Estimating motor unit numbers from a CMAP scan

INTRODUCTION: Compound muscle action potential (CMAP) scans are detailed stimulus-response curves which provide information about motor unit properties in neuromuscular disorders. This study assessed a method of automatic motor unit number estimation (MUNE) from 5-min CMAP scans. METHODS: A preliminary model, derived from the variance and slope of the scan, is refined to fit the CMAP scan more closely. The method was tested by application to 60 simulated scans, generated from between 5 and 160 motor unit potentials. RESULTS: The fitting procedure took an average of 1.5 min on a standard personal computer. Small unit numbers (5-20) were on average correctly estimated, but large unit numbers (>40) were slightly underestimated. Overall, the absolute MUNE error averaged 6.9%. CONCLUSIONS: This new MUNE method takes all excitable motor units into account and provides realistic estimates of unit numbers over the range 5 to 160. Validation as a clinical tool awaits further study

Changes in extracellular pH during electrical stimulation of isolated rat vagus nerve

Double-barrelled pH-sensitive micro-electrodes were used to record changes of extracellular pH during repetitive stimulation of isolated rat vagus nerves. It was found that a small initial alkaline shift was followed by a prolonged acidification. The acidification was correlated in time with the poststimulus undershoot of the extracellular K+ activity and with the recovery phase of the nerve conduction velocity. In the presence of ouabain, the acid component of the pH change was completely abolished (indicating a metabolic origin), whereas the alkaline component remained unaltered. These pH changes were too small to make a significant contribution to the activity-related changes in conduction velocity of the vagal C-fibres

A test to determine the site of abnormal neuromuscular refractoriness

Objective: The relative refractory period (RRP) of motor axons is an important parameter in nerve excitability tests of the recovery cycle (RC). Abnormalities may have a site in the axonal membrane, the neuromuscular junction, or in a dysfunction of the muscle. We aimed in this study to determine the site of abnormality, using a modified protocol of the conventional RC test, whereby an additional supramaximal stimulus is added at the same interstimulus interval as in RC recordings (RCSM). Methods: Twenty-four healthy subjects aged 37.8 ± 2.4 years (mean ± SE) were examined with median nerve excitability testing using RC and RCSM protocols at normal temperature (34.1 ± 0.2 °C). The recordings were repeated in 12 subjects after selective cooling of the thenar muscle (25.2 ± 0.7 °C) and in 12 subjects after cooling the nerve trunk at the wrist (24.9 ± 0.3 °C). Results: After cooling the nerve, RRP measured with RC and RCSM were prolonged similarly (medians by 1.8 ms, and 2.1 ms respectively). In contrast, cooling the muscle prolonged RRP measured with RC (by 1.3 ms), but did not significantly prolong RRP measured with RCSM. RRPs measured by RC and RCSM were significantly different when cooling was at the muscle (P = 5.10-4), but not when cooling was at the nerve (P = 0.57). Conclusions: A difference between RC and RCSM indicates abnormal excitability distal to the axonal membrane under the stimulating electrode. Significance: Combining RCSM with the conventional RC protocol should help to localize the site of abnormal neuromuscular refractoriness

CMAP Scan MUNE (MScan) - A Novel Motor Unit Number Estimation (MUNE) Method

Like other methods for motor unit number estimation (MUNE), compound muscle action potential (CMAP) scan MUNE (MScan) is a non-invasive electrophysiologic method to estimate the number of functioning motor units in a muscle. MUNE is an important tool for the assessment of neuropathies and neuronopathies. Unlike most MUNE methods in use, MScan assesses all the motor units in a muscle, by fitting a model to a detailed stimulus-response curve, or CMAP scan. It thereby avoids the bias inherent in all MUNE methods based on extrapolating from a small sample of units. Like 'Bayesian MUNE,' MScan analysis works by fitting a model, made up of motor units with different amplitudes, thresholds, and threshold variabilities, but the fitting method is quite different, and completed within five minutes, rather than several hours. The MScan off-line analysis works in two stages: first, a preliminary model is generated based on the slope and variance of the points in the scan, and second, this model is then refined by adjusting all the parameters to improve the fit between the original scan and scans generated by the model. This new method has been tested for reproducibility and recording time on 22 amyotrophic lateral sclerosis (ALS) patients and 20 healthy controls, with each test repeated twice by two blinded physicians. MScan showed excellent intra- and inter-rater reproducibility with ICC values of >0.98 and a coefficient of variation averaging 12.3 ± 1.6%. There was no difference in the intra-rater reproducibility between the two observers. Average recording time was 6.27 ± 0.27 min. This protocol describes how to record a CMAP scan and how to use the MScan software to derive an estimate of the number and sizes of the functioning motor units. MScan is a fast, convenient, and reproducible method, which may be helpful in diagnoses and monitoring disease progression in neuromuscular disorders

Accommodation to hyperpolarization of human axons assessed in the frequency domain

Human axonsin vivowere subjected to subthreshold currents with a threshold-"ZAP" profile (Impedance [ Z: ] A: mplitude P: rofile) to allow the use of frequency domain techniques to determine the propensity for resonant behavior, and to clarify the relative contributions of different ion channels to their low-frequency responsiveness. Twenty-four studies were performed on the motor and sensory axons in 6 subjects. The response to oscillatory currents was tested between 'DC' and 16 Hz. A resonant peak at ~2 to 2.5 Hz was found in the response of hyperpolarized axons, but there was only a small broad response in axons at resting membrane potential (RMP). A mathematical model of axonal excitability developed using DC pulses provided a good fit to the frequency response for human axons, and indicated that the hyperpolarization-activated currentIh, and the slow potassium currentIKsare principally responsible for the resonance. However the results indicate that if axons are hyperpolarized more than -60% of resting threshold, the only conductances that are appreciably active areIhand the leak conductance - i.e., that the activity of these conductances can be studiedin vivovirtually in isolation at hyperpolarized membrane potentials. Given that the leak conductance dampens resonance it is suggested that the -60% hyperpolarization used here is optimal forIh As expected differences between the frequency responses of motor and sensory axons were present and best explained by reduced GKs, up-modulation ofIhand increased persistent Na(+)current,INaP(due to depolarization of RMP) in sensory axons

