Motor Unit Synchronization Research Articles

Electromyographic traces of motor unit synchronization of fatigued lower limb muscles during gait.

The study of the signal in the frequency domain has shown to be a good tool to identify muscular fatigue. Previous research has shown that the low frequency band and 40Hz frequency band increase their relative intensity with the onset of fatigue. These findings were obtained in rectus femoris, but the behaviours of other muscles of the lower limb are unknown. In this article we explored the changes in the low frequency and 40Hz frequency band of lower limb muscles with respect to fatigue. Thirty healthy subjects were recruited to analyse the electromyography (EMG) of biceps femoris, tibialis anterior and gastrocnemius medialis and lateralis of both legs during gait. Four two-minutes walks at a self-selected speed were recorded, the first two walks with a normal muscular function and the last two walks after a fatigue protocol. All the signals were decomposed using wavelet transformations. The signals were normalized in time and spectral intensities normalized to the sum of intensities in the frequency domain. Two frequency bands were studied in each walk: the 40-Hz (34-53Hz) and the low frequency (< 25Hz) bands. A ratio of the spectral intensities of those frequency bands at each walk was obtained by dividing the 40-Hz frequency band spectral intensity by the low frequency band spectral intensity. Statistical parametric mapping techniques were used to compare the ratios of the prefatigue walks against the postfatigue walks. The results of the Statistical Non-Parametric Mapping (SnPM) analysis of all muscles depict a higher relative spectral intensity in the low frequency band in the comparison of fatigue versus prefatigue recordings except for the right gastrocnemius lateralis. The critical thresholds F* were exceeded by multiple suprathreshold clusters with p values <0.05, showing that the low frequency band increased its relative spectral intensity in the case of fatigue. The obtained results suggest that the low frequency band increases its relative spectral intensity in all the studied muscles when fatigue onsets. This increase in relative spectral intensity may be linked to an increase in motor unit synchronization promoted by the central nervous system to ensure good motor control.

Motor unit filter prelearning strategies for decomposition of compound muscle action potentials in high-density surface electromyograms.

We analyze the efficiency of motor unit (MU) filter prelearning from high-density surface electromyographic (HDEMG) recordings of voluntary muscle contractions in the identification of the motor unit firing patterns during elicited muscle contractions. Motor unit filters are assessed from 10 s long low level isometric voluntary contractions by gradient-based optimization of three different cost functions and then applied to synthetic HDEMG recordings of elicited muscle contractions with dispersion of motor unit firings ranging from 13 ms to 1 ms. We demonstrate that the number of identified MUs and the precision of MU identification depend significantly on the selected cost function. Regardless the selected cost function and MU synchronization level, the median precision of motor unit identification in elicited contraction is ≥ 95 % and is comparable to the precision in voluntary contractions. On the other hand, median miss rate increases significantly from < 1 % to ~ 3 % with the tested level of MU synchronization.Clinical Relevance-The identification of MU firings from HDEMG in elicited muscle contractions provides a new tool for in vivo investigation of motor excitability in humans.

MotoRneuron: an open-source R toolbox for time-domain motor unit analyses

Motor unit synchronization is the tendency of motor neurons and their associated muscle fibers to discharge near-simultaneously. It has been theorized as a control mechanism for force generation by common excitatory inputs to these motor neurons. Magnitude of synchronization is calculated from peaks in cross-correlation histograms between motor unit discharge trains. However, there are many different methods for detecting these peaks and even more indices for calculating synchronization from them. Methodology is diverse, typically laboratory-specific and requires expensive software, like Matlab or LabView. This lack of standardization makes it difficult to draw definitive conclusions about motor unit synchronization. A free, open-source toolbox, “motoRneuron”, for the R programming language, has been developed which contains functions for calculating time domain synchronization using different methods found in the literature. The objective of this paper is to detail the toolbox’s functionality and present a case study showing how the same synchronization index can differ when different methods are used to compute it. A pair of motor unit action potential trains were collected from the forearm during a isometric finger flexion task using fine wire electromyography. The motoRneuron package was used to analyze the discharge time of the motor units for time-domain synchronization. The primary function “mu_synch” automatically performed the cross-correlation analysis using three different peak detection methods, the cumulative sum method, the z-score method, and a subjective visual method. As function parameters defined by the user, only first order recurrence intervals were calculated and a 1 ms bin width was used to create the cross correlation histogram. Output from the function were six common synchronization indices, the common input strength (CIS), k′, k′ − 1, E, S, and Synch Index. In general, there was a high degree of synchronization between the two motor units. However, there was a varying degree of synchronization between methods. For example, the widely used CIS index, which represents a rate of synchronized discharges, shows a 45% difference between the visual and z-score methods. This singular example demonstrates how a lack of consensus in motor unit synchronization methodologies may lead to substantially differing results between studies. The motoRneuron toolbox provides researchers with a standard interface and software to examine time-domain motor unit synchronization.

