Reading and Modulating Cortical ß Bursts from Motor Unit Spiking Activity.

ß Oscillations (13-30 Hz) are ubiquitous in the human motor nervous system. Yet, their origins and roles are unknown. Traditionally, ß activity has been treated as a stationary signal. However, recent studies observed that cortical ß occurs in "bursting events," which are transmitted to muscles. This short-lived nature of ß events makes it possible to study the main mechanism of ß activity found in the muscles in relation to cortical ß. Here, we assessed whether muscle ß activity mainly results from cortical projections. We ran two experiments in healthy humans of both sexes (N = 15 and N = 13, respectively) to characterize ß activity at the cortical and motor unit (MU) levels during isometric contractions of the tibialis anterior muscle. We found that ß rhythms observed at the cortical and MU levels are indeed in bursts. These bursts appeared to be time-locked and had comparable average durations (40-80 ms) and rates (approximately three to four bursts per second). To further confirm that cortical and MU ß have the same source, we used a novel operant conditioning framework to allow subjects to volitionally modulate MU ß. We showed that volitional modulation of ß activity at the MU level was possible with minimal subject learning and was paralleled by similar changes in cortical ß activity. These results support the hypothesis that MU ß mainly results from cortical projections. Moreover, they demonstrate the possibility to decode cortical ß activity from MU recordings, with a potential translation to future neural interfaces that use peripheral information to identify and modulate activity in the central nervous system.SIGNIFICANCE STATEMENT We show for the first time that ß activity in motor unit (MU) populations occurs in bursting events. These bursts observed in the output of the spinal cord appear to be time-locked and share similar characteristics of ß activity at the cortical level, such as the duration and rate at which they occur. Moreover, when subjects were exposed to a novel operant conditioning paradigm and modulated MU ß activity, cortical ß activity changed in a similar way as peripheral ß. These results provide evidence for a strong correspondence between cortical and peripheral ß activity, demonstrating the cortical origin of peripheral ß and opening the pathway for a new generation of neural interfaces.

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

Motor units convert the last neural code of movement into muscle forces. The classic view of motor unit control is that the central nervous system sends common synaptic inputs to motoneuron pools and that motoneurons respond in an orderly fashion dictated by the size principle. This view however is in contrast with the large number of dimensions observed in motor cortex which may allow individual and flexible control of motor units. Evidence for flexible control of motor units may be obtained by tracking motor units longitudinally during 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.SIGNIFICANCE STATEMENT:With a new non-invasive high-density electromyographic framework we show the activity of motor unit ensembles in macaques during voluntary contractions. The discharge characteristics of brachioradialis motor units revealed a relatively fixed recruitment order and discharge characteristics across days and rate of force developments. These results were further confirmed through invasive axonal stimulation and recordings of intramuscular electromyographic activity from 16 arm muscles. The study shows for the first time the feasibility of longitudinal non-invasive motor unit interfacing and tracking of the same motor units in non-human primates.

Beta inputs to motor neurons do not directly contribute to volitional force modulation.

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. KEY POINTS: It has been previously proposed that beta (13-30 Hz) common inputs to a motor neuron pool may have a non-linear effect in voluntary force control. The needed strength of beta oscillations to modulate forces has not been analysed yet. Based on computer simulations, we show that sustained beta inputs to a spinal motoneuron pool at physiologically reported levels have minimal effect on force. Levels of sustained beta rhythmic activity that can cause a significant change in force are not compatible with experimental observations of intramuscular coherence in human skeletal muscles.

Common synaptic input, synergies and size principle: Control of spinal motor neurons for movement generation.

Understanding how movement is controlled by the CNS remains a major challenge, with ongoing debate about basic features underlying this control. In current established views, the concepts of motor neuron recruitment order, common synaptic input to motor neurons and muscle synergies are usually addressed separately and therefore seen as independent features of motor control. In this review, we analyse the body of literature in a broader perspective and we identify a unified approach to explain apparently divergent observations at different scales of motor control. Specifically, we propose a new conceptual framework of the neural control of movement, which merges the concept of common input to motor neurons and modular control, together with the constraints imposed by recruitment order. This framework is based on the following assumptions: (1) motor neurons are grouped into functional groups (clusters) based on the common inputs they receive; (2) clusters may significantly differ from the classical definition of motor neuron pools, such that they may span across muscles and/or involve only a portion of a muscle; (3) clusters represent functional modules used by the CNS to reduce the dimensionality of the control; and (4) selective volitional control of single motor neurons within a cluster receiving common inputs cannot be achieved. Here, we discuss this framework and its underlying theoretical and experimental evidence.

