How many motor units is enough? An assessment of the influence of the number of motor units on firing rate calculations

The number of motor units included in calculations of mean firing rates varies widely in the literature. It is unknown how the number of decomposed motor units included in the calculation of firing rate per participant compares to the total number of active motor units in the muscle, and if this is different for males and females. Bootstrapped distributions and confidence intervals (CI) of mean motor unit firing rates decomposed from the tibialis anterior were used to represent the total number of active motor units for individual participants in trials from 20 to 100 % of maximal voluntary contraction. Bootstrapped distributions of mean firing rates were constructed using different numbers of motor units, from one to the maximum number for each participant, and compared to the CIs. A probability measure for each number of motor units involved in firing rate was calculated and then averaged across all individuals. Motor unit numbers required for similar levels of probability increased as contraction intensity increased (p < 0.001). Increased levels of probability also required higher numbers of motor units (p < 0.001). There was no effect of sex (p ≥ 0.97) for any comparison. This methodology should be repeated in other muscles, and aged populations.

Tutorial: Analysis of central and peripheral motor unit properties from decomposed High-Density surface EMG signals with openhdemg

High-Density surface Electromyography (HD-sEMG) is the most established technique for the non-invasive analysis of single motor unit (MU) activity in humans. It provides the possibility to study the central properties (e.g., discharge rate) of large populations of MUs by analysis of their firing pattern. Additionally, by spike-triggered averaging, peripheral properties such as MUs conduction velocity can be estimated over adjacent regions of the muscles and single MUs can be tracked across different recording sessions. In this tutorial, we guide the reader through the investigation of MUs properties from decomposed HD-sEMG recordings by providing both the theoretical knowledge and practical tools necessary to perform the analyses. The practical application of this tutorial is based on openhdemg, a free and open-source community-based framework for the automated analysis of MUs properties built on Python 3 and composed of different modules for HD-sEMG data handling, visualisation, editing, and analysis. openhdemg is interfaceable with most of the available recording software, equipment or decomposition techniques, and all the built-in functions are easily adaptable to different experimental needs. The framework also includes a graphical user interface which enables users with limited coding skills to perform a robust and reliable analysis of MUs properties without coding.

Selective vulnerability of motor neuron types and functional groups to degeneration in amyotrophic lateral sclerosis: review of the neurobiological mechanisms and functional correlates

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative condition characterised by a progressive loss of motor neurons controlling voluntary muscle activity. The disease manifests through a variety of motor dysfunctions related to the extent of damage and loss of neurons at different anatomical locations. Despite extensive research, it remains unclear why some motor neurons are especially susceptible to the disease, while others are affected less or even spared. In this article, we review the neurobiological mechanisms, neurochemical profiles, and morpho-functional characteristics of various motor neuron groups and types of motor units implicated in their differential exposure to degeneration. We discuss specific cell-autonomous (intrinsic) and extrinsic factors influencing the vulnerability gradient of motor units and motor neuron types to ALS, with their impact on disease manifestation, course, and prognosis, as revealed in preclinical and clinical studies. We consider the outstanding challenges and emerging opportunities for interpreting the phenotypic and mechanistic variability of the disease to identify targets for clinical interventions.

Spatial decomposition of ultrafast ultrasound images to identify motor unit activity - A comparative study with intramuscular and surface EMG