Beta-band motor unit coherence and nonlinear surface EMG features of the first dorsal interosseous muscle vary with force.

Motor unit firing times are weakly coupled across a range of frequencies during voluntary contractions. Coherent activity within the beta-band (15-35 Hz) has been linked to oscillatory cortical processes, providing evidence of functional connectivity between the motoneuron pool and motor cortex. The aim of this study was to investigate whether beta-band motor unit coherence is altered with increasing abduction force in the first dorsal interosseous muscle. Coherence between motor unit firing times, extracted from decomposed surface electromyography (EMG) signals, was investigated in 17 subjects at 10, 20, 30, and 40% of maximum voluntary contraction. Corresponding changes in nonlinear surface EMG features (specifically sample entropy and determinism, which are sensitive to motor unit synchronization) were also examined. A reduction in beta-band and alpha-band coherence was observed as force increased [F(3, 151) = 32, P < 0.001 and F(3, 151) = 27, P < 0.001, respectively], accompanied by corresponding changes in nonlinear surface EMG features. A significant relationship between the nonlinear features and motor unit coherence was also detected (r = -0.43 ± 0.1 and r = 0.45 ± 0.1 for sample entropy and determinism, respectively; both P < 0.001). The reduction in beta-band coherence suggests a change in the relative contribution of correlated and uncorrelated presynaptic inputs to the motoneuron pool, and/or a decrease in the responsiveness of the motoneuron pool to synchronous inputs at higher forces. The study highlights the importance of considering muscle activation when investigating changes in motor unit coherence or nonlinear EMG features and examines other factors that can influence coherence estimation.NEW & NOTEWORTHY Intramuscular alpha- and beta-band coherence decreased as muscle contraction force increased. Beta-band coherence was higher in groups of high-threshold motor units than in simultaneously active lower threshold units. Alterations in motor unit coherence with increases or decreases in force and with the onset of fatigue were accompanied by corresponding changes in surface electromyography sample entropy and determinism. Mixed-model analysis indicated mean firing rate and number of motor units also influenced the coherence estimate.

Single channel surface electromyogram deconvolution to explore motor unit discharges

Interference surface electromyogram (EMG) reflects many bioelectric properties of active motor units (MU), which are however difficult to estimate due to the asynchronous summation of their discharges. This paper introduces a deconvolution technique to estimate the cumulative firings of MUs. Tests in simulations show that the power spectral density of the estimated MU firings has a low-frequency peak corresponding to the mean firing rate of MUs in the detection volume of the recording system, weighted by the amplitudes of MU action potentials. The peak increases in amplitude and its centroid shifts to a higher frequency when MU synchronization is simulated (mainly due to the shift of discharges of large MUs). The peak is found even at high force levels, when such a contribution does not emerge from the EMG. This result is also confirmed in preliminary applications to experimental data. Moreover, the simulated cumulative firings of MUs are estimated with a correlation above 90% (considering frequency contributions up to 150 Hz), for all force levels. The method requires a single EMG channel, thus being feasible even in applied studies using simple recording systems. It may open many potential applications, e.g., in the study of the modulation of MU firing rate induced by either fatigue or pathology and in coherency analysis. Graphical Abstract Examples of application of the deconvolution (Deconv) algorithm and comparison with the cumulative firings and the cumulated weighted firings (CWF, i.e., each firing pattern is weighted by the root mean squared amplitude of the corresponding MU action potential). Portions of data are shown on the left, the power spectral densities (PSD) on the right (Welch method applied to 3 s of data, sub-epochs of 0.5 s, mean value removed from each of them, 50% of overlap). A) Simulated signal (50% of maximal voluntary contraction, MVC) with random MU firings. B) Simulated signal (50% MVC) with a level of synchronization equal to 10%. C) Experimental data from vastus medialis at 40% MVC (data decomposed by the algorithm of Holobar and Zazula, IEEE Trans. Sig. Proc. 2007; PSD of the cumulated firings almost identical to that of CWF, as few MUs were identified).

