Individual Motor Unit Action Potentials Research Articles

Motor unit firing rates during slow and fast contractions in boys and men.

Motor unit (MU) activation during maximal contractions is lower in children compared with adults. Among adults, discrete MU activation differs, depending on the rate of contraction. We investigated the effect of contraction rate on discrete MU activation in boys and men. Following a habituation session, 14 boys and 20 men completed two experimental sessions for knee extension and wrist flexion, in random order. Maximal voluntary isometric torque (MVIC) was determined before completing trapezoidal isometric contractions (70%MVIC) at low (10%MVIC/s) and high (35%MVIC/s) contraction rates. Surface electromyography was captured from the vastus lateralis (VL) and flexor carpi radialis (FCR) and decomposed into individual MU action potential (MUAP) trains. In both groups and muscles, the initial MU firing rate (MUFR) was greater (p < 0.05) at high compared with low contraction rates. The increase in initial MUFR at the fast contraction in the VL was greater in men than boys (p < 0.05). Mean MUFR was significantly lower during fast contractions only in the FCR (p < 0.05). In both groups and muscles, the rate of decay of MUFR with increasing MUAP amplitude was less steep (p < 0.05) during fast compared with slow contractions. In both groups and muscles, initial MUFRs, as well as MUFRs of large MUs were higher during fast compared with slow contractions. However, in the VL, the increase in initial MUFR was greater in men compared with boys. This suggests that in large muscles, men may rely more on increasing MUFR to generate torque at faster rates compared with boys.

Design and Test of an Intraoral Electrode Grid for Tongue High-Density Electromyography.

Tongue motor function is crucial in a wide range of basic activities and its impairment affects quality of life. The electrophysiological assessment of the tongue relies primarily on needle electromyography, which is limited by its invasiveness and inability to capture the concurrent activity of the different tongue muscles. This work aimed at developing an intraoral grid for high-density surface electromyography (HDsEMG) to non-invasively map the electrical excitation of tongue muscles. We developed a grid of 4×8 electrodes deposited over an adhesive 8- μ m thick polyurethane membrane. The testing protocol was conducted on 7 healthy participants and included functional tasks (vowels articulation and tongue movements) aimed at activating different regions of the tongue. The electrical stability of contact was assessed by measuring electrode-tongue impedances before and after the tasks. The spatial amplitude distribution of global EMG and single motor unit action potentials (MUAPs) was characterized. Electrode-tongue impedance magnitude showed no significant changes in the pre-post comparison ( 58±46 k Ω vs. 67±58 k Ω at 50Hz). Contact stability was confirmed by the quality of the signals that allowed to quantify spatiotemporal characteristics of muscle activation during the different tasks. The analysis of the spatial distribution of individual MUAPs amplitude showed that they were confined to relatively small areas on the tongue surface (range: 0.5cm2 -3.9cm [Formula: see text]. A variety of different spatiotemporal MUAP patterns, likely due to the presence of different muscle compartments with different fiber orientations, were observed. Our results demonstrate that the developed electrode grid enables HDsEMG acquisition from the tongue during functional tasks, thus opening new possibilities in tongue muscle assessment both at global and single motor unit level.

Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units

Objective. High-density surface electromyography (HD-sEMG) allows the reliable identification of individual motor unit (MU) action potentials. Despite the accuracy in decomposition, there is a large variability in the number of identified MUs across individuals and exerted forces. Here we present a systematic investigation of the anatomical and neural factors that determine this variability. Approach. We investigated factors of influence on HD-sEMG decomposition, such as synchronization of MU discharges, distribution of MU territories, muscle-electrode distance (MED—subcutaneous adipose tissue thickness), maximum anatomical cross-sectional area (ACSAmax), and fiber cross-sectional area. For this purpose, we recorded HD-sEMG signals, ultrasound and magnetic resonance images, and took a muscle biopsy from the biceps brachii muscle from 30 male participants drawn from two groups to ensure variability within the factors—untrained-controls (UT = 14) and strength-trained individuals (ST = 16). Participants performed isometric ramp contractions with elbow flexors (at 15%, 35%, 50% and 70% maximum voluntary torque—MVT). We assessed the correlation between the number of accurately detected MUs by HD-sEMG decomposition and each measured parameter, for each target force level. Multiple regression analysis was then applied. Main results. ST subjects showed lower MED (UT = 5.1 ± 1.4 mm; ST = 3.8 ± 0.8 mm) and a greater number of identified MUs (UT: 21.3 ± 10.2 vs ST: 29.2 ± 11.8 MUs/subject across all force levels). The entire cohort showed a negative correlation between MED and the number of identified MUs at low forces (r = −0.6, p = 0.002 at 15% MVT). Moreover, the number of identified MUs was positively correlated to the distribution of MU territories (r = 0.56, p = 0.01) and ACSAmax (r = 0.48, p = 0.03) at 15% MVT. By accounting for all anatomical parameters, we were able to partly predict the number of decomposed MUs at low but not at high forces. Significance. Our results confirmed the influence of subcutaneous tissue on the quality of HD-sEMG signals and demonstrated that MU spatial distribution and ACSAmax are also relevant parameters of influence for current decomposition algorithms.

Effects of hand muscle function and dominance on intra-muscle synergies.

The goal of the study was to explore the effects of hand dominance and muscle function (prime mover vs. supporting muscle) on recently discovered intra-muscle synergies as potential windows into their neural origin. Healthy right-handed subjects performed accurate cyclical force production tasks while pressing with the middle phalanges and distal phalanges of the fingers of the dominant and non-dominant hand. Surface electromyography was used to identify individual motor unit action potentials in two muscles, flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC). Stable motor unit groups (MU-modes) were defined in each muscle and in both muscles together. The composition of the MU-modes allowed linking them to the reciprocal and co-activation command. Force-stabilizing synergies were quantified in each hand and during force production at both sites using the framework of the uncontrolled manifold hypothesis. Force-stabilizing synergies were seen in the spaces of MU-modes from FDS and EDC separately, but not of MU-modes defined for both muscles together. Synergy indices were similar for both hands and both sites of force application. In contrast, force-stabilizing synergies in the space of finger forces were present in the non-dominant hand and absent in the dominant hand. The data suggest existence of distributed mechanisms of synergic control. Finger force synergies are likely to reflect functioning of subcortical loops involving the basal ganglia and cerebellum, while MU-mode synergies are likely to reflect spinal circuitry. Studies of both force-based and motor-unit-based synergies may be clinically valuable for distinguishing effects of spinal and supraspinal disorders.

Motor unit action potential amplitude during low torque fatiguing contractions versus high torque non-fatiguing contractions: a multilevel analysis.

The ability to maintain an absolute, submaximal torque level during fatiguing contractions is controlled, in part, by the recruitment of larger motor units. These motor units are commonly identified based on greater action potential peak-to-peak amplitude values. It is unclear, however, if motor unit action potential (MUAP) amplitude values during low torque, fatiguing contractions reach similar levels as those observed during non-fatigued, high torque contractions. To establish a clearer understanding of motor unit control during fatigue, we compared MUAP amplitude during 50 and 80% maximum voluntary contraction (MVC) torque contractions and at the beginning, middle, and end of a 30% MVC fatigue protocol. Eleven untrained men (mean age = 24years) performed isometric contractions at 50 and 80% MVC, followed by repeated contractions at 30% MVC. Surface electromyographic (EMG) signals were detected from the vastus lateralis and decomposed to quantify the peak-to-peak amplitude of individual MUAPs. A two-level multilevel model was estimated, allowing examination of simultaneous measures of MUAP amplitude within participants and controlling for the dependence between measures within participants. Results from the multilevel analyses suggested that there were not statistically significant differences in MUAP amplitude between 80% MVC and end fatigue. Separate repeated-measures analyses of variance indicated that there were not statistically significant mean differences in greatest MUAP or surface EMG amplitude between 80% MVC and end fatigue. MUAP and surface EMG amplitude values during a 30% MVC fatiguing protocol appear to be comparable to those observed during a non-fatigued 80% MVC condition.

