Single Motor Unit Action Potentials Research Articles

Simulated Surface Electromyographic (SEMG) Signal Generation and Detection Model

Abstract For didactic purposes, the aim of this work was to improve a simulation model of surface electromyographic (sEMG) signal by taking into consideration the shortcomings of previously developed models. This model started with the simulation of the single fibre action potential (SFAP), then the model of the single motor unit action potential (MUAP), afterwards the imitation of the train of MUAP and finally the modellig of the resultant sEMG signal which is the sum of the MUAPs trains. SFAP simulation was based on: i) the description of the volume conductor model which is composed of four layers (bone, muscle, fat and skin), ii) the description of the electrodes shapes and sizes as well as spatial filters, iii) and the transmebrane current. The proposed model shows its effectiveness in the possibility of carrying out practical work by simulation on the modelling of SFAP, MUAP, MUAPT and the sEMG signal. The most important result of this model is that signal processing tools can be applied to analyze and interpret real-world phenomena such as the effects of physiological, non physiological and sensing system parameters on the shape of the simulated sEMG signal.

Estimation of Muscle Fiber Direction by Multi-channel Surface EMG Conductiong Wave Analysis Using Grid Surface Electrodes

Skeletal muscle is a set of motor units (MU). Muscle contractile activity is carried out by regulating the firing frequency of MU and the types of muscle fibers to be mobilized. Multi-channel surface electromyogram (sEMG) contains many conducting waves that represent a single motor unit action potentials (MUAP). In previous study, we proposed a method to extract conducting waves quantitatively and automatically. This method is useful for elucidating mobilized MUs and can be applied to kinematic analysis and diagnosis of muscle diseases. In multi-channel sEMG measurement, rows of electrodes need to be applied along the direction of the muscle fibers. However, the electrodes are difficult to set because the direction of the muscle fibers cannot be visually confirmed on the skin. This study investigated a method for estimating muscle fiber direction by analyzing conducting waves from two-dimensional multichannel surface electromyograms using grid-shaped surface electrodes. By examining the number of conducting waves acquired in each direction of the electrode row, it was suggested that the direction of muscle fiber may be estimated from the direction with the largest number of propagating wave acquisitions. It was also found that the method of acquiring differential potential signals has a significant impact on the analysis of propagation direction.

Pain P-PA001. Parsonage turner syndrome

Introduction . Parsonage Turner Syndrome (PTS) is a rare syndrome that may occur in healthy subjects. The clinical presentation might not be typical and risk factors attributed to the development of disease may not be easily depicted. We present a case of abrupt onset of unilateral shoulder pain, followed by progressive neurologic weakness. Result . A 54-year-old male presented with abrupt onset of shoulder pain mainly on the right side. Pain was felt in both shoulder and thigh which progressed to weakness, dysesthesia, and numbness in the right upper arm. In 4 days, he could barely lift his right upper arm. There was no history of trauma nor infection on the affected area. On physical examination, there were limitation of shoulder abduction and external rotation. His right arm strength from proximal to distal was 1344. Other extremities showed no significant weakness. Sensory involvement did not match dermatomal and peripheral sensory distribution. Nerve Conduction Velocity (NCV) showed axonal motor neuropathy of right axillary nerve. Electromyography (EMG) showed no Motor Unit Action Potential (MUAP) on deltoid muscle. His CK was 457, and there was an increase in LDH and CRP. Cervical MRI was unremarkable. Steroids were immediately given, and the response was fast and satisfactory. After 1 day, his motor strength increased, and the pain subsided. EMG showed single MUAP on deltoid. After 10 days, his motor strength returned to near normal. NCV study showed decreased amplitude of right axillary nerve, and recruitment was slightly decreased on right deltoid muscle. He underwent physical therapy and was making marked progress. Conclusion . PTS generally involves one upper limb, and axillary nerve is one the most commonly involved. PTS should be considered as a differential diagnosis in cases of shoulder pain and arm weakness without any clear etiology.