The Influence of Force Level and Motor Unit Coherence on Nonlinear Surface EMG Features Examined Using Model Simulation.

Nonlinear features extracted from surface EMG signals have been previously used to infer information on coherent or synchronous activity in the underlying motor unit discharges. However, it has not yet been assessed how these features are affected by the density of the surface EMG signal, and whether changes in the level of muscle activation can influence the effective detection of correlated motor unit firing. To examine this, a motoneuron pool model receiving a beta-band modulated cortical input was used to generate correlated motor unit firing trains. These firing trains were convolved with motor unit action potentials generated from an anatomically accurate electrophysiological model of the first dorsal interosseous muscle. The sample entropy (SampEn) and percentage determinism (%DET) of recurrence quantification analysis were calculated from the composite surface EMG signals, for signals comprised of both correlated and uncorrelated motor unit firing trains. The results show that although both SampEn and %DET are influenced by motor unit coherence, they are differentially affected by muscle activation and motor unit distribution. The results also suggest that sample entropy may provide a more accurate assessment of the underlying motor unit coherence than percentage determinism, as it is less sensitive to factors unrelated to motor unit synchrony.

Analysis of Dynamic Contractions from Biceps Brachii Muscle using Surface Electromyography signals and Multiscale Visibility Graph Features.

In this work, an attempt is made to characterize the variation in the complexity of the surface electromyography (sEMG) signals in fatigue. For this, sEMG signals from 58 healthy volunteers are recorded from the biceps brachii muscle under well-defined dynamic contraction protocol. The contractions are segmented, and the initial and final curls are extracted. These are considered as nonfatigue and fatigue respectively. Further, visibility graphs are constructed at multiple scales, and median degree centrality (MSMC) is calculated in them. To quantify the variations in the MSMC, two features namely, the average and standard deviation are calculated. The results reveal that the recorded signals are non-stationary. The constructed networks form distinct clusters in space. The MSMC feature shows a decreasing trend with scale in both nonfatigue and fatigue conditions. Additionally, the extracted features have higher values in fatigue. This may be due to the motor unit synchronization, which causes an increase in connectivity between nodes. All the extracted features showed statistical significance with p<; 0.005. This approach of analysis can be extended to characterize muscle in other neuromuscular conditions.

Investigation of The Neural Drive During Vibration Exercise by High-density Surface-electromyography.

Mechanical vibration applied directly to the muscle belly or tendon has been reported to elicit a specific reflex loop named tonic vibration reflex (TVR), which involves motor unit (MU) activation synchronized and un-synchronized within the vibration cycle. Indirect application of vibration to the muscle by vibration exercise (VE) has also been suggested to evoke TVR, as evidenced by the spectral peaks observed at the vibration frequency in the surface electromyography (sEMG). However, other studies interpreted these spectral peaks as the result of motion artifacts (MAs). The aim of the present study is, therefore, to investigate MU activation patterns during VE in order to clarify the nature of those spectral peaks. To this end, low-intensity isometric contractions were executed with and without VE, and high-density sEMG measurements were performed during the contraction tasks. MU action potential (MUAP) trains were extracted by decomposing the recorded high-density sEMG signals. The spectra of the MUAP trains were then calculated and compared between vibration and no-vibration conditions. Clear MU synchronization was observed during VE, confirming the spectral peaks at the vibration frequency to be mainly due to the reflex loop rather than MAs.