Decomposing single-channel intramuscular electromyography signal sampled at a low frequency into its motor unit action potential trains with a generative adversarial network

Conventional methods decompose single-channel intramuscular electromyography (iEMG) signals into their constituent motor unit action potential trains (MUAPTs) by detecting and clustering individual motor unit action potentials (MUAPs). However, these methods are not applicable for iEMG signals recorded by electrodes with a large sensing areas or iEMG signals sampled at a low frequency, in which detecting and clustering individual MUAPs are difficult due to superimpositions of the MUAPs and the loss of MUAP morphological characteristics. In this study, we propose an approach based on a generative adversarial network to decompose iEMG signals, which does not depend on detecting and clustering individual MUAPs from the iEMG signal. The proposed approach decomposes the iEMG signal into its MUAPTs based on Bayes’ law and a Wasserstein generative adversarial network with gradient penalty (WGAN-GP). MUAPTs generated by the WGAN-GP were used to decompose the iEMG signal to maximize the posterior probability of the generated MUAPTs given the iEMG signal. The accuracy of the proposed approach is analysed directly by decomposing the simulated iEMG signal with seven gold-standard motor units. The results showed that the proposed approach achieved a 53% accuracy in capturing the firing regularities of the MUs, while the conventional method achieved a 37% accuracy on the same task.

Properties of the motor unit action potential shape in proximal and distal muscles of the upper limb in healthy and post-stroke individuals.

Spectral analysis of surface electromyograms (sEMG) is often used to estimate central and peripheral characteristics of a motor unit (MU) population, such as average conduction velocity, proportion of muscle fiber types, and pattern of MU recruitment. This estimation is based on the assumption that the sEMG adequately reflects the frequency characteristics of the underlying MU action potentials (MUAP). However, sEMG has limitations in this respect, based on physiological and non-physiological factors that influence its frequency content. We present a method to examine characteristics of a MU population more reliably by assessing the distributions of frequency content and amplitude for a collection of individual MUAPs, identified using high-density sEMG decomposition. We demonstrate the use of this approach to examine how MU characteristics differ across muscles and in the post-stroke state by presenting preliminary data from deltoid (DELT), biceps (BIC), and finger flexor (FF) MU populations from 12 post-stroke individuals and 8 able-bodied controls. The results show differences in the magnitude and range of MUAP median frequencies across muscles in both groups. The group median values were higher in the stroke group for the DELT and FF and lower in the stroke group for the BIC. The range of frequencies was larger in the stroke group for all muscles. The distribution of MUAP RMS amplitude in both stroke and control groups had a substantially larger range in FF than in DELT and BIC. The group median values for the FF were twice as large in the stroke group. In addition, there were differences in the frequency and amplitude results between MUAP and global sEMG analyses. The implications of these findings and possible applications of the approach are discussed.

Multi-channel intramuscular and surface EMG decomposition by convolutive blind source separation

Objective. The study of motor unit behavior has been classically performed by selective recording systems of muscle electrical activity (EMG signals) and decomposition algorithms able to discriminate between individual motor unit action potentials from multi-unit signals. In this study, we provide a general framework for the decomposition of multi-channel intramuscular and surface EMG signals and we extensively validate this approach with experimental recordings. Approach. First, we describe the conditions under which the assumptions of the convolutive blind separation model are satisfied. Second, we propose an approach of convolutive sphering of the observations followed by an iterative extraction of the sources. This approach is then validated using intramuscular signals recorded by novel multi-channel thin-film electrodes on the Abductor Digiti Minimi of the hand and Tibilias Anterior muscles, as well as on high-density surface EMG signals recorded by electrode grids on the First Dorsal Interosseous muscle. The validation was based on the comparison with the gold standard of manual decomposition (for intramuscular recordings) and on the two-source method (for comparison of intramuscular and surface EMG recordings) for the three human muscles and contraction forces of up to 90% MVC. Main results. The average number of common sources identified for the validation was 14 ± 7 (averaged across all trials and subjects and all comparisons), with a rate of agreement in their discharge timings of 92.8 ± 3.2%. The average Decomposability Index, calculated on the automatic decomposed signals, was 16.0 ± 2.2 (7.3–44.1). For comparison, the same index calculated on the manual decomposed signals was 15.0 ± 3.0 (6.3–76.6). Significance. These results show that the method provides a solid framework for the decomposition of multi-channel invasive and non-invasive EMG signals that allows the study of the behavior of a large number of concurrently active motor units.