The smallest voluntarily controlled structure of the human body is the motor unit (MU), comprised of a motoneuron and its innervated fibres. MUs have been investigated in neurophysiology research and clinical applications, primarily using electromyographic (EMG) techniques. Nonetheless, EMG (both surface and intramuscular) has a limited detection volume. A recent alternative approach to detect MUs is ultrafast ultrasound (UUS) imaging. The possibility of identifying MU activity from UUS has been shown by blind source separation (BSS) of UUS images, using optimal separation spatial filters. However, this approach has yet to be fully compared with EMG techniques for a large population of unique MU spike trains. Here we identify individual MU activity in UUS images using the BSS method for 401 MU spike trains from eleven participants based on concurrent recordings of either surface or intramuscular EMG from forces up to 30% of the maximum voluntary contraction (MVC) force. We assessed the BSS method's ability to identify MU spike trains from direct comparison with the EMG-derived spike trains as well as twitch areas and temporal profiles from comparison with the spike-triggered-averaged UUS images when using the EMG-derived spikes as triggers. We found a moderate rate of correctly identified spikes (53.0 ± 16.0%) with respect to the EMG-identified firings. However, the MU twitch areas and temporal profiles could still be identified accurately, including at 30% MVC force. These results suggest that the current BSS methods for UUS can accurately identify the location and average twitch of a large pool of MUs in UUS images, providing potential avenues for studying neuromechanics from a large cross-section of the muscle. On the other hand, more advanced methods are needed to address the convolutive and partly non-linear summation of velocities for recovering the full spike trains.

Comparison of decomposition algorithms for identification of single motor units in ultrafast ultrasound image sequences of low force voluntary skeletal muscle contractions

OBJECTIVE

In this study, the aim was to compare the performance of four spatiotemporal decomposition algorithms (stICA, stJADE, stSOBI, and sPCA) and parameters for identifying single motor units in human skeletal muscle under voluntary isometric contractions in ultrafast ultrasound image sequences as an extension of a previous study. The performance was quantified using two measures: (1) the similarity of components' temporal characteristics against gold standard needle electromyography recordings and (2) the agreement of detected sets of components between the different algorithms.

RESULTS

We found that out of these four algorithms, no algorithm significantly improved the motor unit identification success compared to stICA using spatial information, which was the best together with stSOBI using either spatial or temporal information. Moreover, there was a strong agreement of detected sets of components between the different algorithms. However, stJADE (using temporal information) provided with complementary successful detections. These results suggest that the choice of decomposition algorithm is not critical, but there may be a methodological improvement potential to detect more motor units.

A new biological central pattern generator model and its relationship with the motor units

The central pattern generator (CPG) is a key neural-circuit component of the locomotion control system. Recently, numerous molecular and genetic approaches have been proposed for investigating the CPG mechanisms. The rhythm in the CPG locomotor circuits comes from the activity in the ipsilateral excitatory neurons whose output is controlled by inter-neuron inhibitory connections. Conventional models for simulating the CPG mechanism are complex Hodgkin-Huxley-type models. Inspired by biological investigations and the continuous-time Matsuoka model, we propose new integral-order and fractional-order CPG models, which consider time delays and synaptic interfaces. The phase diagrams exhibit limit cycles and periodic solutions, in agreement with the CPG biological characteristics. As well, the fractional-order model shows state transitions with order variations. In addition, we investigate the relationship between the CPG and the motor units through the construction of integral-order and fractional-order coupling models. Simulations of these coupling models show that the states generated by the three motor units are in accordance with the experimentally-obtained states in previous studies. The proposed models reveal that the CPG can regulate limb locomotion patterns through connection weights and synaptic interfaces. Moreover, in comparison to the integral-order models, the fractional-order ones appear to be more effective, and hence more suitable for describing the dynamics of the CPG biological system.

Maintenance of standing posture during multi-directional leaning demands the recruitment of task-specific motor units in the ankle plantarflexors

The purpose of this study is to investigate whether regional modulation of the ankle plantarflexors during standing was related to the recruitment of motor units associated with force direction. Fourteen participants performed a multi-directional leaning task in standing. Participants stood on a force platform and maintained their center of pressure in five different target directions. Motor unit firings were extracted by decomposition of high-density surface electromyograms recorded from the ankle plantarflexor muscles. The motor unit barycentre, defined as the weighted mean of the maximal average rectified values across columns and rows, was used to evaluate the medio-lateral and proximo-distal changes in the surface representation of single motor units across different leaning target directions. Using a motor unit tracking analysis, groups of motor units were identified as being common or unique across the target directions. The leaning directions had an effect on the spatial representations of motor units in the medial gastrocnemius and soleus (p < 0.05), but not in the lateral gastrocnemius (p > 0.05). Motor unit action potentials were represented in the medial and proximal aspects of the muscles during forward vs. lateral leans. Further analysis determined that the common motor units were found in similar spatial locations across the target directions, whereas newly recruited unique motor units were found in different spatial locations according to target direction (p < 0.05). The central nervous system may possess the ability to activate different groups of motor units according to task demands to meet the force-direction requirements of the leaning task.