Motor potentials evoked by transcranial magnetic stimulation: interpreting a simple measure of a complex system.

Transcranial magnetic stimulation (TMS) is a non-invasive technique that is increasingly used to study the human brain. One of the principal outcome measures is the motor-evoked potential (MEP) elicited in a muscle following TMS over the primary motor cortex (M1), where it is used to estimate changes in corticospinal excitability. However, multiple elements play a role in MEP generation, so even apparently simple measures such as peak-to-peak amplitude have a complex interpretation. Here, we summarize what is currently known regarding the neural pathways and circuits that contribute to the MEP and discuss the factors that should be considered when interpreting MEP amplitude measured at rest in the context of motor processing and patients with neurological conditions. In the last part of this work, we also discuss how emerging technological approaches can be combined with TMS to improve our understanding of neural substrates that can influence MEPs. Overall, this review aims to highlight the capabilities and limitations of TMS that are important to recognize when attempting to disentangle sources that contribute to the physiological state-related changes in corticomotor excitability.

Standard intensities of transcranial alternating current stimulation over the motor cortex do not entrain corticospinal inputs to motor neurons.

Transcranial alternating current stimulation (TACS) is commonly used to synchronize a cortical area and its outputs to the stimulus waveform, but gathering evidence for this based on brain recordings in humans is challenging. The corticospinal tract transmits beta oscillations (∼21 Hz) from the 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 the motor cortex. Here, we assessed whether 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 the 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 1 mA) was delivered over the motor cortex at 21 Hz (beta stimulation), or at 7 Hz or 40 Hz (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 1 mA TACS over the motor cortex given at beta frequencies does not entrain corticospinal activity. KEY POINTS: Transcranial alternating current stimulation (TACS) is commonly used to entrain the communication between brain regions. It is challenging to find direct evidence supporting TACS-driven neural entrainment due to the technical difficulties in recording brain activity during stimulation. Computational simulations of motor neuron pools receiving common inputs in the beta (∼21 Hz) band indicate that motor neurons are highly sensitive to corticospinal beta entrainment. Motor unit activity from human muscles does not support TACS-driven corticospinal entrainment.

EEG responses induced by cerebellar TMS at rest and during visuomotor adaptation.

BACKGROUND: Connections between the cerebellum and the cortex play a critical role in learning and executing complex behaviours. Dual-coil transcranial magnetic stimulation (TMS) can be used non-invasively to probe connectivity changes between the lateral cerebellum and motor cortex (M1) using the motor evoked potential as an outcome measure (cerebellar-brain inhibition, CBI). However, it gives no information about cerebellar connections to other parts of cortex. OBJECTIVES: We used electroencephalography (EEG) to investigate whether it was possible to detect activity evoked in any areas of cortex by single-pulse TMS of the cerebellum (cerebellar TMS evoked potentials, cbTEPs). A second experiment tested if these responses were influenced by the performance of a cerebellar-dependent motor learning paradigm. METHODS: In the first series of experiments, TMS was applied over either the right or left cerebellar cortex, and scalp EEG was recorded simultaneously. Control conditions that mimicked auditory and somatosensory inputs associated with cerebellar TMS were included to identify responses due to non-cerebellar sensory stimulation. We conducted a follow-up experiment that evaluated whether cbTEPs are behaviourally sensitive by assessing individuals before and after learning a visuomotor reach adaptation task. RESULTS: A TMS pulse over the lateral cerebellum evoked EEG responses that could be distinguished from those caused by auditory and sensory artefacts. Significant positive (P80) and negative peaks (N110) over the contralateral frontal cerebral area were identified with a mirrored scalp distribution after left vs. right cerebellar stimulation. The P80 and N110 peaks were replicated in the cerebellar motor learning experiment and changed amplitude at different stages of learning. The change in amplitude of the P80 peak was associated with the degree of learning that individuals retained following adaptation. Due to overlap with sensory responses, the N110 should be interpreted with caution. CONCLUSIONS: Cerebral potentials evoked by TMS of the lateral cerebellum provide a neurophysiological probe of cerebellar function that complements the existing CBI method. They may provide novel insight into mechanisms of visuomotor adaptation and other cognitive processes.