Comparison of AR parametric methods with subspace-based methods for EMG signal classification using stand-alone and merged neural network models

This research introduces an electromyogram (EMG) pattern classication of individual motor unit action potentials (MUPs) from intramuscular electromyographi c signals. The presented technique automatically classies EMG patterns into healthy, myopathic, or neurogenic categories. To extract a feature vector from the EMG signal, we use different autoregressive (AR) parametric methods and subspace-based methods. The proposal was validated using EMG recordings composed of 1200 EMG patterns obtained from 7 healthy, 7 myopathic, and 13 neurogenic-disor people. A feedforward error backpropagation articial neural network (FEBANN) and combined neural network (CNN) were used for classication, where the success rate was slightly higher in CNN. Among the different AR and subspace methods used in this study, the highest performance was obtained with the eigenvector method. The following rates were the results achieved by using the CNN. The correct classication rate for EMG patterns was 97% for healthy, 93% for myopathic, and 92% for neurogenic patterns. The obtained accuracy for EMG signal classication is approximately 94% for CNN. The rates for FEBANN were as follows: 97% for healthy patterns, 92% for myopathic patterns, and 91% for neurogenic patterns. The obtained accuracy was 93.3%. By directly using raw EMG signals, EMG classications of healthy, myopathic, or neurogenic classes are automatically addressed.

Application of the F-Response for Estimating Motor Unit Number and Amplitude Distribution in Hand Muscles of Stroke Survivors.

The F-response was used in this study to assess changes in the first dorsal interosseous (FDI) muscle after a hemispheric stroke. The number of motor units and their sizes were estimated bilaterally in 12 stroke survivors by recording both the compound muscle action potential (CMAP) and F wave responses. These F waves were induced by applying a large number of electrical stimuli to the ulnar nerve. The amplitude distribution of individual motor unit action potentials (MUAPs) was also compared between paretic and contralateral muscles. When averaged across all the subjects, a significantly lower motor unit number estimate was obtained for the paretic FDI muscle ( 88 ±13) compared with the contralateral side ( 139 ±11) ( ). Pooled surface MUAP amplitude analysis demonstrated a right-skewed distribution for both paretic (kurtosis 3.0) and contralateral (kurtosis 8.52) muscles. When normalized to each individual muscle's CMAP, the surface MUAP amplitude ranged from 0.22% to 4.94% (median 1.17%) of CMAP amplitude for the paretic muscle, and from 0.13% to 3.2% (median 0.62%) of CMAP amplitude for the contralateral muscle. A significant difference in MUAP outliers was also observed between the paretic and contralateral muscles. The findings of this study suggest significant motor unit loss and muscle structural reorganization after stroke.

Changes in motor unit behavior following isometric fatigue of the first dorsal interosseous muscle.

The neuromuscular strategies employed to compensate for fatigue-induced muscle force deficits are not clearly understood. This study utilizes surface electromyography (sEMG) together with recordings of a population of individual motor unit action potentials (MUAPs) to investigate potential compensatory alterations in motor unit (MU) behavior immediately following a sustained fatiguing contraction and after a recovery period. EMG activity was recorded during abduction of the first dorsal interosseous in 12 subjects at 20% maximum voluntary contraction (MVC), before and directly after a 30% MVC fatiguing contraction to task failure, with additional 20% MVC contractions following a 10-min rest. The amplitude, duration and mean firing rate (MFR) of MUAPs extracted with a sEMG decomposition system were analyzed, together with sEMG root-mean-square (RMS) amplitude and median frequency (MPF). MUAP duration and amplitude increased immediately postfatigue and were correlated with changes to sEMG MPF and RMS, respectively. After 10 min, MUAP duration and sEMG MPF recovered to prefatigue values but MUAP amplitude and sEMG RMS remained elevated. MU MFR and recruitment thresholds decreased postfatigue and recovered following rest. The increase in MUAP and sEMG amplitude likely reflects recruitment of larger MUs, while recruitment compression is an additional compensatory strategy directly postfatigue. Recovery of MU MFR in parallel with MUAP duration suggests a possible role for metabolically sensitive afferents in MFR depression postfatigue. This study provides insight into fatigue-induced neuromuscular changes by examining the properties of a large population of concurrently recorded single MUs and outlines possible compensatory strategies involving alterations in MU recruitment and MFR.

