for the classifiers: kinematics (wrist flexion-extension angle), raw EMG and EMG envelopes from wrist flexor and extensor muscles. All the models showed high classification scores (Tremor vs. No Tremor) for the different input data modalities, ranging from 0.8 to 0.99 for the f1 score. The LSTM models achieved 0.98 f1 scores for the classification of raw EMG signals, showing high potential to detect tremors without any processed features or preliminary information. These models may be explored in real-time closed-loop PES strategies to detect tremors and enable stimulation with minimal signal processing steps.
Khan MN, Cherukuri P, Negro F, et al., 2022, ERR2 and ERR3 promote the development of gamma motor neuron functional properties required for proprioceptive movement control., PLoS Biol, Vol: 20
The ability of terrestrial vertebrates to effectively move on land is integrally linked to the diversification of motor neurons into types that generate muscle force (alpha motor neurons) and types that modulate muscle proprioception, a task that in mammals is chiefly mediated by gamma motor neurons. The diversification of motor neurons into alpha and gamma types and their respective contributions to movement control have been firmly established in the past 7 decades, while recent studies identified gene expression signatures linked to both motor neuron types. However, the mechanisms that promote the specification of gamma motor neurons and/or their unique properties remained unaddressed. Here, we found that upon selective loss of the orphan nuclear receptors ERR2 and ERR3 (also known as ERRβ, ERRγ or NR3B2, NR3B3, respectively) in motor neurons in mice, morphologically distinguishable gamma motor neurons are generated but do not acquire characteristic functional properties necessary for regulating muscle proprioception, thus disrupting gait and precision movements. Complementary gain-of-function experiments in chick suggest that ERR2 and ERR3 could operate via transcriptional activation of neural activity modulators to promote a gamma motor neuron biophysical signature of low firing thresholds and high firing rates. Our work identifies a mechanism specifying gamma motor neuron functional properties essential for the regulation of proprioceptive movement control.
Hug F, Avrillon S, Ibanez J, et al., 2022, Common synaptic input, synergies and size principle: Control of spinal motor neurons for movement generation, JOURNAL OF PHYSIOLOGY-LONDON, Vol: 601, Pages: 11-20, ISSN: 0022-3751
Muceli S, Poppendieck W, Holobar A, et al., 2022, Blind identification of the spinal cord output in humans with high-density electrode arrays implanted in muscles, SCIENCE ADVANCES, Vol: 8, ISSN: 2375-2548
Levine J, Avrillon S, Farina D, et al., 2022, Two motor neuron synergies, invariant across ankle joint angles, activate the triceps surae during plantarflexion
<jats:title>Abstract</jats:title><jats:p>Recent studies have suggested that the central nervous system generates movements by controlling groups of motor neurons (synergies) that do not always align with muscle anatomy. In this study, we determined whether these synergies are robust across tasks with different mechanical constraints. We identified motor neuron synergies using principal component analysis (PCA) and cross-correlations between smoothed discharge rates of motor neurons. In Part 1, we used simulations to validate these methods. The results suggested that PCA can accurately identity the number of common inputs and classify motor neurons according to the synaptic weights of the common inputs they receive. Moreover, the results confirmed that cross-correlation can separate pairs of motor neurons that receive common inputs from those that do not receive common inputs. In Part 2, sixteen individuals performed plantarflexion at three ankle angles while recording high-density surface electromyography from the gastrocnemius lateralis (GL) and medialis (GM) and the soleus (SOL) muscles. We identified and tracked the same motor units across angles. PCA revealed two motor neuron synergies, primarily grouping motor neurons innervating GL-SOL and GM-SOL. These motor neuron synergies were relatively stable with 74.0% of motor neurons classified in the same synergy across angles. Cross-correlation demonstrated that only 13.9% of pairs of motor neurons maintained a non-significant level of correlation across angles, confirming the large presence of common inputs. Overall, these results highlighted the modularity of movement control at the motor neuron level, which may ensure a sensible reduction of computational resources for movement control.</jats:p><jats:sec><jats:title>Significance statement</jats:title><jats:p>The central nervous system may generate movements by activating clusters of motor neurons with common inputs.
