Larger and denser: an optimal design for surface grids of EMG electrodes to identify greater and more representative samples of motor units

The spinal motor neurons are the only neural cells whose individual activity can be non-invasively identified. This is usually done using grids of surface electromyographic (EMG) electrodes and source separation algorithms; an approach called EMG decomposition. In this study, we combined computational and experimental analyses to assess how the design parameters of grids of electrodes influence the number and the properties of the identified motor units. We first computed the percentage of motor units that could be theoretically discriminated within a pool of 200 simulated motor units when decomposing EMG signals recorded with grids of various sizes and interelectrode distances (IED). Increasing the density, the number of electrodes, and the size of the grids, increased the number of motor units that our decomposition algorithm could theoretically discriminate, i.e., up to 83.5% of the simulated pool (range across conditions: 30.5-83.5%). We then identified motor units from experimental EMG signals recorded in six participants with grids of various sizes (range: 2-36 cm2) and IED (range: 4-16 mm). The configuration with the largest number of electrodes and the shortest IED maximized the number of identified motor units (56±14; range: 39-79) and the percentage of early recruited motor units within these samples (29±14%). Finally, the number of identified motor units further increased with a prototyped grid of 256 electrodes and an IED of 2 mm. Taken together, our results showed that larger and denser surface grids of electrodes allow to identify a more representative pool of motor units than currently reported in experimental studies.Significance StatementThe application of source separation methods to multi-channel EMG signals recorded with grids of electrodes enables users to accurately identify the activity of individual motor units. However, the design parameters of these grids have never been discussed. They are usually arbitrarily fixed, often based on commercial availability. Here, we showed that using larger and denser grids of electrodes than conventionally proposed drastically increases the number of identified motor units. The samples of identified units are more balanced between early- and late-recruited motor units. Thus, these grids provide a more representative sampling of the active motor unit population. Gathering large datasets of motor units using large and dense grids will impact the study of motor control, neuromuscular modelling, and human-machine interfacing

Neuromuscular control of wingbeat kinematics in Anna's hummingbirds (Calypte anna)

Hummingbirds can maintain the highest wingbeat frequencies of any flying vertebrate – a feat accomplished by the large pectoral muscles that power the wing strokes. An unusual feature of these muscles is that they are activated by one or a few spikes per cycle as revealed by electromyogram recordings (EMGs). The relatively simple nature of this activation pattern provides an opportunity to understand how motor units are recruited to modulate limb kinematics. Hummingbirds made to fly in low-density air responded by moderately increasing wingbeat frequency and substantially increasing the wing stroke amplitude as compared with flight in normal air. There was little change in the number of spikes per EMG burst in the pectoralis major muscle between flight in normal and low-density heliox (mean=1.4 spikes cycle^(–1)). However the spike amplitude, which we take to be an indication of the number of active motor units, increased in concert with the wing stroke amplitude, 1.7 times the value in air. We also challenged the hummingbirds using transient load lifting to elicit maximum burst performance. During maximum load lifting, both wing stroke amplitude and wingbeat frequency increased substantially above those values during hovering flight. The number of spikes per EMG burst increased to a mean of 3.3 per cycle, and the maximum spike amplitude increased to approximately 1.6 times those values during flight in heliox. These results suggest that hummingbirds recruit additional motor units (spatial recruitment) to regulate wing stroke amplitude but that temporal recruitment is also required to maintain maximum stroke amplitude at the highest wingbeat frequencies

CONTROL OF MOTOR UNITS DURING VOLUNTARY FORCE-PRODUCTION: IMPLICATIONS FOR EXERCISE

We have recently developed a technology that enables studies of the firing properties of a large set (typically 30 to 40) of concurrently active motor units during isometric voluntary contractions ranging from low force levels to maximal voluntary contractions (MVC). With this technology we have executed studies to investigate the behavior of the firing rates of motor units as a function of their recruitment properties during contractions at various force levels. We found that the firing rates have a hierarchical structure wherein the firing rate value of motor units is inversely related to their recruitment threshold, with earlier recruited motor units having greater firing rates at any time and any force level during a contraction. This relationship does not support the opposite notion that has been generally held for the past five decades. Knowing the structure of the firing behavior of motor units during voluntary contractions provides guidance for understanding the performance of muscles during exercise and sports

The new technique for accurate estimation of the spinal cord circuitry:recording reflex responses of large motor unit populations

We propose and validate a non-invasive method that enables accurate detection of the discharge times of a relatively large number of motor units during excitatory and inhibitory reflex stimulations. HDsEMG and intramuscular EMG (iEMG) were recorded from the tibialis anterior muscle during ankle dorsiflexions performed at 5%, 10%, and 20% of the maximum voluntary contraction (MVC) force, in 9 healthy subjects. The tibial nerve (inhibitory reflex) and the peroneal nerve (excitatory reflex) were stimulated with constant current stimuli. In total, 416 motor units were identified from the automatic decomposition of the HDsEMG. The iEMG was decomposed using a state-of-the-art decomposition tool and provided 84 motor units (average of two recording sites). The reflex responses of the detected motor units were analyzed using the peri-stimulus time histogram (PSTH) and the peri-stimulus frequencygram (PSF). The reflex responses of the common motor units identified concurrently from the HDsEMG and the iEMG signals showed an average disagreement (the difference between number of observed spikes in each bin relative to the mean) of 8.2±2.2% (5% MVC), 6.8±1.0% (10% MVC), and 7.5±2.2% (20% MVC), for reflex inhibition, and 6.5±4.1%, 12.0±1.8%, 13.9±2.4%, for reflex excitation. There was no significant difference between the characteristics of the reflex responses, such as latency, amplitude and duration, for the motor units identified by both techniques. Finally, reflex responses could be identified at higher force (four of the nine subjects performed contraction up to 50% MVC) using HDsEMG but not iEMG, because of the difficulty in decomposing the iEMG at high forces. In conclusion, single motor unit reflex responses can be estimated accurately and non-invasively in relatively large populations of motor units using HDsEMG. This non-invasive approach may enable a more thorough investigation of the synaptic input distribution on active motor units at various force levels

