The relationship between Bayesian motor unit number estimation and histological measurements of motor neurons in wild-type and SOD1 G93A mice

Objective: To assess the relationship between Bayesian MUNE and histological motor neuron counts in wild-type mice and in an animal model of ALS. Methods: We performed Bayesian MUNE paired with histological counts of motor neurons in the lumbar spinal cord of wild-type mice and transgenic SOD1 G93A mice that show progressive weakness over time. We evaluated the number of acetylcholine endplates that were innervated by a presynaptic nerve. Results: In wild-type mice, the motor unit number in the gastrocnemius muscle estimated by Bayesian MUNE was approximately half the number of motor neurons in the region of the spinal cord that contains the cell bodies of the motor neurons supplying the hindlimb crural flexor muscles. In SOD1 G93A mice, motor neuron numbers declined over time. This was associated with motor endplate denervation at the end-stage of disease. Conclusion: The number of motor neurons in the spinal cord of wild-type mice is proportional to the number of motor units estimated by Bayesian MUNE. In SOD1 G93A mice, there is a lower number of estimated motor units compared to the number of spinal cord motor neurons at the end-stage of disease, and this is associated with disruption of the neuromuscular junction. Significance: Our finding that the Bayesian MUNE method gives estimates of motor unit numbers that are proportional to the numbers of motor neurons in the spinal cord supports the clinical use of Bayesian MUNE in monitoring motor unit loss in ALS patients. © 2012 International Federation of Clinical Neurophysiology.

Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation

Motor unit number estimation (MUNE) is a method which aims to provide a quantitative indicator of progression of diseases that lead to loss of motor units, such as motor neurone disease. However the development of a reliable, repeatable and fast real-time MUNE method has proved elusive hitherto. Ridall et al. (2007) implement a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to produce a posterior distribution for the number of motor units using a Bayesian hierarchical model that takes into account biological information about motor unit activation. However we find that the approach can be unreliable for some datasets since it can suffer from poor cross-dimensional mixing. Here we focus on improved inference by marginalising over latent variables to create the likelihood. In particular we explore how this can improve the RJMCMC mixing and investigate alternative approaches that utilise the likelihood (e.g. DIC (Spiegelhalter et al., 2002)). For this model the marginalisation is over latent variables which, for a larger number of motor units, is an intractable summation over all combinations of a set of latent binary variables whose joint sample space increases exponentially with the number of motor units. We provide a tractable and accurate approximation for this quantity and also investigate simulation approaches incorporated into RJMCMC using results of Andrieu and Roberts (2009).

Motor unit number estimation - A Bayesian approach

All muscle contractions are dependent on the functioning of motor units. In diseases such as amyotrophic lateral sclerosis (ALS), progressive loss of motor units leads to gradual paralysis. A major difficulty in the search for a treatment for these diseases has been the lack of a reliable measure of disease progression. One possible measure would be an estimate of the number of surviving motor units. Despite over 30 years of motor unit number estimation (MUNE), all proposed methods have been met with practical and theoretical objections. Our aim is to develop a method of MUNE that overcomes these objections. We record the compound muscle action potential (CMAP) from a selected muscle in response to a graded electrical stimulation applied to the nerve. As the stimulus increases, the threshold of each motor unit is exceeded, and the size of the CMAP increases until a maximum response is obtained. However, the threshold potential required to excite an axon is not a precise value but fluctuates over a small range leading to probabilistic activation of motor units in response to a given stimulus. When the threshold ranges of motor units overlap, there may be alternation where the number of motor units that fire in response to the stimulus is variable. This means that increments in the value of the CMAP correspond to the firing of different combinations of motor units. At a fixed stimulus, variability in the CMAP, measured as variance, can be used to conduct MUNE using the "statistical" or the "Poisson" method. However, this method relies on the assumptions that the numbers of motor units that are firing probabilistically have the Poisson distribution and that all single motor unit action potentials (MUAP) have a fixed and identical size. These assumptions are not necessarily correct. We propose to develop a Bayesian statistical methodology to analyze electrophysiological data to provide an estimate of motor unit numbers. Our method of MUNE incorporates the variability of the threshold, the variability between and within single MUAPs, and baseline variability. Our model not only gives the most probable number of motor units but also provides information about both the population of units and individual units. We use Markov chain Monte Carlo to obtain information about the characteristics of individual motor units and about the population of motor units and the Bayesian information criterion for MUNE. We test our method of MUNE on three subjects. Our method provides a reproducible estimate for a patient with stable but severe ALS. In a serial study, we demonstrate a decline in the number of motor unit numbers with a patient with rapidly advancing disease. Finally, with our last patient, we show that our method has the capacity to estimate a larger number of motor units.