Modeling motor-evoked potentials from neural field simulations of transcranial magnetic stimulation

ObjectiveTo develop a population-based biophysical model of motor-evoked potentials (MEPs) following transcranial magnetic stimulation (TMS). MethodsWe combined an existing MEP model with population-based cortical modeling. Layer 2/3 excitatory and inhibitory neural populations, modeled with neural-field theory, are stimulated with TMS and feed layer 5 corticospinal neurons, which also couple directly but weakly to the TMS pulse. The layer 5 output controls mean motoneuron responses, which generate a series of single motor-unit action potentials that are summed to estimate a MEP. ResultsA MEP waveform was generated comparable to those observed experimentally. The model captured TMS phenomena including a sigmoidal input–output curve, common paired pulse effects (short interval intracortical inhibition, intracortical facilitation, long interval intracortical inhibition) including responses to pharmacological interventions, and a cortical silent period. Changes in MEP amplitude following theta burst paradigms were observed including variability in outcome direction. ConclusionsThe model reproduces effects seen in common TMS paradigms. SignificanceThe model allows population-based modeling of changes in cortical dynamics due to TMS protocols to be assessed in terms of changes in MEPs, thus allowing a clear comparison between population-based modeling predictions and typical experimental outcome measures.

Exclusive Image Gallery on Human Spinal Cord Regeneration-Clinical Image-17

Layout for measuring coordination dynamics (arrhythmicity of exercising) between arm and leg movements, displayed on the laptop; for the intermediate coordination’s between pace and trot gait, the fluctuation of the network states is larger. The recording of sEMG activity (displayed on the oscilloscope) from the tibialis anterior and other muscles is also shown. The inset shows single motor unit action potentials on the lowest trace. The recordings are taken from a patient (Kadri) with a motoric complete cervical spinal cord injury C5/6 (95% injury).

Separation of interference surface electromyogram into propagating and non-propagating components

A new algorithm is introduced to decompose interference surface electromyogram (EMG) recorded by a multi-channel system aligned to muscle fibers into propagating and non-propagating contributions. Muscle fiber conduction velocity (CV) is also estimated, reducing the bias induced by non-propagating components. The algorithm is fast and stable, as it is based on alignment and averaging procedures. Simulated signals (with different fat thickness, SNR, number of channels, epoch duration and force level) are used to test the algorithm. The median cross-correlation of simulated and estimated components were about 98% and 90%, for propagating and non-propagating terms, respectively. CV was estimated better than using a multi-channel maximum likelihood approach applied to double differential data (mean error of 0.08 versus 0.13 m/s), with a greater gain in case of thinner fat layer, low SNR and few channels. Example applications to experimental data are also shown (single motor unit action potential, M-wave and interference EMG).Propagating components reflect the travelling of action potentials along muscle fibers. Preliminary tests show that non-propagating contributions provide selective information on motor units firing statistics. The separation of interference EMG into propagating and non-propagating components opens new perspectives, e.g., in the study of synergies, common drive and myoelectric manifestations of fatigue.

A modified multiple point stimulation method for motor unit number estimation of the hypothenar muscles.

The goal of this study is to test the hypothesis that single motor unit action potentials (SMUPs) originating from other ulnar nerve-innervated intrinsic hand muscles can inflate the motor unit number estimation (MUNE) of the hypothenar muscles. Using the multiple point stimulation method, SMUPs recorded over the hypothenar muscles from distant origins were characterized through multichannel recordings. The MUNE calculated using only the hypothenar SMUPs was compared with estimations based on the whole ensemble. Of the 41 studies performed, distant SMUPs represented 17 ± 9.5% (mean ± SD) of the overall sample. MUNE calculated using only hypothenar SMUPs was 423 ± 204, compared with 537 ± 290 if all SMUPs were included (P < 0.05). The extent of increase in MUNE was highly correlated with the proportion of distant SMUPs found (r = 0.89, P < 0.05). Erroneous inclusion of SMUPs from distant muscles can significantly distort the MUNE results. Muscle Nerve 59:337-341, 2019.