Automatic detection of motor unit innervation zones of the external anal sphincter by multichannel surface EMG

A method to detect automatically the location of innervation zones (IZs) from 16-channel surface EMG (sEMG) recordings from the external anal sphincter (EAS) muscle is presented in order to guide episiotomy during child delivery. The new algorithm (2DCorr) is applied to individual motor unit action potential (MUAP) templates and is based on bidimensional cross correlation between the interpolated image of each MUAP template and two images obtained by flipping upside-down (around a horizontal axis) and left–right (around a vertical axis) the original one. The method was tested on 640 simulated MUAP templates of the sphincter muscle and compared with previously developed algorithms (Radon Transform, RT; Template Match, TM). Experimental signals were detected from the EAS of 150 subjects using an intra-anal probe with 16 equally spaced circumferential electrodes. The results of the three algorithms were compared with the actual IZ location (simulated signal) and with IZ location provided by visual analysis (VA) (experimental signals). For simulated signals, the inter quartile error range (IQR) between the estimated and the actual locations of the IZ was 0.20, 0.23, 0.42, and 2.32 interelectrode distances (IED) for the VA, 2DCorr, RT and TM methods respectively.

Neuromuscular remodeling and neuromuscular junction instability in human diabetic neuropathy (1168.1)

Diabetic polyneuropathy (DPN) is a progressive axonopathy marked by loss of motor fibers, compensatory collateral reinnervation and reduced stability of neuromuscular transmission. Our objective was to assess the degree of reinnervation and motor unit instability in patients with DPN using decomposition‐based quantitative electromyography (DQEMG). Additionally, relationships between motor unit stability and muscle function were examined. The tibialis anterior (TA) muscle was tested in twelve patients with DPN (65 ± 15 yrs) and 12 age‐matched controls (63 ± 15 yrs). DQEMG was used to analyze surface and intramuscular EMG signals recorded from the TA during moderate voluntary dorsiflexion contractions. Individual motor unit action potential (MUP) trains were identified and analyzed for: MUP size (peak to peak amplitude, area), complexity (turns, fiber dispersion) and stability (near fiber jiggle). DPN patients featured larger (+45% MUP area), more complex (+40% fiber dispersion), and less stable (+30% near fiber jiggle) MUPs (p&lt;0.05). No significant relationships were found between MUP stability and muscular denervation, or strength. MUP complexity and instability were positively related in DPN patients (r=0.46; p&lt;0.05) and controls (r=0.37; p&lt;0.05). DPN is associated with neuromuscular remodeling which leads to increasingly impaired neuromuscular transmission that is detectable using DQEMG.Grant Funding Source: NSERC

Combined Cystometrography and Electromyography of the External Urethral Sphincter Following Complete Primary Repair of Bladder Exstrophy

Concern in patients with bladder exstrophy after reconstruction regarding potential injury to pelvic neurourological anatomy and a resultant functional deficit prompted combined (simultaneous) cystometrography and electromyography after complete primary repair of bladder exstrophy. We determined whether complete primary repair of bladder exstrophy would adversely affect the innervation controlling bladder and external urethral sphincter function. Complete primary repair of bladder exstrophy was performed via a modified Mitchell technique in newborns without osteotomy. Postoperative evaluation included combined cystometrography and needle electrode electromyography via the perineum, approximating the external urethral sphincter muscle complex. Electromyography was done to evaluate the external urethral sphincter response to sacral reflex stimulation and during voiding. Nine boys and 4 girls underwent combined cystometrography/electromyography after complete primary repair of bladder exstrophy. Age at study and time after complete primary repair of bladder exstrophy was 3 months to 10 years (median 11.5 months). Cystometrography revealed absent detrusor overactivity and the presence of a sustained detrusor voiding contraction in all cases. Electromyography showed universally normal individual motor unit action potentials of biphasic pattern, amplitude and duration. The external urethral sphincter sacral reflex response was intact with a normal caliber with respect to Valsalva, Credé, bulbocavernosus and anocutaneous (bilateral) stimulation. Synergy was documented by abrupt silencing of external urethral sphincter electromyography activity during voiding. After complete primary repair of bladder exstrophy combined cystometrography/electromyography in patients with bladder exstrophy showed normal neurourological findings, including sacral reflex responses, sustained detrusor voiding contraction and synergic voiding, in all patients postoperatively. These findings confirm the safety of complete primary repair of bladder exstrophy. Based on our results we have discontinued routine electromyography in these patients.