The relative strength of common synaptic input to motor neurons is not a determinant of the maximal rate of force development in humans.

Correlation between motor unit discharge times, often referred to as motor unit synchronization, is determined by common synaptic input to motor neurons. Although it has been largely speculated that synchronization should influence the rate of force development, the association between the degree of motor unit synchronization and rapid force generation has not been determined. In this study, we examined this association with both simulations and experimental motor unit recordings. The analysis of experimental motor unit discharges from the tibialis anterior muscle of 20 healthy individuals during rapid isometric contractions revealed that the average motor unit discharge rate was associated with the rate of force development. Moreover, the extent of motor unit synchronization was entirely determined by the average motor unit discharge rate (R > 0.7, P < 0.0001). The simulation model demonstrated that the relative proportion of common synaptic input received by motor neurons, which determines motor unit synchronization, does not influence the rate of force development (R = 0.03, P > 0.05). Nonetheless, the estimates of correlation between motor unit spike trains were significantly correlated with the rate of force generation (R > 0.8, P < 0.0001). These results indicate that the average motor unit discharge rate, but not the degree of motor unit synchronization, contributes to most of the variance of human contractile speed among individuals. In addition, estimates of correlation between motor unit discharge times depend strongly on the number of identified motor units and therefore are not indicative of the strength of common input. NEW & NOTEWORTHY It is commonly assumed that motor unit synchronization has an impact on the rate of force development of a muscle. Here we present computer simulations and experimental data of human tibialis anterior motor units during rapid contractions that show that motor unit synchronization is not a determinant of the rate of force production. This conclusion clarifies the neural determinants of rapid force generation.

Maturation of feedforward toe walking motor program is impaired in children with cerebral palsy.

Voluntary toe walking in adults is characterized by feedforward control of ankle muscles in order to ensure optimal stability of the ankle joint at ground impact. Toe walking is frequently observed in children with cerebral palsy, but the mechanisms involved have not been clarified. Here, we investigated maturation of voluntary toe walking in typically-developing children and typically-developed adults and compared it to involuntary toe walking in children with cerebral palsy. Twenty-eight children with cerebral palsy (age 3-14 years), 24 typically-developing children (age 2-14 years) and 15 adults (mean age 30.7 years) participated in the study. EMG activity was measured from the tibialis anterior and soleus muscles together with knee and ankle joint position during treadmill walking. In typically-developed adults, low step-to-step variability of the drop of the heel after ground impact was correlated with low tibialis anterior and high soleus EMG with no significant coupling between the antagonist muscle EMGs. Typically-developing children showed a significant age-related decline in EMG amplitude reaching an adult level at 10-12 years of age. The youngest typically-developing children showed a broad peak EMG-EMG synchronization (>100 ms) associated with large 5-15 Hz coherence between antagonist muscle activities. EMG coherence declined with age and at the age of 10-12 years no correlation was observed similar to adults. This reduction in coherence was closely related to improved step-to-step stability of the ankle joint position. Children with cerebral palsy generally showed lower EMG levels than typically-developing children and larger step-to-step variability in ankle joint position. In contrast to typically-developing children, children with cerebral palsy showed no age-related decline in tibialis anterior EMG amplitude. Motor unit synchronization and 5-15 Hz coherence between antagonist EMGs was observed more frequently in children with cerebral palsy when compared to typically-developing children and in contrast to typically-developing participants there was no age-related decline. We conclude that typically-developing children develop mature feedforward control of ankle muscle activity as they age, such that at age 10-12 years there is little agonist-antagonist muscle co-contraction around the time of foot-ground contact during toe walking. Children with cerebral palsy, in contrast, continue to co-contract agonist and antagonist ankle muscles when toe walking. We speculate that children with cerebral palsy maintain a co-contraction activation pattern when toe walking due to weak muscles and insufficient motor and sensory signalling necessary for optimization of feedforward motor programs. These findings are important for understanding of the pathophysiology and treatment of toe walking.