Short-interval intracortical inhibition: Comparison between conventional and threshold-tracking techniques

BACKGROUND: Short-interval intracortical inhibition (SICI) is conventionally measured as the relative amplitude reduction of motor evoked potentials (MEPs) by subthreshold conditioning stimuli. In threshold-tracking SICI (T-SICI), stimulus intensity is instead adjusted repeatedly to maintain a constant MEP and inhibition is measured as the relative threshold increase. T-SICI is emerging as a useful diagnostic test, but its relationship to conventional amplitude SICI (A-SICI) is unclear. OBJECTIVE: To compare T-SICI and its reliability with conventional A-SICI measurements. METHODS: In twelve healthy volunteers (6 men, median age 30 years), conventional and T-SICI were recorded at conditioning stimuli (CS) of 50-80% resting motor threshold (RMT) and interstimulus interval of 2.5 ms. Measurements were repeated on the same day and at least a week later by a single operator. RESULTS: Across the CS range, mean group T-SICI showed a strong linear relationship to the mean group values measured by conventional technique (y = 29.7-0.3x, R2 = 0.99), but there was considerable interindividual variability. At CS 60-80% RMT, T-SICI had excellent intraday (intraclass correlation coefficient, ICC, 0.81-0.92) and adequate-to-excellent interday (ICC 0.61-0.88) reproducibility. Conventional SICI took longer to complete (median of 5.8 vs 3.8 min, p < 0.001) and tended to have poorer reproducibility (ICC 0.17-0.42 intraday, 0.37-0.51 interday). With T-SICI, smaller sample sizes were calculated for equally powered interventional studies. CONCLUSION: The close relationship between conventional and T-SICI suggests that both techniques reflect similar cortical inhibitory mechanisms. Threshold-tracking measurements of SICI may be able to improve reproducibility, to shorten acquisition time and to reduce sample sizes for interventional studies compared with the conventional technique

Conventional and threshold-tracking transcranial magnetic stimulation tests for single-handed operation

Most single-pulse transcranial magnetic stimulation (TMS) parameters (e.g., motor threshold, stimulus-response function, cortical silent period) are used to examine corticospinal excitability. Paired-pulse TMS paradigms (e.g., short-and long-interval intracortical inhibition (SICI/LICI), short-interval intracortical facilitation (SICF), and short-and long-latency afferent inhibition (SAI/LAI)) provide information about intracortical inhibitory and facilitatory networks. This has long been done by the conventional TMS method of measuring changes in the size of the motor-evoked potentials (MEPs) in response to stimuli of constant intensity. An alternative threshold-tracking approach has recently been introduced whereby the stimulus intensity for a target amplitude is tracked. The diagnostic utility of threshold-tracking SICI in amyotrophic lateral sclerosis (ALS) has been shown in previous studies. However, threshold-tracking TMS has only been used in a few centers, in part due to the lack of readily available software but also perhaps due to uncertainty over its relationship to conventional single-and paired-pulse TMS measurements. A menu-driven suite of semi-automatic programs has been developed to facilitate the broader use of threshold-tracking TMS techniques and to enable direct comparisons with conventional amplitude measurements. These have been designed to control three types of magnetic stimulators and allow recording by a single operator of the common single-and paired-pulse TMS protocols. This paper shows how to record a number of single-and paired-pulse TMS protocols on healthy subjects and analyze the recordings. These TMS protocols are fast and easy to perform and can provide useful biomarkers in different neurological disorders, particularly neurodegenerative diseases such as ALS

Short interval intracortical inhibition: Variability of amplitude and threshold-tracking measurements with 6 or 10 stimuli per point

Reduced short-interval intracortical inhibition (SICI) in motor neuron disease has been demonstrated by amplitude changes (A-SICI) and threshold-tracking (T-SICI) using 10 stimuli per inter-stimulus interval (ISI). To test whether fewer stimuli would suffice, A-SICI and T-SICI were recorded twice from 30 healthy subjects using 6 and 10 stimuli per ISI. Using fewer stimuli increased mean A-SICI variances by 23.8% but the 7.3% increase in T-SICI variance was not significant. We conclude that our new parallel threshold-tracking SICI protocol, with 6 stimuli per ISI, can reduce time and stimulus numbers by 40% without appreciable loss of accuracy

Peacock Bundles: Bundle Coloring for Graphs with Globality-Locality Trade-off

Bundling of graph edges (node-to-node connections) is a common technique to enhance visibility of overall trends in the edge structure of a large graph layout, and a large variety of bundling algorithms have been proposed. However, with strong bundling, it becomes hard to identify origins and destinations of individual edges. We propose a solution: we optimize edge coloring to differentiate bundled edges. We quantify strength of bundling in a flexible pairwise fashion between edges, and among bundled edges, we quantify how dissimilar their colors should be by dissimilarity of their origins and destinations. We solve the resulting nonlinear optimization, which is also interpretable as a novel dimensionality reduction task. In large graphs the necessary compromise is whether to differentiate colors sharply between locally occurring strongly bundled edges ("local bundles"), or also between the weakly bundled edges occurring globally over the graph ("global bundles"); we allow a user-set global-local tradeoff. We call the technique "peacock bundles". Experiments show the coloring clearly enhances comprehensibility of graph layouts with edge bundling.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016