Electrophysiological method to examine muscle fiber architecture in the upper lip in cleft-lip patients

The upper lip's musculature comprises several muscle fiber groups with different spatial orientations for various lip movements. In the past, it has not been possible to describe these various groups and their motor units in detail with traditional methods of electromyography (EMG). The purpose of this investigation was to create a viable method for studying the architecture of upper-lip muscle fibers in patients with surgically closed cleft lip by refining the design of a flexible electrode array for multichannel EMG. Calibrated perioral photographs of 36 adult subjects were used to determine the basic geometry of an electrode array for use on different facial shapes. A total of 256 chloride silver electrodes, 1 mm in diameter, were distributed over this geometry to form a grid with interelectrode distances of 2.5 mm. Technical implementation of the electrode array was based on a modified technique used for flexible printed circuit boards. A double-sided adhesive tape with perforations was used to apply the array to the skin in the upper-lip area. Surface EMG signals were recorded while the subjects were performing various lip movements and exerting specific lip forces. The latter were recorded with a specially developed transducer. Despite an extremely dense grid of electrodes associated with downsized contacts, the electrode array could be precisely applied to the perforated adhesive tape. The electrode array remained firmly attached to the skin even during extensive lip movements. The recorded EMG signals offered high baseline stability and a strong signal-to-noise ratio, thus, allowing us to extract individual motor unit action potentials (MUAPs). Spatiotemporal tracking of MUAPs succeeded in demonstrating the course of muscle fibers belonging to individual motor units. Pilot measurements taken on subjects with surgically closed unilateral cleft lip revealed an asymmetric distribution of muscle activity surrounding the closed cleft-lip segments. Our refined noninvasive electrophysiological method is capable of providing detailed information about muscle fiber architecture and the position, size, and organization of motor units in the lip area. It is thus feasible to conduct further studies to analyze differences in muscle morphology and motor control between surgically treated cleft-lip patients and noncleft individuals.

Recruitment of motor units in two fascicles of the semispinalis cervicis muscle

This study investigated the behavior of motor units in the semispinalis cervicis muscle. Intramuscular EMG recordings were obtained unilaterally at levels C2 and C5 in 15 healthy volunteers (8 men, 7 women) who performed isometric neck extensions at 5%, 10%, and 20% of the maximal force [maximum voluntary contraction (MVC)] for 2 min each and linearly increasing force contractions from 0 to 30% MVC over 3 s. Individual motor unit action potentials were identified. The discharge rate and interspike interval variability of the motor units in the two locations did not differ. However, the recruitment threshold of motor units detected at C2 (n = 16, mean ± SD: 10.3 ± 6.0% MVC) was greater than that of motor units detected at C5 (n = 92, 6.9 ± 4.3% MVC) (P < 0.01). A significant level of short-term synchronization was identified in 246 of 307 motor unit pairs when computed within one spinal level but only in 28 of 110 pairs of motor units between the two levels. The common input strength, which quantifies motor unit synchronization, was greater for pairs within one level (0.47 ± 0.32) compared with pairs between levels (0.09 ± 0.07) (P < 0.05). In a second experiment on eight healthy subjects, interference EMG was recorded from the same locations during a linearly increasing force contraction from 0 to 40% MVC and showed significantly greater EMG amplitude at C5 than at C2. In conclusion, synaptic input is distributed partly independently and nonuniformly to different fascicles of the semispinalis cervicis muscle.