Mirror therapy can promote the activation and synchronization of lower-limb muscles after stroke

Objective To explore the effects of mirror therapy on the lower-limb muscles of hemiplegic stroke survivors. Methods Sixty-two hemiplegic stroke survivors were divided by stratified random grouping into a mirror group and a control group, each of 31. Both groups accepted routine rehabilitation training, while the mirror group was additionally provided with mirror therapy to train the non-paretic limb for 30 min per day, 5 days a week, lasting 4 weeks. Before and after the 4 weeks of training, integrated electromyography was performed and the maximum voluntary contraction force (MVC) of the tibialis anterior, rectus femoris and biceps femoris of the paretic limb were recorded and compared. Results Compared with before the training, the average root mean square values of the electromyographs and the average MVCs of all three muscles had improved significantly in both groups after training. Compared with the control group, the improvements were significantly greater in the mirror group. Conclusion Mirror therapy can promote the activation and synchronization of motor units, as well as increase the number discharging and the total discharge, promoting the recovery of muscle strength. Key words: Surface electromyography; Mirror therapy; Stroke; Hemiplegia; Lower limbs

PO-243 Correlation between exercise performance and muscle electrical activity in Exercise-induced Fatigue Rats

Objective Assess the muscle contraction ability of rats before and after exercise fatigue quantitatively, and analyze the correlation between exercise performance and muscle electrical activity. This study intends to provide a theoretical principle for exercise fatigue.&#x0D; Methods 7 healthy adult male SD rats (300~350g) were used and trained for adaptive treadmill by running on the treadmill for 1 week and holding on a vertical rectangular railing (20×10cm, 10 iron bars) until it's mastered. After this training, we used rat grasping force tester( BioSEB GS3) to measure the maximum grasping force(MGF) of rat's limbs, each rat was carried out 3 times, bout interval is 2 minutes. In addition, the grasping bar time(GBT) was recorded 3 times , bout interval is 30 minutes. We let rats to grasp and hold on a vertical rectangular railing(20×10cm， 10 iron bars), evaluation of rat muscular endurance by grasping bar time(GBT), each rat was carried out 3 times, bout interval is 30 minutes; During the MGF and GBT test, motor unit recruitment and discharge frequency was predicted by measuring the EMG of extensor muscles of the right hindlimb and flexor elbow muscles of the right forelimb by wireless non-invasive miniature surface EMG tester (Italy, BTS FREEEMG), the max Root Mean Square (maxRMS) and Median Frequency (MF) parameter was used to evaluate motor unit recruitment and discharge frequency, respectively.&#x0D; After these, the rats were allowed to have a one-day rest, and then had a load motion program on the treadmill (three levels’ load: the first stage movement speed 8.2 m/min, exercise time 15 min; second stage speed 15 m/min, exercise time 15 min; third stage speed at 20 m/min, exercise to fatigue ) to build the rats EF model by monitoring the acceleration of the rat's sprint with a miniature wireless acceleration sensor (18g). 30 continuous sprint acceleration at the end of running was less than half of initial acceleration and the running posture of the rats changed to prostrate, and remained at the end of the runway for a long time. Later, quantitative correlational data analyses such as mean, Pearson correlation, analysis of one-way ANOVA and paired sample t test were performed in this study.&#x0D; Results (1) The rats’ sprint acceleration of treadmill exercise at the end stage (the final 1/5 of the total time) decreased by 56.9% (P &lt; 0.01) when compared with the early stage (the begining 1/5 of the total time). (2) The MGF and GBT of EF decreased by 68.1% (P &lt; 0.01) and 90.38% (P &lt; 0.01), respectively when compared with the beginning EF; in addition, the EMG maxRMS and MF of hindlimb and forelimb of EF rats had significantly reduced (P &lt; 0.01), and the rats’ MGF/GBT was positively correlated with EMG maxRMS/MF significantly (MGF: forelimb rmaxRMS = 0.901, P &lt; 0.01，rMF = 0.761, P &lt; 0.01; hindlimb rmaxRMS = 0.913, P &lt; 0.01，rMF = 0.783, P &lt; 0.01; GBT: forelimb rmaxRMS = 0.922, P &lt; 0.01，rMF = 0.806, P &lt; 0.01; hindlimb rmaxRMS = 0.908, P &lt; 0.01，rMF = 0.896, P &lt; 0.01).&#x0D; Conclusions Exercise fatigue reduced the muscle strength, muscular endurance and muscle power of rates significantly, which may be related to the decreased recruitment, rhythm synchronization and discharge frequency of muscle motor units of forelimb flexor and hindlimb extensor.