Impact of stimulus duration on motor unit thresholds and alternation in compound muscle action potential scans

OBJECTIVE

To investigate the impact of stimulus duration on motor unit (MU) thresholds and alternation within compound muscle action potential (CMAP) scans.

METHODS

The stimulus duration (0.1, 0.2, 0.6, and 1.0 ms) in thenar CMAP scans and individual MUs of 14 healthy subjects was systematically varied. We quantified variability of individual MU's thresholds by relative spread (RS), MU thresholds by stimulus currents required to elicit target CMAPs of 5% (S5), 50% (S50) and 95% (S95) of the maximum CMAP, and relative range (RR) by 100*[S95-S5]/S50. We further assessed the strength-duration time constant (SDTC). Experimental observations were subsequently simulated to quantify alternation.

RESULTS

RS, unaffected by stimulus duration, was 1.65% averaged over all recordings. RR increased for longer stimulus duration (11.4% per ms, p < 0.001). SDTC shortened with higher target CMAPs (0.007 ms per 10% CMAP, p < 0.001). Experiments and simulations supported that this may underlie the increased RR. A short compared to long stimulus duration recruited relative more MUs at S50 (more alternation) than at the tails (less alternation).

CONCLUSIONS

The stimulus duration significantly affects MU threshold distribution and alternation within CMAP scans.

SIGNIFICANCE

Stimulation settings can be further optimized and their standardization is preferred when using CMAP scans for monitoring neuromuscular diseases.

Keep calm and hang on: EMG activation in the forelimb musculature of three-toed sloths (Bradypus variegatus)

Sloths exhibit below branch locomotion whereby their limbs are loaded in tension to support the body weight. Suspensory behaviors require both strength and fatigue resistance from the limb flexors; however, skeletal muscle mass of sloths is reduced compared with other arboreal mammals. Although suspensory locomotion demands that muscles are active to counteract the pull of gravity, it is possible that sloths minimize muscle activation and/or selectively recruit slow motor units to maintain support, thus indicating neuromuscular specializations to conserve energy. Electromyography (EMG) was evaluated in a sample of three-toed sloths (Bradypus variegatus; N=6) to test this hypothesis. EMG was recorded at 2000 Hz via fine-wire electrodes implanted into two suites of four muscles in the left forelimb while sloths performed suspensory hanging (SH), suspensory walking (SW) and vertical climbing (VC). All muscles were minimally active for SH. During SW and VC, sloths moved slowly (duty factor: 0.83) and activation patterns were consistent between behaviors; the flexors were activated early and for a large percentage of limb contact, whereas the extensors were activated for shorter burst durations on average and showed biphasic (contact and swing) activity. Muscle activities were maximal for the elbow flexors and lowest for the carpal/digital flexors, and overall activity was significantly greater for SW and VC compared with SH. Wavelet analysis indicated high mean EMG frequencies from the myoelectric intensity spectra coupled with low burst intensities for SH, although the opposite pattern occurred for SW and VC, with the shoulder flexors and elbow flexor, m. brachioradialis, having extremely low mean EMG frequencies that are consistent with recruitment of slow fibers. Collectively, these findings support the hypothesis and suggest that sloths may selectively recruit smaller, fast motor units for suspensory postures but have the ability to offset the cost of force production by recruitment of large, slow motor units during locomotion.