Quantitative studies of lower motor neuron degeneration in amyotrophic lateral sclerosis : Evidence for exponential decay of motor unit numbers and greatest rate of loss at the site of onset

Objective: To use our Bayesian method of motor unit number estimation (MUNE) to evaluate lower motor neuron degeneration in ALS. Methods: In subjects with ALS we performed serial MUNE studies. We examined the repeatability of the test and then determined whether the loss of MUs was fitted by an exponential or Weibull distribution. Results: The decline in motor unit (MU) numbers was well-fitted by an exponential decay curve. We calculated the half life of MUs in the abductor digiti minimi (ADM), abductor pollicis brevis (APB) and/or extensor digitorum brevis (EDB) muscles. The mean half life of the MUs of ADM muscle was greater than those of the APB or EDB muscles. The half-life of MUs was less in the ADM muscle of subjects with upper limb than in those with lower limb onset. Conclusions: The rate of loss of lower motor neurons in ALS is exponential, the motor units of the APB decay more quickly than those of the ADM muscle and the rate of loss of motor units is greater at the site of onset of disease. Significance: This shows that the Bayesian MUNE method is useful in following the course and exploring the clinical features of ALS. 2012 International Federation of Clinical Neurophysiology.

The stimulus-response curve and motor unit variability in normal subjects and subjects with amyotrophic lateral sclerosis

The behavior and stability of motor units (MUs) in response to electrical stimulation of different intensities can be assessed with the stimulus-response curve, which is a graphical representation of the size of the compound muscle action potential (CMAP) in relation to stimulus intensity. To examine MU characteristics across the whole stimulus range, the variability of CMAP responses to electrical stimulation, and the differences that occur between normal and disease states, the curve was studied in 11 normal subjects and 16 subjects with amyotrophic lateral sclerosis (ALS). In normal subjects, the curve showed a gradual increase in CMAP size with increasing stimulus intensity, although one or two discrete steps were sometimes observed in the upper half of the curve, indicating the activation of large MUs at higher intensities. In ALS subjects, large discrete steps, due to loss of MUs and collateral sprouting, were frequently present. Variability of the CMAP responses was greater than baseline variability, indicating variability of MU responses, and at certain levels this variability was up to 100 mu Vms. The stimulus-response curve shows differences between normal and ALS subjects and provides information on MU activation and variability throughout the curve.

Motor-unit coherence and its relation with synchrony are influenced by training

The purpose of the study was to quantify the strength of motor-unit coherence from the left and right first dorsal interosseous muscles in untrained, skill-trained (musicians), and strength-trained (weightlifters) individuals who had long-term specialized use of their hand muscles. The strength of motor-unit coherence was quantified from a total of 394 motor-unit pairs in 13 subjects using data from a previous study in which differences were found in the strength of motor-unit synchronization depending on training status. In the present study, we found that the strength of motor-unit coherence was significantly greater in the left compared with the right hand of untrained right-handed subjects with the largest differences observed between 21 and 24 Hz. The strength of motor-unit coherence was lower in both hands of skill-trained subjects (21–27 Hz) and the right (skilled) hand of untrained subjects (21–24 Hz), whereas the largest motor-unit coherence was observed in both hands of strength-trained subjects (3–9 and 21–27 Hz). A strong curvilinear association was observed between motor-unit synchronization and the integral of coherence at 10–30 Hz in all motor-unit pairs (r² = 0.77), and was most pronounced in strength-trained subjects (r² = 0.90). Furthermore, this association was accentuated when using synchronization data with broad peaks (>11 ms), suggesting that the 10- to 30-Hz coherence is due to oscillatory activity in indirect branched common inputs. The altered coherence with training may be due to an interaction between cortical inhibition and the number of direct common inputs to motor neurons in skill- or strength-trained hands.

Quantitative motor unit action potential analysis in 2 paraspinal neck muscles in adult Royal Dutch Sport horses