Motor unit innervation zone localization based on robust linear regression analysis

With the aim of developing a flexible and reliable procedure for superficial muscle innervation zone (IZ) localization, we proposed a method to estimate IZ location using surface electromyogram (EMG) based on robust linear regression. Regression lines were used to model the bidirectional propagation pattern of a single motor unit action potential (MUAP) and visualize the trajectory of the MUAP propagation. IZ localization was performed by identifying the origin of the bidirectional MUAP propagation. Robust linear regression and MUAP peak detection, combined with propagation phase reversal identification, may provide an efficient way to estimate IZ location. Our method offers high resolution in locating IZs based on simulation studies and experimental tests. Furthermore, our method is flexible and may also be applied using a relatively small number of EMG channels. A comparative study of the proposed method with the cross-correlation method for IZ localization was conducted. The results obtained with simulated MUAPs and measured spontaneous MUAPs in the biceps brachii muscle in six subjects (four males and two females, 57 ± 10 years old) with amyotrophic lateral sclerosis (ALS). Our method achieved estimation performance comparable to that obtained by using the cross-correlation method but with higher resolution. This study provides an accurate and practical method to estimate IZ location.

Motor Unit Action Potential Clustering-Theoretical Consideration for Muscle Activation during a Motor Task.

During dynamic or sustained isometric contractions, bursts of muscle activity appear in the electromyography (EMG) signal. Theoretically, these bursts of activity likely occur because motor units are constrained to fire temporally close to one another and thus the impulses are “clustered” with short delays to elicit bursts of muscle activity. The purpose of this study was to investigate whether a sequence comprised of “clustered” motor unit action potentials (MUAP) can explain spectral and amplitude changes of the EMG during a simulated motor task. This question would be difficult to answer experimentally and thus, required a model to study this type of muscle activation pattern. To this end, we modeled two EMG signals, whereby a single MUAP was either convolved with a randomly distributed impulse train (EMG-rand) or a “clustered” sequence of impulses (EMG-clust). The clustering occurred in windows lasting 5–100 ms. A final mixed signal of EMG-clust and EMG-rand, with ratios (1:1–1:10), was also modeled. A ratio of 1:1 would indicate that 50% of MUAP were randomly distributed, while 50% of “clustered” MUAP occurred in a given time window (5–100 ms). The results of the model showed that clustering MUAP caused a downshift in the mean power frequency (i.e., ~30 Hz) with the largest shift occurring with a cluster window of 10 ms. The mean frequency shift was largest when the ratio of EMG-clust to EMG-rand was high. Further, the clustering of MUAP also caused a substantial increase in the amplitude of the EMG signal. This model potentially explains an activation pattern that changes the EMG spectra during a motor task and thus, a potential activation pattern of muscles observed experimentally. Changes in EMG measurements during fatiguing conditions are typically attributed to slowing of conduction velocity but could, per this model, also result from changes of the clustering of MUAP. From a clinical standpoint, this type of muscle activation pattern might help describe the pathological movement issues in people with Parkinson’s disease or essential tremor. Based on our model, researchers moving forward should consider how MUAP clustering influences EMG spectral and amplitude measurements and how these changes influence movements.

Intramuscular EMG Decomposition Basing on Motor Unit Action Potentials Detection and Superposition Resolution.

A novel electromyography (EMG) signal decomposition framework is presented for the thorough and precise analysis of intramuscular EMG signals. This framework first detects all of the active motor unit action potentials (MUAPs) and assigns single MUAP segments to their corresponding motor units. MUAP waveforms that are found to be superimposed are then resolved into their constituent single MUAPs using a peel-off approach and similarly assigned. The method is composed of six stages of analytical procedures: preprocessing, segmentation, alignment and feature extraction, clustering and refinement, supervised classification, and superimposed waveform resolution. The performance of the proposed decomposition framework was evaluated using both synthetic EMG signals and real recordings obtained from healthy and stroke participants. The overall detection rate of MUAPs was 100% for both synthetic and real signals. The average accuracy for synthetic EMG signals was 87.23%. Average assignment accuracies of 88.63 and 94.45% were achieved for the real EMG signals obtained from healthy and stroke participants, respectively. Results demonstrated the ability of the developed framework to decompose intramuscular EMG signals with improved accuracy and efficiency, which we believe will greatly benefit the clinical utility of EMG for the diagnosis and rehabilitation of motor impairments in stroke patients.