Reply to: "Reflecting the causes of variability of EEG responses elicited by cerebellar TMS".

In their commentary on our recently published paper about electroencephalographic responses induced by cerebellar transcranial magnetic stimulation (Fong et al., 2023), Gassmann and colleagues (Gassmann et al., 2023b) try to explain the differences between our results and their own previous work on the same topic. We agree with them that many of the differences arise from our use of a different magnetic stimulation coil. However, two unresolved questions remain. (1) Which method is most likely to achieve optimal activation of cerebellar output? (2) To what extent are the evoked cerebellar responses contaminated by concomitant sensory input? We highlight the role of careful experimental design and of combining electrophysiological and behavioural data to obtain reliable TMS-EEG data.

RECENT ADVANCES IN INSTRUMENTAL APPROACHES TO TIME-OF-FLIGHT MASS SPECTROMETRY.

Time-of-flight mass spectrometry (TOFMS) is one of the simplest and most powerful approaches for mass spectrometry. Realization of the advantages inherent in TOFMS requires innovation in the theory and practice of the technique. Instrumental developments, in turn, create new capabilities that enable applications in chemical measurement. This review focuses on the recent advances in TOFMS instrumentation. New strategies for ion acceleration, multiplexed detection, miniaturized TOFMS instruments, approaches to extend the length of ion flight, and novel ion detection technologies are reviewed. Techniques that change the basic paradigm of TOFMS by measuring m/z based on ion flight distance are considered, as are applications at the frontiers of instrumental performance. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Towards a mechanistic approach for the development of non-invasive brain-computer interfaces for motor rehabilitation.

Brain-computer interfaces (BCIs) designed for motor rehabilitation use brain signals associated with motor-processing states to guide neuroplastic changes in a state-dependent manner. These technologies are uniquely positioned to induce targeted and functionally relevant plastic changes in the human motor nervous system. However, while several studies have shown that BCI-based neuromodulation interventions may improve motor function in patients with lesions in the central nervous system, the neurophysiological structures and processes targeted with the BCI interventions have not been identified. In this review, we first summarize current knowledge of the changes in the central nervous system associated with learning new motor skills. Then, we propose a classification of current BCI paradigms for plasticity induction and motor rehabilitation based on the expected neural plastic changes promoted. This classification proposes four paradigms based on two criteria: the plasticity induction methods and the brain states targeted. The existing evidence regarding the brain circuits and processes targeted with these different BCIs is discussed in detail. The proposed classification aims to serve as a starting point for future studies trying to elucidate the underlying plastic changes following BCI interventions.

Corticospinal excitability modulation by pairing peripheral nerve stimulation with cortical states of movement initiation.

KEY POINTS: We compare the effects on corticospinal excitability of repeatedly delivering peripheral nerve stimulation at three time points (-30 ms, 0 ms, +50 ms) relative to muscle onset in a cue-guided task. Plastic changes in excitability are only observed when stimuli are delivered immediately before the time when muscles activate, while stimuli delivered at muscle onset or shortly later (0, +50 ms) have no effect. Plastic effects are abolished if there is ongoing volitional electromyogram activity in the muscles prior to the onset of the phasic contraction. The plastic effects induced by timing peripheral stimulation relative to electromyographic markers of muscle activation are as effective as those that occur if stimulation is timed relative to electroencephalographic markers of motor cortical activation. We provide a simple alternative protocol to induce plasticity in people in whom electroencephalogram recording is difficult. ABSTRACT: Plastic changes in corticospinal excitability (CSE) and motor function can be induced in a targeted and long-term manner if afferent volleys evoked by peripheral nerve stimulation are repeatedly associated with the peak of premovement brain activity assessed with an electroencephalogram (EEG). The present study investigated whether other factors might also characterize this optimal brain state for plasticity induction. In healthy human volunteers (n = 24), we found that the same reliable changes in CSE can be induced by timing peripheral afferent stimulation relative to the onset of electromyogram (EMG) activity rather than using the EEG peak. Specifically, we observed an increase in CSE when peripheral stimulation activated the cortex just before movement initiation. By contrast, there was no effect on CSE if the afferent input reached the cortex at the same time or after EMG onset, consistent with the idea that the temporal order of synaptic activation from afferent input and voluntary movement is important for production of plasticity. Finally, in 14 volunteers, we found that background voluntary muscle activity prior to movement also abolished the effect on CSE. One possible explanation is that the intervention strengthens synapses that are inactive at rest but change their activity in anticipation of movement, and that the intervention fails when the synapses are tonically active during background EMG activity. Overall, we demonstrate that, in individuals with voluntary control of muscles targeted by our intervention, EMG signals are a suitable alternative to an EEG for inducing plasticity by coupling movement-related brain states with peripheral afferent input.