Modelling the electrical activity of skeletal muscle tissue using a multi-domain approach

Electromyography (EMG) can be used to study the behaviour of the motor neurons and thus provides insights into the physiology of the central nervous system. However, due to the high complexity of neuromuscular control, EMG signals are challenging to interpret. While the exact knowledge of the excitation patterns of a specific muscle within an in vivo experimental setting remains elusive, simulations allow to systematically investigate EMG signals in a controlled environment. Within this context, simulations can provide virtual EMG data, which, for example, can be used to validate and optimise signal analysis methods that aim to estimate the relationship between EMG signals and the output of motor neuron pools. However, since existing methods, which are employed to compute EMG signals, exhibit deficiencies with respect to the physical model itself as well as with respect to numerical aspects, we propose a novel homogenised continuum model that closely resolves the electro-physiological behaviour of skeletal muscle tissue. The proposed model is based on an extension of the well-established bidomain model and includes a biophysically detailed description of the electrical activity within the tissue, which is due to the depolarisation of the muscle fibre membranes. In contrast to all other published EMG models, which assume that the electrical potential field for each muscle fibre can be calculated independently, the proposed model assumes that the electrical potential in the muscle fibres is coupled to the electrical potential in the extracellular space. We show that the newly proposed model is able to simulate realistic EMG signals and demonstrate the potential to employ the predicted virtual EMG signal in order to evaluate the goodness of automated decomposition algorithms.

Motor unit firing rates of the first dorsal interosseous differ between male and female children aged 8-10 years

The purpose of this study was to examine possible differences in motor unit action potential amplitudes (MUAP_AMPS) and firing rates of the first dorsal interosseous (FDI) in male and female children aged 8-10 years. Eight male (mean ± SD, age = 8.8 ± 0.7 yrs; BMI = 16.5 ± 1.3 kg/m²) and eight female (age = 9.3 ± 0.9 yrs; BMI = 16.1 ± 1.5 kg/m²) children volunteered to complete isometric trapezoidal muscle actions of the first dorsal interosseous at 50% of maximal voluntary contraction (MVC). Electromyographic signals were decomposed to yield MUAP_AMPS and mean firing rates (MFR) at the targeted force. An exponential model was fitted to the MUAP_AMPS vs. recruitment threshold (RT) while linear models were fitted to the MFRs vs. RT relationships for each subject. Ultrasonography determined the muscle cross-sectional area (CSA) of the FDI. Independent samples t-tests were used to examine possible differences between the male and female children for MVC strength, CSA, and the coefficients from the MU relationships. There were no differences in MVC strength, CSA, or the MUAP_AMP vs. RT relationships between the male and female children (P < 0.05). Males, however, had greater MFRs of lower-threshold MUs as evident by significantly larger y-intercepts (P = 0.019) and more negative slopes (P = 0.004) from the MFR vs. RT relationships. Despite no differences in muscle strength, CSA, and MUAP_AMPS, differences in firing rates existed between male and female children aged 8-10 years. Neural mechanisms may primarily contribute to sex-related differences in firing rates.

Predicting wrist kinematics from motor unit discharge timings for the control of active prostheses

BACKGROUND

Current myoelectric control algorithms for active prostheses map time- and frequency-domain features of the interference EMG signal into prosthesis commands. With this approach, only a fraction of the available information content of the EMG is used and the resulting control fails to satisfy the majority of users. In this study, we predict joint angles of the three degrees of freedom of the wrist from motor unit discharge timings identified by decomposition of high-density surface EMG.

METHODS

We recorded wrist kinematics and high-density surface EMG signals from six able-bodied individuals and one patient with limb deficiency while they performed movements of three degrees of freedom of the wrist at three different speeds. We compared the performance of linear regression to predict the observed individual wrist joint angles from, either traditional time domain features of the interference EMG or from motor unit discharge timings (which we termed neural features) obtained by EMG decomposition. In addition, we propose and test a simple model-based dimensionality reduction, based on the physiological notion that the discharge timings of motor units are partly correlated.

RESULTS

The regression approach using neural features outperformed regression on classic global EMG features (average R² for neural features 0.77 and 0.64, for able-bodied subjects and patients, respectively; for time-domain features 0.70 and 0.52).