Distribution of muscle fibre conduction velocity for representative samples of motor units in the full recruitment range of the tibialis anterior muscle.

Motor units are recruited in an orderly manner according to the size of motor neurones. Moreover, because larger motor neurones innervate fibres with larger diameters than smaller motor neurones, motor units should be recruited orderly according to their conduction velocity (MUCV). Because of technical limitations, these relations have been previously tested either indirectly or in small motor unit samples that revealed weak associations between motor unit recruitment threshold (RT) and MUCV. Here, we analyse the relation between MUCV and RT for large samples of motor units. Ten healthy volunteers completed a series of isometric ankle dorsiflexions at forces up to 70% of the maximum. Multi-channel surface electromyographic signals recorded from the tibialis anterior muscle were decomposed into single motor unit action potentials, from which the corresponding motor unit RT, MUCV and action potential amplitude were estimated. Established relations between muscle fibre diameter and CV were used to estimate the fibre size. Within individual subjects, the distributions of MUCV and fibre diameters were unimodal and did not show distinct populations. MUCV was strongly correlated with RT (mean (SD) R2 =0.7 (0.09), P<0.001; 406 motor units), which supported the hypothesis that fibre diameter is associated with RT. The results provide further evidence for the relations between motor neurone and muscle fibre properties for large samples of motor units. The proposed methodology for motor unit analysis has also the potential to open new perspectives in the study of chronic and acute neuromuscular adaptations to ageing, training and pathology.

P 157 Detection radius of EMG for fasciculations: combined ultrasonographic-electromyographic analysis

Background Fasciculations are caused by spontaneous discharges of single motor units. In electromyography (EMG), they are characterized by single motor unit action potentials. Muscle ultrasonography is increasingly applied as a non-invasive screening tool for the examination of fasciculations. In the context of motor neuron disease, the sensitivity of muscle ultrasonography to detect fasciculations was superior to EMG. Limited detection radius of concentric needle EMG may explain this discrepancy, but a direct EMG-ultrasonography-correlation of single fasciculations has not been reported so far. In the current study, we aimed to define an “EMG detection radius” of fasciculations by simultaneous recording of EMG and muscle ultrasonography. Methods Parallel to concentric needle EMG, we recorded in-plane high-resolution videos of muscle ultrasonography showing the needle tip within the transverse section of the muscle. A total of 200 fasciculations were acquired during 50 recordings of 10 patients with motor neuron disease. Amplitude and duration of EMG fasciculation potentials were subsequently correlated to the corresponding ultrasonographic muscle displacement and the distance from the EMG needle tip. Results The onset of ultrasonographic muscle displacement was concurrent to its EMG fasciculation potential whereas the plateau phase and the backward movement occurred when the EMG had already returned to baseline. About 40% of fasciculations observed on ultrasonography were not detected in EMG and this included fasciculations located close to the needle tip. The amplitude of EMG-positive fasciculations was negatively correlated to their distance from the needle tip. However, the correlation differed significantly between different patients and between different muscles. Discussion Analysis of fasciculations on simultaneous EMG and ultrasonography recordings improves the understanding of the “EMG-detection radius” of fasciculations. A relevant portion of ultrasonographic fasciculations was not detected on EMG which may in part explain the superior sensitivity of ultrasonography. Different localization of neuromuscular endplates and of myofibrils along the longitudinal axis of the analyzed muscles might explain the occurrence of “EMG-negative” fasciculations. Alternatively, muscle remodeling or changes of axon terminals due to neurodegeneration may alter the sensitivity of EMG. Further studies are needed to classify fasciculations of other entities with this method.