The phase difference between neural drives to antagonist muscles in essential tremor is associated with the relative strength of supraspinal and afferent input.

The pathophysiology of essential tremor (ET), the most common movement disorder, is not fully understood. We investigated which factors determine the variability in the phase difference between neural drives to antagonist muscles, a long-standing observation yet unexplained. We used a computational model to simulate the effects of different levels of voluntary and tremulous synaptic input to antagonistic motoneuron pools on the tremor. We compared these simulations to data from 11 human ET patients. In both analyses, the neural drive to muscle was represented as the pooled spike trains of several motor units, which provides an accurate representation of the common synaptic input to motoneurons. The simulations showed that, for each voluntary input level, the phase difference between neural drives to antagonist muscles is determined by the relative strength of the supraspinal tremor input to the motoneuron pools. In addition, when the supraspinal tremor input to one muscle was weak or absent, Ia afferents provided significant common tremor input due to passive stretch. The simulations predicted that without a voluntary drive (rest tremor) the neural drives would be more likely in phase, while a concurrent voluntary input (postural tremor) would lead more frequently to an out-of-phase pattern. The experimental results matched these predictions, showing a significant change in phase difference between postural and rest tremor. They also indicated that the common tremor input is always shared by the antagonistic motoneuron pools, in agreement with the simulations. Our results highlight that the interplay between supraspinal input and spinal afferents is relevant for tremor generation.

Influence of common synaptic input to motor neurons on the neural drive to muscle in essential tremor.

Tremor in essential tremor (ET) is generated by pathological oscillations at 4-12 Hz, likely originating at cerebello-thalamo-cortical pathways. However, the way in which tremor is represented in the output of the spinal cord circuitries is largely unknown because of the difficulties in identifying the behavior of individual motor units from tremulous muscles. By using novel methods for the decomposition of multichannel surface EMG, we provide a systematic analysis of the discharge properties of motor units in nine ET patients, with concurrent recordings of EEG activity. This analysis allowed us to infer the contribution of common synaptic inputs to motor neurons in ET. Motor unit short-term synchronization was significantly greater in ET patients than in healthy subjects. Furthermore, the strong association between the degree of synchronization and the peak in coherence between motor unit spike trains at the tremor frequency indicated that the high synchronization levels were generated mainly by common synaptic inputs specifically at the tremor frequency. The coherence between EEG and motor unit spike trains demonstrated the presence of common cortical input to the motor neurons at the tremor frequency. Nonetheless, the strength of this input was uncorrelated to the net common synaptic input at the tremor frequency, suggesting a contribution of spinal afferents or secondary supraspinal pathways in projecting common input at the tremor frequency. These results provide the first systematic analysis of the neural drive to the muscle in ET and elucidate some of its characteristics that determine pathological tremulous muscle activity.

Excitation of natural spinal reflex loops in the sensory-motor control of hand prostheses.

Sensory feedback for prosthesis control is typically based on encoding sensory information in specific types of sensory stimuli that the users interpret to adjust the control of the prosthesis. However, in physiological conditions, the afferent feedback received from peripheral nerves is not only processed consciously but also modulates spinal reflex loops that contribute to the neural information driving muscles. Spinal pathways are relevant for sensory-motor integration, but they are commonly not leveraged for prosthesis control. We propose an approach to improve sensory-motor integration for prosthesis control based on modulating the excitability of spinal circuits through the vibration of tendons in a closed loop with muscle activity. We measured muscle signals in healthy participants and amputees during different motor tasks, and we closed the loop by applying vibration on tendons connected to the muscles, which modulated the excitability of motor neurons. The control signals to the prosthesis were thus the combination of voluntary control and additional spinal reflex inputs induced by tendon vibration. Results showed that closed-loop tendon vibration was able to modulate the neural drive to the muscles. When closed-loop tendon vibration was used, participants could achieve similar or better control performance in interfaces using muscle activation than without stimulation. Stimulation could even improve prosthetic grasping in amputees. Overall, our results indicate that closed-loop tendon vibration can integrate spinal reflex pathways in the myocontrol system and open the possibility of incorporating natural feedback loops in prosthesis control.