CONCLUSIONS

These results indicate that the use of neural information extracted from EMG decomposition can advance man-machine interfacing for prosthesis control.

Motor unit recruitment in myopathy: The myopathic EMG reconsidered

Motor unit recruitment is abnormal in myopathies. We have addressed this subject by recording motor unit potentials (MUPs) using a standard concentric needle electrode in tibialis anterior muscles of clinically normal strength in a group of patients with myopathy (15 with myositis and 4 with facioscapulohumeral muscular dystrophy Type 1). In each recording site, a minimal voluntary contraction was sought in order to activate only 2 MUPs. At least 5 pairs of MUPs were recorded in each muscle. We analysed the recruitment rate of the first activated MUP and the mean consecutive difference (MCD) of firing frequency between the individual MUPs of each recruited pair. Results were compared with 30 healthy control subjects. In myopathy the first recorded MUs fired at similar rates to controls (8.2 vs 8.0 Hz, respectively), but the MCD of the firing rate difference between the first two recruited MUPs was less than in controls (median difference 1.78 Hz vs median difference 2.47 Hz, p = 0.02). This change suggests increased lower motor neuron excitability as a functional adaptation, since muscle strength was normal in the studied muscles. These findings are consistent with spinal cord adaptation to the functional changes associated with myopathic muscle disease, although a primary muscle fibre feedback sensing mechanism could also be involved.

Crush injury to motor nerves in the G93A transgenic mouse model of amyotrophic lateral sclerosis promotes muscle reinnervation and survival of functionally intact nerve-muscle contacts

Selective survival of small motor nerve fibers and their neuromuscular contacts in the SOD1^G93A transgenic mouse model of amyotrophic lateral sclerosis (ALS) suggests that smaller regenerated nerve fibers are more able to sustain reformed nerve-muscle connections as functionally intact motor units (MUs). The sciatic nerve was crushed unilaterally in SOD1^G93A transgenic mice at 40 days of age and contractile forces of reinnervated muscles and their MUs were recorded at 90 days in order to determine the capacities of the nerves to regenerate and to form and retain functional neuromuscular connections. Reduced MU numbers in fast-twitch tibialis anterior, extensor digitorum longus and medial gastrocnemius muscles and the lesser reductions in slow-twitch soleus muscle of SOD1^G93A transgenic mice were reversed in reinnervated muscles: there were more reinnervated MUs and their contractile forces and the muscle forces and weights increased. In line with the contrasting ability of only small not large nerve fibers to sprout to form enlarged MUs in the SOD1^G93A transgenic mouse, the smaller regenerating nerve fibers formed enlarged MUs that were better able to survive. Because nerve fibers with and without muscle contacts were severed by the sciatic nerve crush injury, the conditioning lesion is untenable as the explanation for improved maintenance of reinnervated neuromuscular junctions. Elevated neurotrophic factor expression in axotomized motoneurons and/or denervated Schwann cells and the synapse withdrawal from axotomized motoneurons are other factors that, in addition to reduced size of nerve fibers reinnervating muscles, may account for increased survival and size of reinnervated MUs in ALS.

Physiology of the fasciculation potentials in amyotrophic lateral sclerosis: which motor units fasciculate?

We set out to study whether in amyotrophic lateral sclerosis (ALS) fasciculation potentials (FPs) arise from the most excitable motor units (MUs). We studied 70 patients with ALS and 18 subjects with benign fasciculation syndrome (BFS). Of the 56 eligible ALS patients, 31 had signs of reinnervation in the right first dorsal interosseous muscle selected for study, and 25 did not. Two needle electrodes were placed in different MUs in each studied muscle. We defined the most excitable MU as that first activated by minimal voluntary contraction. In muscles without reinnervation, the recording site with most frequent FPs had a higher probability of showing the first recruited MU (p < 0.001). No significant difference was found in other patients or in BFS subjects. In very early affected muscles, fasciculating MUs are the most likely to be recruited volitionally. This probably represents hyperexcitability at lower motor neuronal level.