Assessment of the Electrophysiological Properties of the Muscle Fibers of a Transplanted Hand

The muscle fibers in a transplanted hand remain denervated for a long period of time after the transplant. This prolonged inactivity may change the electrophysiological membrane properties of muscle fibers, as observed in long-term denervation. We investigated whether electrophysiological properties of the muscle fibers are preserved in a transplanted hand even after several months of denervation. Specifically, we assessed the dependence of muscle fiber conduction velocity (CV) on discharge rate in motor units of the abductor digiti minimi muscle. Surface electromyography signals were recorded from the transplanted hand of a patient who was 35 years of age at the time of the transplant. In each of 11 experimental sessions performed over a period of 23 months after the transplant, the subject was asked to linearly increase the activation or to maintain a maximum activation of the abductor digiti minimi muscle for 60 sec. Individual motor unit action potentials were identified from the electromyography recordings and muscle fiber CV was estimated for each action potential as a function of the time interval separating the action potential from the preceding discharge (interspike interval [ISI]). The baseline (ISI >1000 msec) CV was 3.8±0.3 m/sec. CV decreased monotonically with increasing ISI (R=0.95). For ISI in the range 0 to 10 msec, muscle fiber CV was 24.9%±16.3% higher than the baseline value (P<0.05). The results indicate that in the investigated muscle, the baseline value of CV and its dependency on discharge rate were similar as in able-bodied individuals, despite a period of several months of denervation.

Application of time-varying analysis to diagnostic needle electromyography

Quantification in clinical, diagnostic electromyography (EMG) currently includes motor unit action potential (MUAP) analysis and interference pattern analysis. Early efforts to examine the frequency/power spectra of the interference pattern showed modest value but the technique was not developed further. This paper re-examines spectral analysis, extending it into the time-varying domain, which has never been studied in diagnostic needle EMG. Time–frequency and time-scale analysis employing wavelet and non-wavelet techniques were applied to short trains of MUAPs. The results show that time-varying analysis produces clear visual representations of the energy content of individual MUAPs within an interference pattern. The time frequency representations allow easy, qualitative distinction between normal and neurogenic MUAPs. Furthermore, the quantified MUAP energy correlates well with the current morphological standard and the quantification process is substantially faster. Time-varying analysis links classical power spectral analysis in the realm of interference patterns with quantitative MUAP analysis. In addition to morphological classification, MUAPs might also be classified by energy content, which more closely reflects the physical and physiological consequences of neuromuscular pathology on the motor unit.

Changes in motor unit characteristics after eccentric elbow flexor exercise

Morphological evidence suggests that fast-twitch fibers are prone to disruption of their membrane structures by eccentric exercise. However, it is unclear how this is reflected in the discharge rate and action potential propagation of individual motor units, especially at high contraction levels. High-density surface electromyograms were recorded from biceps brachii muscle and decomposed to individual motor unit action potentials at isometric contraction levels between 10% and 75% of maximal voluntary contraction (MVC) before intermittent maximal elbow flexor eccentric exercise, and two hours (2H), two days (2D) and four days (4D) post-exercise. Maximal voluntary force decreased by 21.3±5.6% 2H and by 12.6±11.1% 2D post-exercise. Motor unit discharge rate increased and mean muscle fiber conduction velocity decreased, at the highest isometric contraction levels only (50% and 75% of MVC) at 2H post-exercise. These results indicate that eccentric exercise can disturb the function of motor units active at high contraction levels in the early stages after exercise, which seems to be compensated by the central nervous system with an increase in neural drive during submaximal isometric contractions.

Poisson distribution to analyze near‐threshold motor evoked potentials

Motor unit action potentials (MUAPs) evoked by repetitive, low-intensity transcranial magnetic stimulation can be modeled as a Poisson process. A mathematical consequence of such a model is that the ratio of the variance to the mean of the amplitudes of motor evoked potentials (MEPs) should provide an estimate of the mean size of the individual MUAPs that summate to generate each MEP. We found that this is, in fact, the case. Our finding thus supports the use of the Poisson distribution to model MEP generation and indicates that this model enables characterization of the motor unit population that contributes to near-threshold MEPs.