OKeeffe R, Shirazi SY, Del Vecchio A, et al., 2022, Low-frequency motor cortex EEG predicts four levels of rate of change of force during ankle dorsiflexion
<jats:title>Abstract</jats:title><jats:p>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)<jats:italic>MRCP morphological characteristics</jats:italic>in the<jats:italic>δ</jats:italic>-band such as amplitude and timing, (ii)<jats:italic>MRCP statistical characteristics</jats:italic>in the<jats:italic>δ</jats:italic>-band such as mean, standard deviation, and kurtosis, and (iii)<jats:italic>wideband time-frequency features</jats:italic>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<jats:italic>min</jats:italic><jats:sub>1</jats:sub>and<jats:italic>min<jats:sub>n</jats:sub></jats:italic>for the morphological sets. This monotonical response of features explains the observed performance of the<jats:italic>δ</jats:italic>-band MRCP and corresponding high discriminative power. Results from temporal analysis
Koutsoftidis S, Barsakcioglu DY, Petkos K, et al., 2022, Myolink: A 128-Channel, 18 nV/root Hz, Embedded Recording System, Optimized for High-Density Surface Electromyogram Acquisition, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 69, Pages: 3389-3396, ISSN: 0018-9294
Caillet A, Phillips ATM, Farina D, et al., 2022, Mathematical relationships between spinal motoneuron properties, eLife, Vol: 11, ISSN: 2050-084X
Our understanding of the behaviour of spinal alpha-motoneurons (MNs) in mammals partly relies on our knowledge of the relationships between MN membrane properties, such as MN size, resistance, rheobase, capacitance, time constant, axonal conduction velocity and afterhyperpolarization period. We reprocessed the data from 40 experimental studies in adult cat, rat and mouse MN preparations, to empirically derive a set of quantitative mathematical relationships between these MN electrophysiological and anatomical properties. This validated mathematical framework, which supports past findings that the MN membrane properties are all related to each other and clarifies the nature of their associations, is besides consistent with the Henneman’s size principle and Rall’s cable theory. The derived mathematical relationships provide a convenient tool for neuroscientists and experimenters to complete experimental datasets, to explore relationships between pairs of MN properties never concurrently observed in previous experiments, or to investigate inter-mammalian-species variations in MN membrane properties. Using this mathematical framework, modelers can build profiles of inter-consistent MN-specific properties to scale pools of MN models, with consequences on the accuracy and the interpretability of the simulations.
Lin C, Chen X, Guo W, et al., 2022, A BERT based Method for Continuous Estimation of Cross-subject Hand Kinematics from Surface Electromyographic Signals., IEEE Trans Neural Syst Rehabil Eng, Vol: PP
Estimation of hand kinematics from surface electromyographic (sEMG) signals provides a non-invasive human-machine interface. This approach is usually subject-specific, so that the training on one individual does not generalise to different subjects. In this paper, we propose a method based on Bidirectional Encoder Representation from Transformers (BERT) structure to predict the movement of hands from the root mean square (RMS) feature of the sEMG signal following μ-law normalization. The method was tested for within-subject and cross-subject conditions. We trained the model with two hard sample mining methods, Gradient Harmonizing Mechanism (GHM) and Online Hard Sample Mining (OHEM). The proposed method was compared with classic approaches, including long short-term memory (LSTM) and Temporal Convolutional Network (TCN) as well as a recent method called Long Exposure Convolutional Memory Network (LE-ConvMN). Correlation coefficient (CC), normalized root mean square error (NRMSE) and time costs were used as performance metrics. Our method (sBERT-OHEM) achieved state-of-the-art performance in cross-subject evaluation as well as high performance in subject-specific tests on the Ninapro dataset. The above tests are based on the same randomly selected 10 subjects. Generally, in the cross-subject situation, with the increasing of the subjects' number, it unavoidably leads to the decline of the performance. While the performance of our method on 38 subjects was significantly higher than the other methods on 10 subjects in cross-subject conditions, which further verified the advantage of our methods.