Modifying motor unit territory placement in the Fuglevand model

The Fuglevand model is often used to address challenging questions in neurophysiology; however, there are elements of the neuromuscular system unaccounted for in the model. For instance, in some muscles, slow and fast motor units (MUs) tend to reside deep and superficially in the muscle, respectively, necessarily altering the development of surface electromyogram (EMG) power during activation. Thus, the objective of this study was to replace the randomized MU territory (MUT) placement algorithm in the Fuglevand model with an optimized method capable of reflecting these observations. To accomplish this, a weighting term was added to a previously developed optimization algorithm to encourage regionalized MUT placement. The weighting term consequently produced significantly different muscle fibre type content in the deep and superficial portions of the muscle. The relation between simulated EMG and muscle force was found to be significantly affected by regionalization. These changes were specifically a function of EMG power, as force was unaffected by regionalization. These findings suggest that parameterizing MUT regionalization will allow the model to produce a larger variety of EMG-force relations, as is observed physiologically, and could potentially simulate the loss of specific MU types as observed in ageing and clinical populations.

Motor unit number in a small facial muscle, dilator naris

A loss of functioning motor units underlies many neuromuscular disorders. The facial nerve innervates the muscles of facial expression, including nasal muscles, which also play an important role in the regulation of airflow resistance. It is difficult to accurately assess motor unit number in the facial muscles, because the muscles are difficult to activate in isolation. Here, we apply the manual McComas method to estimate the number of motor units in a nasal dilator muscle. EMG of the dilator naris was recorded during graded stimulation of the zygomatic branch of the facial nerve in 26 subjects (12 males and 14 females), aged 20-41 years. Each subject was studied twice, on separate days, to estimate method reproducibility. As a check on our use of the McComas method, we also estimated motor unit number in the first dorsal interosseus muscle (FDI) of six subjects, as the muscle is also small and has been studied with the McComas method. Reproducibility was evaluated with a rigorous statistical approach, the Bland-Altman procedure. We estimate that dilator naris is composed of 75 ± 15.6 (SD) motor units, compared to 144 ± 35.5 in FDI. The coefficient of variation for test-retest reproducibility of dilator naris motor unit estimates was 29.6 %, similar to separate-day reproducibility reported for other muscles. Recording and stimulation were done with surface electrodes, and the recordings were of high quality and reproducible. This simple technique could be applied clinically to track motor neuron loss and to monitor facial nerve integrity.

Interrelationship between muscle strength, motor units, and aging

The interrelationship between muscle strength, motor unit (MU) number, and age is poorly understood, and in this study we sought to determine whether age-related differences in muscle strength are moderated by estimates of functioning MU number and size. Eighteen older adults (OA; 67 ± 1.20 years) and 24 young adults (YA; 22 ± 0.74 years) participated in this study. Maximum voluntary pinch-grip strength of the nondominant hand was determined and estimates of MU number were obtained from the abductor pollicis brevis muscle using the noninvasive motor unit number index (MUNIX) technique. The MUNIX technique was also utilized to derive a motor unit size index (MUSIX). An analysis of covariance (Age Group × MUNIX or MUSIX) was used to test heterogeneity of regression slopes, with body mass and gender serving as covariates. We observed that the slope of pinch-grip strength on the estimated number of MUs between YA and OA differed, indicated by an Age Group × MUNIX interaction (p = 0.04). Specifically, after controlling for the effect of body mass and gender, the slope in OA was significantly positive (0.14 ± 0.06 N/MUs, p = 0.03), whereas no such relationship was found in YA (-0.08 ± 0.09 N/MUs, p = 0.35). A significant Age Group × MUSIX interaction was also observed for strength (p < 0.01). In contrast to MUNIX, the slope in younger adults was significantly positive (0.48 ± 0.11 N/μV, p < 0.01), whereas no such relationship was found in older adults (-0.30 ± 0.22 N/μV, p = 0.18). These findings indicate that there is an interrelationship between muscle strength, MU numbers, and aging, which suggests that a portion of muscle weakness in seniors may be attributable to the loss of functioning motor units.