MP26-12 MOTOR UNIT NUMBER ESTIMATION OF THE PUBORECTALIS MUSCLE

You have accessJournal of UrologyUrodynamics/Lower Urinary Tract Dysfunction/Female Pelvic Medicine: Basic Research & Pathophysiology I1 Apr 2017MP26-12 MOTOR UNIT NUMBER ESTIMATION OF THE PUBORECTALIS MUSCLE Nicholas Dias, Yun Peng, Jinbao He, Charles Popeney, and Yingchun Zhang Nicholas DiasNicholas Dias More articles by this author , Yun PengYun Peng More articles by this author , Jinbao HeJinbao He More articles by this author , Charles PopeneyCharles Popeney More articles by this author , and Yingchun ZhangYingchun Zhang More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.783AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Motor unit number estimation (MUNE) techniques estimate the number of functioning motor units (MUs) in a muscle, and serve as a biomarker for neuromuscular and muscular atrophy. Application of current MUNE techniques to the pelvic floor is impractical because of the need for either multiple stimulations or invasive needle electrodes. The objective is to propose a novel MUNE technique applicable to pelvic floor muscles, by combining a high-density surface EMG (HD-sEMG) decomposition approach with pudendal nerve stimulation, negating the need for invasive needles or multiple stimulations. METHODS All procedures were approved by UH IRB. The pudendal nerve was stimulated transrectally with a St. Mark′s electrode mounted on the operator′s glove. HD-sEMG recordings were acquired from the puborectalis muscle with a vaginal EMG probe (Figure 1b) during supramaximal stimulation and three maximal voluntary contractions of pelvic floor muscles. Firstly, single motor unit action potentials (SMUPs) were decomposed from EMG recordings during muscle contraction using our recently developed K-Means Clustering Convolution Kernel Compensation (KmCKC) Algorithm. All SMUPs were grouped into left or right side by visually checking their innervation zone locations following an established procedure. Next, mean SMUPs were derived for both sides by averaging all HD-sEMG profiles of grouped SMUPs. Last, MUNE was calculated as the weighted average of compound muscle action potential (CMAP) size to mean SMUP size ratios for both sides. RESULTS Left and right branches of the pudendal nerve were simulated. Four SMUPs were decomposed from HD-sEMG signals (left: 3 and right: 1). MUNE for the left and right sides were 22.8 and 27.0, respectively. CONCLUSIONS This pilot study proves the feasibility of a novel MUNE technique for muscles in the pelvic floor region. The KmCKC algorithm enables a non-invasive collection of SMUPs, negating the need for repeated electrical stimulation or invasive needle electrodes. Results from more subjects will be available from our ongoing subject recruitment. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e324 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Nicholas Dias More articles by this author Yun Peng More articles by this author Jinbao He More articles by this author Charles Popeney More articles by this author Yingchun Zhang More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Recruitment of rat diaphragm motor units across motor behaviors with different levels of diaphragm activation

Phrenic motor neurons are recruited across a range of motor behaviors to generate varying levels of diaphragm muscle (DIAm) force. We hypothesized that DIAm motor units are recruited in a fixed order across a range of motor behaviors of varying force levels, consistent with the Henneman Size Principle. Single motor unit action potentials and compound DIAm EMG activities were recorded in anesthetized, neurally intact rats across different motor behaviors, i.e., eupnea, hypoxia-hypercapnia (10% O2 and 5% CO2), deep breaths, sustained airway occlusion, and sneezing. Central drive [estimated by root-mean-squared (RMS) EMG value 75 ms after the onset of EMG activity (RMS75)], recruitment delay, and onset discharge frequencies were similar during eupnea and hypoxia-hypercapnia. Compared with eupnea, central drive increased (∼25%) during deep breaths, and motor units were recruited ∼12 ms earlier (P < 0.01). During airway occlusion, central drive was ∼3 times greater, motor units were recruited ∼30 ms earlier (P < 0.01), and motor unit onset discharge frequencies were significantly higher (P < 0.01). Recruitment order of motor unit pairs observed during eupnea was maintained for 98%, 87%, and 84% of the same pairs recorded during hypoxia-hypercapnia, deep breaths, and airway occlusion, respectively. Reversals in motor unit recruitment order were observed primarily if motor unit pairs were recruited <20 ms apart. These results are consistent with DIAm motor unit recruitment order being determined primarily by the intrinsic size-dependent electrophysiological properties of phrenic motor neurons.