Caillet AH, Phillips ATM, Carty C, et al., 2022, Hill-type computational models of muscle-tendon actuators: a systematic review
<jats:title>Abstract</jats:title><jats:p>Backed by a century of research and development, Hill-type muscle-tendon models are extensively used for countless applications. Lacking recent reviews, the field of Hill-type modelling is however dense and hard-to-explore, with detrimental consequences on knowledge transmission, inter-study consistency, and innovation. Here we present the first systematic review of the field of Hill-type muscle-tendon modelling. It aims to clarify the literature by detailing its contents and proposing updated terminology and definitions, and discussing the state-of-the-art by identifying the latest advances, current gaps, and potential improvements in modelling muscle properties. To achieve this aim, fifty-five criteria-abiding studies were extracted using a systematic search and their Hill-type models assessed according to a completeness evaluation, which identified the modelled muscle-tendon properties, and a modelling evaluation, which considered the level of validation and reusability of the model, and attention given to its modelling strategy and calibration. It is concluded that most models (1) do not significantly advance the dated gold standards in muscle modelling and do not build upon more recent advances, (2) overlook the importance of parameter identification and tuning, (3) are not strongly validated, and (4) are not reusable in other studies. Besides providing a convenient tool supported by extensive supplementary material for understanding the literature, the results of this review open a discussion on the necessity for global recommendations in Hill-type modelling and more frequent reviews to optimize inter-study consistency, knowledge transmission and model reusability.</jats:p>
Zicher B, Ibáñez J, Farina D, 2022, Beta inputs to motor neurons do not directly contribute to volitional force modulation, The Journal of Physiology, ISSN: 0022-3751
Neural oscillatory activity in the beta band (13–30 Hz) is prominent in the brain and it is transmitted partly linearly to the spinal cord and muscles. Multiple views on the functional relevance of beta activity in the motor system have been proposed. Previous simulation work suggested that pools of spinal motoneurons (MNs) receiving a common beta input could demodulate this activity, transforming it into low-frequency neural drive that could alter force production in muscles. This may suggest that common beta inputs to muscles have a direct role in force modulation. Here we report the experimental average levels and ranges of common beta activity in spinal MNs projecting to single muscles and use a computational model of a MN pool to test if the experimentally observed beta levels in MNs can influence force. When beta was modelled as a continuous activity, the amplitude needed to produce non-negligible changes in force corresponded to beta representation in the MN pool that was far above the experimental observations. On the other hand, when beta activity was modelled as short-lived events (i.e. bursts of beta activity separated by intervals without beta oscillations), this activity approximated levels that could cause small changes in force with estimated average common beta inputs to the MNs compatible with the experimental observations. Nonetheless, bursting beta is unlikely to be used for force control due to the temporal sparsity of this activity. It is therefore concluded that beta oscillations are unlikely to contribute to the voluntary modulation of force.
Tereshenko V, Dotzauer DC, Luft M, et al., 2022, Autonomic nerve fibers aberrantly reinnervate denervated facial muscles and alter muscle fiber population., J Neurosci, Vol: 42, Pages: 8297-8307
The surgical redirection of efferent neural input to a denervated muscle via a nerve transfer can reestablish neuromuscular control after nerve injuries. The role of autonomic nerve fibers during the process of muscular reinnervation remains largely unknown. Here, we investigated the neurobiological mechanisms behind the spontaneous functional recovery of denervated facial muscles in male rodents. Recovered facial muscles demonstrated an abundance of cholinergic axonal endings establishing functional neuromuscular junctions. The parasympathetic source of the neuronal input was confirmed to be in the pterygopalatine ganglion. Furthermore, the autonomically reinnervated facial muscles underwent a muscle fiber change to a purely intermediate muscle fiber population (MHCIIa). Finally, electrophysiological tests revealed that the postganglionic parasympathetic fibers travel to the facial muscles via the sensory infraorbital nerve. Our findings demonstrated expanded neuromuscular plasticity of denervated striated muscles enabling functional recovery via alien autonomic fibers. These findings may further explain the underlying mechanisms of sensory protection implemented to prevent atrophy of a denervated muscle.SIGNIFICANCE STATEMENT:Nerve injuries represent significant morbidity and disability for patients. Rewiring motor nerve fibers to other target muscles have shown to be a successful approach in the restoration of motor function. This demonstrates the remarkable capacity of the central nervous system to adapt to the needs of the neuromuscular system. Yet, the capability of skeletal muscles being reinnervated by non-motor axons remains largely unknown. Here, we show that under deprivation of original efferent input, the neuromuscular system can undergo functional and morphological remodeling via autonomic nerve fibers. This may explain neurobiological mechanisms of the sensory protection phenomenon, which is due to parasympathetic reinnervation.