BACKGROUND: Reference values for quantitative electromyography (QEMG) in neck muscles of Royal Dutch Sport horses are lacking. OBJECTIVE: Determine normative data on quantitative motor unit action potential (QMUP) analysis of serratus ventralis cervicis (SV) and brachiocephalicus (BC) muscle. ANIMALS: Seven adult normal horses (mean age 9.5 standard deviation [SD] +/- 2.3 years, mean height 1.64 SD +/- 4.5 cm, and mean rectal temperature 37.6 SD +/- 0.3 degrees C). METHODS: An observational study on QMUP analysis in 6 segments of each muscle was performed with commercial electromyography equipment. Measurements were made according to formerly published methods. Natural logarithm transformed data were tested with ANOVA and posthoc testing according to Bonferroni. RESULTS: Mean duration, amplitude, phases, turns, area, and size index (SI) did not differ significantly among the 6 segments in each muscle. Mean amplitude, number of phases, and SI were significantly (P < .002) higher in SV than BC, 520 versus 448 muV, 3.0 versus 2.8 muV, and 0.48 versus 0.30 muV, respectively. In SV 95% confidence intervals (CI) for amplitude, duration, number of phases, turns, polyphasia area, and SI were 488-551 muV, 4.3-4.6 ms, 2.9-3.0, 2.4-2.6, 7-12%, 382-448, and 0.26-0.70, respectively; in BC this was 412-483 muV, 4.3-4.7 ms, 2.7-2.8, 2.4-2.6, 4-7%, 393-469, and 0.27-0.34, respectively. Maximal voluntary activity expressed by turns/second did not differ significantly between SV and BC with a 95% CI of 132-173 and 137-198, respectively. CONCLUSIONS AND CLINICAL IMPORTANCE: The establishment of normative data makes objective QEMG of paraspinal muscles in horses suspected of cervical neurogenic disorders possible. Differences between muscles should be taken into account.

Use of Bayesian MUNE to show differing rate of loss of motor units in subgroups of ALS

Objectives To evaluate differences among patients with different clinical features of ALS, we used our Bayesian method of motor unit number estimation (MUNE). Methods We performed serial MUNE studies on 42 subjects who fulfilled the diagnostic criteria for ALS during the course of their illness. Subjects were classified into three subgroups according to whether they had typical ALS (with upper and lower motor neurone signs) or had predominantly upper motor neurone weakness with only minor LMN signs, or predominantly lower motor neurone weakness with only minor UMN signs. In all subjects we calculated the half life of MUs, defined as the expected time for the number of MUs to halve, in one or more of the abductor digiti minimi (ADM), abductor pollicis brevis (APB) and extensor digitorum brevis (EDB) muscles. Results The mean half life of MUs was less in subjects who had typical ALS with both upper and lower motor neurone signs than in those with predominantly upper motor neurone weakness or predominantly lower motor neurone weakness. In 18 subjects we analysed the estimated size of the MUs and demonstrated the appearance of large MUs in subjects with upper or lower motor neurone predominant weakness. We found that the appearance of large MUs was correlated with the half life of MUs. Conclusions Patients with different clinical features of ALS have different rates of loss and different sizes of MUs. Significance: These findings could indicate differences in disease pathogenesis.

Decreased motor unit firing rate in the potentiated tibialis anterior in humans

With repeated activity, force production, rate of force production, and relaxation time are impaired. These are characteristics ofa fatigued muscle (Vandenboom, 2004). However, brief bouts of near maximal to maximal activity results in the increased ability of the muscle to generate force, termed post activation potentiation (P AP)(V andervoort et aI., 1983). The purpose of the present study was to characterize motor unit firing rate (MUFR) in the unfatigued, potentiated tibialis anterior (TA). Using a quadrifilar needle electrode, MUFR was measured during a 5s 50% MVC in which the TA was either potentiated or unpotentiated; monopolar electrodes measured surface parameters. A lOs MVC was used to potentiate the muscle. Firing rate decreased significantly from 20.15±2.9Opps to 18.27±2.99pps, while mean power frequency decreased significantly from 60. 13±7.75 Hz to 53.62±8.56 Hz. No change in root mean square (RMS) was observed. Therefore, in the present study, MUFR decreases in response to a potentiated TA.

Determining feature relevance for the grouping of motor unit action potentials through generative topographic mapping

The study of motor unit action potential (MUAP) activity from electrornyographic signals is an important stage on neurological investigations that aim to understand the state of the neuromuscular system. In this context, the identification and clustering of MUAPs that exhibit common characteristics, and the assessment of which data features are most relevant for the definition of such cluster structure are central issues. In this paper, we propose the application of an unsupervised Feature Relevance Determination (FRD) method to the analysis of experimental MUAPs obtained from healthy human subjects. In contrast to approaches that require the knowledge of a priori information from the data, this FRD method is embedded on a constrained mixture model, known as Generative Topographic Mapping, which simultaneously performs clustering and visualization of MUAPs. The experimental results of the analysis of a data set consisting of MUAPs measured from the surface of the First Dorsal Interosseous, a hand muscle, indicate that the MUAP features corresponding to the hyperpolarization period in the physisiological process of generation of muscle fibre action potentials are consistently estimated as the most relevant and, therefore, as those that should be paid preferential attention for the interpretation of the MUAP groupings.