Effect of age and gender on the number of motor units in healthy subjects estimated by the multipoint incremental MUNE method.

Motor unit number estimation (MUNE) is a tool for estimating the number of motor units. The aim was to evaluate the multipoint incremental MUNE method in a healthy population, to analyze whether aging, gender, and the dominant hand side influence the motor unit number, and to assess reproducibility of MUNE with the Shefner modification. We studied 60 volunteers (mean age, 47 ± 17.7 years) in four groups aged 18 to 30, 31 to 45, 46 to 60, and above 60 years. Motor unit number estimation was calculated in the abductor pollicis brevis (APB) and the abductor digiti minimi (ADM) by dividing the single motor unit action potential amplitude into the maximal compound motor action potential amplitude. Test-retest variability was 7%. The mean value of MUNE for APB was 133.2 ± 43 and for ADM was 157.1 ± 39.4. Significant differences in MUNE results were found between groups aged 18 to 30 and 60 years or older and between groups aged 31 to 45 and 60 years or older. Motor unit number estimation results correlated negatively with the age of subjects for both APB and ADM. Single motor unit action potential, reflecting the size of motor unit, increased with the age of subjects only in APB. Compound motor action potential amplitude correlated negatively with the age of subjects in APB and ADM. Significant correlations were seen between MUNE in APB or ADM and compound motor action potential amplitude in these muscles and the age of female subjects. A similar relationship was not found in males. Multipoint incremental MUNE method with the Shefner modification is a noninvasive, easy to perform method with high reproducibility. The loss of motor neurons because of aging could be confirmed by our MUNE study and seems to be more pronounced in females.

The motor neuron response to SMN1 deficiency in spinal muscular atrophy

The purpose of this study was to measure and analyze motor unit number estimation (MUNE) values longitudinally in spinal muscular atrophy (SMA). Sixty-two children with SMA types 2 and 3 were observed prospectively for up to 42 months. Longitudinal electrophysiological data were collected, including compound motor action potential (CMAP), single motor unit action potential (SMUP), and MUNE. Significant motor neuron loss and compensatory collateral reinnervation were noted at baseline. Over time, there was a significant mean increase in MUNE (4.92 units/year, P = 0.009), a mean decrease in SMUP amplitude (-6.32 μV/year, P = 0.10), and stable CMAP amplitude. The unexpected longitudinal results differ from findings in amyotrophic lateral sclerosis studies, perhaps indicating that compensatory processes in SMA involve new motor unit development. A better understanding of the mechanisms of motor unit decline and compensation in SMA is important for assessing novel therapeutic strategies and for providing key insights into disease pathophysiology.

Evaluation of motor unit potential wavelet analysis in the electrodiagnosis of neuromuscular disorders

Electrophysiological studies of human motor units can use various electromyographic techniques. Together with the development of new techniques for analysis and processing of bioelectric signals, motor unit action potential (MUAP) wavelet analysis represents an important change in the development of electromyographic techniques. The proposed approach involves isolating single MUAPs, computing their scalograms, taking the maximum values of the scalograms in 5 selected scales, and averaging across MUAPs to give a single five-dimensional feature vector per muscle. After Support Vector Machine analysis, the feature vector is reduced to a single decision parameter that allows the subject to be assigned to 1 of 3 groups: myogenic, healthy, or neurogenic. The software is available as freeware. MUAP wavelet analysis yielded consistent results for the diagnostic index and muscle classification, with only 7 incorrect classifications out of a total of 1,015 samples. This proposed approach provides a sensitive and reliable method for evaluating and characterizing MUAPs.