Lubel E, Sgambato BG, Barsakcioglu DY, et al., 2022, Kinematics of individual muscle units in natural contractions measured in vivo using ultrafast ultrasound, JOURNAL OF NEURAL ENGINEERING, Vol: 19, ISSN: 1741-2560
- Author Web Link
- Citations: 2
Del Vecchio A, Jones RHA, Schofield IS, et al., 2022, Interfacing motor units in non-human primates identifies a principal neural component for force control constrained by the size principle, The Journal of Neuroscience, Vol: 42, Pages: 7383-7399, ISSN: 0270-6474
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 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 with a broad range of rate of force development (1.8 - 38.6 N∙m∙s-1). 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 fully predicted by the motor unit recruitment intervals, so that small shifts in recruitment thresholds happened only during contractions at 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 represented a time-shifted version of the first. 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.
Sanchez MG, Sanchez JRP, Valdunciel AP, et al., 2022, Electrical Stimulation of Muscle Afferents for Tremor Reduction in Essential Tremor Patients, Publisher: WILEY, Pages: S244-S245, ISSN: 0885-3185
Caillet AH, Phillips ATM, Farina D, et al., 2022, Estimation of the firing behaviour of a complete motoneuron pool by combining electromyography signal decomposition and realistic motoneuron modelling, PLOS COMPUTATIONAL BIOLOGY, Vol: 18, ISSN: 1553-734X
- Author Web Link
- Citations: 1
de Oliveira DS, Casolo A, Balshaw TG, et al., 2022, Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units, JOURNAL OF NEURAL ENGINEERING, Vol: 19, ISSN: 1741-2560
- Author Web Link
- Citations: 2
Yeung D, Guerra IM, Barner-Rasmussen I, et al., 2022, Co-Adaptive Control of Bionic Limbs via Unsupervised Adaptation of Muscle Synergies., IEEE Trans Biomed Eng, Vol: 69, Pages: 2581-2592
OBJECTIVE: In this work, we present a myoelectric interface that extracts natural motor synergies from multi-muscle signals and adapts in real-time with new user inputs. With this unsupervised adaptive myocontrol (UAM) system, optimal synergies for control are continuously co-adapted with changes in user motor control, or as a function of perturbed conditions via online non-negative matrix factorization guided by physiologically informed sparseness constraints in lieu of explicit data labelling. METHODS: UAM was tested in a set of virtual target reaching tasks completed by able-bodied and amputee subjects. Tests were conducted under normative and electrode perturbed conditions to gauge control robustness with comparisons to non-adaptive and supervised adaptive myocontrol schemes. Furthermore, UAM was used to interface an amputee with a multi-functional powered hand prosthesis during standardized Clothespin Relocation Tests, also conducted in normative and perturbed conditions. RESULTS: In virtual tests, UAM effectively mitigated performance degradation caused by electrode displacement, affording greater resilience over an existing supervised adaptive system for amputee subjects. Induced electrode shifts also had negligible effect on the real world control performance of UAM with consistent completion times (23.91 ±1.33 s) achieved across Clothespin Relocation Tests in the normative and electrode perturbed conditions. CONCLUSION: UAM affords comparable robustness improvements to existing supervised adaptive myocontrol interfaces whilst providing additional practical advantages for clinical deployment. SIGNIFICANCE: The proposed system uniquely incorporates neuromuscular control principles with unsupervised online learning methods and presents a working example of a freely co-adaptive bionic interface.