High Performance Wearable Ultrasound as a Human-Machine Interface for Wrist and Hand Kinematic Tracking.

OBJECTIVE: Non-invasive human machine interfaces (HMIs) have high potential in medical, entertainment, and industrial applications. Traditionally, surface electromyography (sEMG) has been used to track muscular activity and infer motor intention. Ultrasound (US) has received increasing attention as an alternative to sEMG-based HMIs. Here, we developed a portable US armband system with 24 channels and a multiple receiver approach, and compared it with existing sEMG- and US-based HMIs on movement intention decoding. METHODS: US and motion capture data was recorded while participants performed wrist and hand movements of four degrees of freedom (DoFs) and their combinations. A linear regression model was used to offline predict hand kinematics from the US (or sEMG, for comparison) features. The method was further validated in real-time for a 3-DoF target reaching task. RESULTS: In the offline analysis, the wearable US system achieved an average [Formula: see text] of 0.94 in the prediction of four DoFs of the wrist and hand while sEMG reached a performance of [Formula: see text]= 0.60. In online control, the participants achieved an average 93% completion rate of the targets. CONCLUSION: When tailored for HMIs, the proposed US A-mode system and processing pipeline can successfully regress hand kinematics both in offline and online settings with performances comparable or superior to previously published interfaces. SIGNIFICANCE: Wearable US technology may provide a new generation of HMIs that use muscular deformation to estimate limb movements. The wearable US system allowed for robust proportional and simultaneous control over multiple DoFs in both offline and online settings.

Brain Analysis with a Complex Network Approach in Stroke Patients Based on Electroencephalography: A Systematic Review and Meta-Analysis.

BACKGROUND AND PURPOSE: Brain function can be networked, and these networks typically present drastic changes after having suffered a stroke. The objective of this systematic review was to compare EEG-related outcomes in adults with stroke and healthy individuals with a complex network approach. METHODS: The literature search was performed in the electronic databases PubMed, Cochrane and ScienceDirect from their inception until October 2021. RESULTS: Ten studies were selected, nine of which were cohort studies. Five of them were of good quality, whereas four were of fair quality. Six studies showed a low risk of bias, whereas the other three studies presented a moderate risk of bias. In the network analysis, different parameters such as the path length, cluster coefficient, small-world index, cohesion and functional connection were used. The effect size was small and not significant in favor of the group of healthy subjects (Hedges'g = 0.189 [-0.714, 1.093], Z = 0.582, p = 0.592). CONCLUSIONS: The systematic review found that there are structural differences between the brain network of post-stroke patients and healthy individuals as well as similarities. However, there was no specific distribution network to allows us to differentiate them and, therefore, more specialized and integrated studies are needed.

Construction and Validation of an Occupational Risks Scale for Intra-hospital Nursing Staff.

Objective: To construct and evaluate initial validity indicators of an instrument on occupational risks for hospital nursing staff. Methods: A methodological study was conducted in four Chilean hospitals. The study was carried out in three stages: (i) integrative literature review on risk assessment instruments for nursing; (ii) descriptive qualitative study on 113 health professionals to identify their work conditions and experiences regarding occupational risks and construct three instruments proposals for nursing managers, clinical nurses, and technicians; and (iii) validity and reliability study of the three instruments in 503 nurses and nursing technicians. To collect the data from the qualitative study, individual interviews, focal groups, and non-participant observation were conducted. The data were analyzed thematically into predefined risk categories. Content validation was performed through expert judgment, and exploratory factor analysis of principal components was conducted for the preliminary construct validity study. Cronbach's alpha was used as an indicator of internal consistency. Results: A total of 128 items were identified, distributed across 11 categories and 25 subcategories of occupational risks for the three instruments derived from the original proposal. After expert validation, pilot study, and instrument administration, Cronbach's alpha values between 0.88 and 0.93 were obtained. Exploratory factor analysis distinguished eight to eleven components, with unsatisfactory goodness-of-fit indicators. Conclusion: The instruments demonstrated good parameters of content validity and reliability, although their construct validity needs further improvement.