Oscillations in Neural Drive and Age-related Reductions in Force Steadiness with a Cognitive Challenge

A cognitive challenge when imposed during a low-force isometric contraction will exacerbate sex- and age-related decreases in force steadiness, but the mechanism is not known. We determined the role of oscillations in the common synaptic input to motor units on force steadiness during a muscle contraction with a concurrent cognitive challenge. Forty-nine young adults (19–30 yr; 25 women, 24 men) and 36 old adults (60–85 yr; 19 women, 17 men) performed a cognitive challenge (counting backward by 13) during an isometric elbow flexion task at 5% of maximal voluntary contraction. Single-motor units were decomposed from high-density surface EMG recordings. For a subgroup of participants, motor units were matched during control and cognitive challenge trials, so the same motor unit was analyzed across conditions. Reduced force steadiness was associated with greater oscillations in the synaptic input to motor units during both control and cognitive challenge trials (r = 0.45–0.47, P \u3c 0.01). Old adults and young women showed greater oscillations in the common synaptic input to motor units and decreased force steadiness when the cognitive challenge was imposed, but young men showed no change across conditions (session × age × sex, P \u3c 0.05). Oscillations in the common synaptic input to motor units is a potential mechanism for altered force steadiness when a cognitive challenge is imposed during low-force contractions in young women and old adults

High-density magnetomyography is superior over surface electromyography for the decomposition of motor units: a simulation study

Studying motor units (MUs) is essential for understanding motor control, the detection of neuromuscular disorders and the control of human-machine interfaces. Individual motor unit firings are currently identified in vivo by decomposing electromyographic (EMG) signals. Due to our body's electric properties, individual motor units can only be separated to a limited extent with surface EMG. Unlike electrical signals, magnetic fields pass through biological tissues without distortion. This physical property and emerging technology of quantum sensors make magnetomyography (MMG) a highly promising methodology. However, the full potential of MMG to study neuromuscular physiology has not yet been explored. In this work, we perform in silico trials that combine a biophysical model of EMG and MMG with state-of-the-art algorithms for the decomposition of motor units. This allows the prediction of an upper-bound for the motor unit decomposition accuracy. It is shown that non-invasive MMG is superior over surface EMG for the robust identification of the discharge patterns of individual motor units. Decomposing MMG instead of EMG increased the number of identifiable motor units by 71%. Notably, MMG exhibits a less pronounced bias to detect superficial motor units. The presented simulations provide insights into methods to study the neuromuscular system non-invasively and in vivo that would not be easily feasible by other means. Hence, this study provides guidance for the development of novel biomedical technologies

High-density magnetomyography is superior to high-density surface electromyography for motor unit decomposition: a simulation study

Objective. Studying motor units is essential for understanding motor control, the detection of neuromuscular disorders and the control of human-machine interfaces. Individual motor unit firings are currently identified in vivo by decomposing electromyographic (EMG) signals. Due to our body’s properties and anatomy, individual motor units can only be separated to a limited extent with surface EMG. Unlike electrical signals, magnetic fields do not interact with human tissues. This physical property and the emerging technology of quantum sensors make magnetomyography (MMG) a highly promising methodology. However, the full potential of MMG to study neuromuscular physiology has not yet been explored. Approach. In this work, we perform in silico trials that combine a biophysical model of EMG and MMG with state-of-the-art algorithms for the decomposition of motor units. This allows the prediction of an upper-bound for the motor unit decomposition accuracy. Main results. It is shown that non-invasive high-density MMG data is superior over comparable high-density surface EMG data for the robust identification of the discharge patterns of individual motor units. Decomposing MMG instead of EMG increased the number of identifiable motor units by 76%. Notably, MMG exhibits a less pronounced bias to detect superficial motor units. Significance. The presented simulations provide insights into methods to study the neuromuscular system non-invasively and in vivo that would not be easily feasible by other means. Hence, this study provides guidance for the development of novel biomedical technologies

Influence of ischemia on the discharge rate in motor units during a sustained submaximal contraction

Motor unit discharge patterns were observed under ischemic and non-ischemic conditions in the tibialis anterior during two sessions approximately 48 hours apart. Ten subjects completed three 5-second maximum voluntary contractions [MVCs) followed by a prolonged, submaximal, isometric contraction to induce fatigue, and three additional MVCs. This fatigue trial was completed under both ischemic and non-ischemic conditions. For the ischemic condition, a pressure cuff was placed above the knee, inflated to 180 mmHg, and arterial occlusion verified via Doppler ultrasound. During the fatigue task, a constant force of 20% MVC was maintained until endurance time. Single motor unit activity was recorded with intramuscular fine wire electrodes. Endurance time during the ischemic fatigue task (3.71 ± 0.58 min) was significantly less than the non-ischemic fatigue task (9.11 ± 0.56 min). Both tasks showed a significant decline in motor unit discharge rate. There was greater variability in the discharge rate during ischemic compared to non-ischemic conditions. Time to minimum discharge rate was greater during ischemic conditions. Overall, ischemic conditions resulted in decreased endurance time, greater rate of decline in discharge rate, and greater variability in discharge rate of motor units.Kinesiology and Health Educatio