Shirzadi M, Marateb HR, McGill KC, et al., 2022, An Accurate and Real-time Method for Resolving Superimposed Action Potentials in MultiUnit Recordings., IEEE Trans Biomed Eng, Vol: PP
OBJECTIVE: Spike sorting of muscular and neural recordings requires separating action potentials that overlap in time (superimposed action potentials (APs)). We propose a new algorithm for resolving superimposed action potentials, and we test it on intramuscular EMG (iEMG) and intracortical recordings. METHODS: Discrete-time shifts of the involved APs are first selected based on a heuristic extension of the peel-off algorithm. Then, the time shifts that provide the minimal residual Euclidean norm are identified (Discrete Brute force Correlation (DBC)). The optimal continuous-time shifts are then estimated (High-Resolution BC (HRBC)). In Fusion HRBC (FHRBC), two other cost functions are used. A parallel implementation of the DBC and HRBC algorithms was developed. The performance of the algorithms was assessed on 11,000 simulated iEMG and 14,000 neural recording superpositions, including two to eight APs, and eight experimental iEMG signals containing four to eleven active motor units. The performance of the proposed algorithms was compared with that of the Branch-and-Bound (BB) algorithm using the Rank-Product (RP) method in terms of accuracy and efficiency. RESULTS: The average accuracy of the DBC, HRBC and FHRBC methods on the entire simulated datasets was 92.16±17.70, 93.65±16.89, and 94.90±15.15 (%). The DBC algorithm outperformed the other algorithms based on the RP method. The average accuracy and running time of the DBC algorithm on 10.5 ms superimposed spikes of the experimental signals were 92.1±21.7 (%) and 2.3±15.3 (ms). CONCLUSION AND SIGNIFICANCE: The proposed algorithm is promising for real-time neural decoding, a central problem in neural and muscular decoding and interfacing.
Hug F, Avrillon S, Sarcher A, et al., 2022, Correlation networks of spinal motor neurons that innervate lower limb muscles during a multi-joint isometric task, JOURNAL OF PHYSIOLOGY-LONDON, ISSN: 0022-3751
- Author Web Link
- Citations: 4
Ibanez Pereda J, Zicher B, Brown KE, et al., 2022, Standard intensities of transcranial alternating current stimulation over the motor cortex do not entrain corticospinal inputs to motor neurons, The Journal of Physiology, ISSN: 0022-3751
Transcranial alternating current stimulation (TACS) is commonly used to synchronise a cortical area and its outputs to the stimulus waveform, but evidence for this based on brain recordings in humans is challenging. The corticospinal tract transmits beta oscillations (~21Hz) from motor cortex to tonically contracted limb muscles linearly. Therefore, muscle activity may be used to measure 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 indirect evidence for TACS-driven neural entrainment. In the first part of this study, we ran simulations of motor neuron (MN) pools receiving inputs from corticospinal neurons with different levels of beta entrainment. Results suggest that MNs are 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 or the tibialis anterior muscle were tonically contracted. Muscle activity was measured using high-density electromyography, which allowed us to decompose the activity of pools of motor units innervating the muscles. By analysing motor unit pool activity, we observed that none of the TACS conditions could consistently alter the spectral contents of the common neural inputs received by the muscles. These results suggest that 1mA-TACS over motor cortex given at beta frequencies does not entrain corticospinal activity.
Hasbani MH, Barsakcioglu DY, Jung MK, et al., 2022, Simultaneous and proportional control of wrist and hand degrees of freedom with kinematic prediction models from high-density EMG., Pages: 764-767
To improve intuitive control and reduce training time for active upper limb prostheses, we developed a myocontrol system for 3 degrees of freedom (DoFs) of the hand and wrist. In an offline study, we systematically investigated movement sets used to train this system, to identify the optimal compromise between training time and performance. High-density surface electromyography (HDsEMG) and optical marker motion capture were recorded concurrently from the lower arms of 8 subjects performing a series of wrist and hand movements activating DoFs individually, sequentially, and simultaneously. The root mean square (RMS) feature extracted from the EMG signal and kinematics obtained from motion capture were used to train regression and classification models to predict the kinematics of wrist movements and opening and closing of the hand, respectively. Results showed successful predictions of kinematics when training with the complete training set (r2 = 0.78 for wrist regression and recall = 0.85 for hand closing/opening classification). In further analysis, the training set was substantially reduced by removing the simultaneous movements. This led to a statistically significant, but relatively small reduction of the effectiveness of the wrist controller (r2 = 0.70, p<0.05), without changes for the hand controller (closing recall = 0.83). Reducing the training time and complexity needed to control a prosthesis with simultaneous wrist control as well as detection of intention to close the hand can lead to improved uptake of upper limb prosthetics.
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