Accurate Identification of Motoneuron Discharges from Ultrasound Images Across the Full Muscle Cross-Section.

OBJECTIVE: Non-invasive identification of motoneuron (MN) activity commonly uses electromyography (EMG). However, surface EMG (sEMG) detects only superficial sources, at less than approximately 10-mm depth. Intramuscular EMG can detect deep sources, but it is limited to sources within a few mm of the detection site. Conversely, ultrasound (US) images have high spatial resolution across the whole muscle cross-section. The activity of MNs can be extracted from US images due to the movements that MN activation generates in the innervated muscle fibers. Current US-based decomposition methods can accurately identify the location and average twitch induced by MN activity. However, they cannot accurately detect MN discharge times. METHODS: Here, we present a method based on the convolutive blind source separation of US images to estimate MN discharge times with high accuracy. The method was validated across 10 participants using concomitant sEMG decomposition as the ground truth. RESULTS: 140 unique MN spike trains were identified from US images, with a rate of agreement (RoA) with sEMG decomposition of 87.4 ± 10.3%. Over 50% of these MN spike trains had a RoA greater than 90%. Furthermore, with US, we identified additional MUs well beyond the sEMG detection volume, at up to >30 mm below the skin. CONCLUSION: The proposed method can identify discharges of MNs innervating muscle fibers in a large range of depths within the muscle from US images. SIGNIFICANCE: The proposed methodology can non-invasively interface with the outer layers of the central nervous system innervating muscles across the full cross-section.

Non-Linearity in Motor Unit Velocity Twitch Dynamics: Implications for Ultrafast Ultrasound Source Separation.

Ultrasound (US) muscle image series can be used for peripheral human-machine interfacing based on global features, or even on the decomposition of US images into the contributions of individual motor units (MUs). With respect to state-of-the-art surface electromyography (sEMG), US provides higher spatial resolution and deeper penetration depth. However, the accuracy of current methods for direct US decomposition, even at low forces, is relatively poor. These methods are based on linear mathematical models of the contributions of MUs to US images. Here, we test the hypothesis of linearity by comparing the average velocity twitch profiles of MUs when varying the number of other concomitantly active units. We observe that the velocity twitch profile has a decreasing peak-to-peak amplitude when tracking the same target motor unit at progressively increasing contraction force levels, thus with an increasing number of concomitantly active units. This observation indicates non-linear factors in the generation model. Furthermore, we directly studied the impact of one MU on a neighboring MU, finding that the effect of one source on the other is not symmetrical and may be related to unit size. We conclude that a linear approximation is partly limiting the decomposition methods to decompose full velocity twitch trains from velocity images, highlighting the need for more advanced models and methods for US decomposition than those currently employed.

The control and training of single motor units in isometric tasks are constrained by a common input signal.

Recent developments in neural interfaces enable the real-time and non-invasive tracking of motor neuron spiking activity. Such novel interfaces could provide a promising basis for human motor augmentation by extracting potentially high-dimensional control signals directly from the human nervous system. However, it is unclear how flexibly humans can control the activity of individual motor neurons to effectively increase the number of degrees of freedom available to coordinate multiple effectors simultaneously. Here, we provided human subjects (N = 7) with real-time feedback on the discharge patterns of pairs of motor units (MUs) innervating a single muscle (tibialis anterior) and encouraged them to independently control the MUs by tracking targets in a 2D space. Subjects learned control strategies to achieve the target-tracking task for various combinations of MUs. These strategies rarely corresponded to a volitional control of independent input signals to individual MUs during the onset of neural activity. Conversely, MU activation was consistent with a common input to the MU pair, while individual activation of the MUs in the pair was predominantly achieved by alterations in de-recruitment order that could be explained by history-dependent changes in motor neuron excitability. These results suggest that flexible MU recruitment based on independent synaptic inputs to single MUs is unlikely, although de-recruitment might reflect varying inputs or modulations in the neuron's intrinsic excitability.