Comparison of the motor discharge to the voluntary sphincters of continence in the rat

The rat external anal sphincter (EAS) and external urethral sphincter (EUS) are voluntary muscles of continence that can display similar synchronous electromyographic (EMG) activity patterns. However, the two sphincters are quite different in structure and function. The EUS is a fast twitch muscle and contains fibers expressing type 2B myosin. In contrast, the EAS exhibits slower kinetics and lacks type 2B fibers. This striking contrast in kinetics and fiber type profiles may be shaped by differences in the basal motor drive that each sphincter receives. A double EMG approach was used to obtain spontaneously active single motor unit action potentials from the EUS and EAS simultaneously and compare their basal discharge frequencies in urethane anaesthetized rats. The basal firing rates of motor units of the EUS and EAS were not significantly different (3.9 ± 0.9 Hz vs. 3.1 ± 1.6 Hz, respectively, n = 7 animals, P = 0.32, paired Student's t-test). However, auto-correlogram analysis showed that EUS is driven by neurons with faster instantaneous firing frequencies: 30.5 ± 2.4 Hz vs 14.3 ± 0.9 Hz in the EAS (P = 0.03, paired Student's t-test). The oscillator(s) driving the EUS operate(s) at a frequency twice that of the EAS. This may explain the presence of type 2B fibers in the EUS. In the inter-micturition periods no cross correlation was found in motor discharge to the sphincters suggesting that the two muscles do not share a common central drive to sustain the continent tonus of the two outlet tracts.

Cortical entrainment of human hypoglossal motor unit activities

Output from the primary motor cortex contains oscillations that can have frequency-specific effects on the firing of motoneurons (MNs). Whereas much is known about the effects of oscillatory cortical drive on the output of spinal MN pools, considerably less is known about the effects on cranial motor nuclei, which govern speech/oromotor control. Here, we investigated cortical input to one such motor pool, the hypoglossal motor nucleus (HMN), which controls muscles of the tongue. We recorded intramuscular genioglossus electromyogram (EMG) and scalp EEG from healthy adult subjects performing a tongue protrusion task. Cortical entrainment of HMN population activity was assessed by measuring coherence between EEG and multiunit EMG activity. In addition, cortical entrainment of individual MN firing activity was assessed by measuring phase locking between single motor unit (SMU) action potentials and EEG oscillations. We found that cortical entrainment of multiunit activity was detectable within the 15- to 40-Hz frequency range but was inconsistent across recordings. By comparison, cortical entrainment of SMU spike timing was reliable within the same frequency range. Furthermore, this effect was found to be intermittent over time. Our study represents an important step in understanding corticomuscular synchronization in the context of human oromotor control and is the first study to document SMU entrainment by cortical oscillations in vivo.

Multipoint incremental motor unit number estimation as an outcome measure in ALS

Improved outcome measures are necessary to reduce sample size and increase power in amyotrophic lateral sclerosis (ALS) clinical trials. Motor unit number estimation (MUNE) is a potentially attractive tool. MUNE methods previously employed in multicenter trials exhibited excessive variability and were prone to artifact. To evaluate a modification of standard incremental MUNE in a multicenter natural history study of subjects with ALS. Fifty healthy subjects were evaluated twice and 71 subjects with ALS were studied repeatedly for up to 500 days. Side and nerve studied was based on clinical examination findings. Nerves were stimulated at 3 specified locations and 3 increments were obtained at each location. Average single motor unit action potential (SMUP) amplitude was calculated by adding the amplitude of the third increment at each location and dividing by 9; SMUP was divided into maximum CMAP amplitude to determine the MUNE. Test-retest variability was 9% in normal subjects. Average MUNE for normal subjects was 225 (±87), and was 41.9 (±39) among subjects with ALS at baseline. Subjects with ALS showed clear decrements over time, with an overage rate of decline of approximately 9% per month. SMUP amplitude increased with time in a fashion consistent with the known pathophysiology of ALS. Multipoint incremental MUNE has a number of attributes that make it attractive as an outcome measure in ALS and other diseases characterized by motor unit loss. It can be rapidly performed on any EMG machine and has repeatability and rates of decline that favorably compare to other previously described methods.