Characteristics of Rest and Postural Tremors in Parkinson's Disease: An Analysis of Motor Unit Firing Synchrony and Patterns.

The neural mechanisms responsible for resting and postural tremor in Parkinson’s disease (PD) have been the object of considerable study, much of it focusing on supraspinal sites. Here, we adopted an alternative approach that emphasizes motor unit (MU) firing synchrony and patterns of discharge. To explore if these could account for known features of PD tremor, we recorded the instantaneous acceleration of the upper limb of 23 PD patients at rest or while they tried to hold a stable posture together with surface EMG and single MU discharges of upper limb muscles. Spectral, coherence and cross-correlation analyses of the recorded signals demonstrated alternating epoch-I and epoch-II intervals in PD patients both at rest and while they held a stable posture. Epoch-II intervals are characterized by the presence of 4–8 Hz overt tremor, enhanced MU synchrony and spike-doublets or triplets bearing a one-to-one relation to each tremor cycle. Epoch-I resembled physiological tremor in that it was characterized by 6–10 Hz non-overt tremor, lower MU synchrony and rhythmical MU firing at the intrinsic rate of the unit. The frequency of overt and non-overt tremor remained the same whether the patient was at rest or held a stable posture and the same was true of the remaining characteristics of epoch-I and epoch-II. The mean interval between spikes of a doublet/triplet varied between 30 and 50 ms and, for any given patient, remained roughly constant throughout measurements. This is the first time that enhanced MU synchrony and spike doublets/triplets characterized by relatively stable interspike intervals, are shown to accompany the overt tremor of PD patients. To account for our findings we propose that a two-state oscillatory spinal stretch reflex loop generates overt parkinsonian tremor in response to intermittent, descending, relatively high frequency oscillatory signals.

The Impact of Imperceptible Vibratory Noise on the Spinal Motor Reflex

Imperceptible noise stimulation has been shown to increase agility, stability and decrease muscle tremor. Previous research has shown that this effect is mediated via decreases in motor unit discharge variability and decreased motor unit synchronization. However, whether these motor unit effects arise from a spinal or cortical mechanisms is unknown and may change how these technologies are implemented to enhance human performance. PURPOSE: Determine the effect of imperceptible vibratory noise on the spinal motor reflex (Hoffman Reflex). METHODS: 12 males participated in the collection of a Hoffman reflex (H-reflex) recruitment curve and underwent either a randomized STIM (noise applied) trial or SHAM (control). The H-reflex recruitment curve was obtained from the median nerve of the subject’s dominant arm. The intensity that elicited the onset of the M-wave was used to standardize the H-reflex stimulation intensity. The STIM trial was performed by introducing a random imperceptible vibratory noise 3 seconds before the collection of the H-reflex. The test was repeated for a total of 10 stimulations with six seconds of rest between stimulations. The resulting H-reflex amplitudes were then normalized to the maximal M-wave (Mmax) found during the H-reflex recruitment curve. Data were assessed with a generalized estimating equation, clustering for multiple observations. RESULTS: The H-reflex was 19.1% (SE±2.42) of Mmax in the STIM trials and 17.4% (SE±2.66) in the SHAM trials, showing a significant increase of 1.73% with STIM (p = 0.0016). CONCLUSIONS: Subjects showed an increase in spinal excitability while undergoing STIM. The results demonstrate that the spinal reflex plays a role in the motor adaptation response to imperceptible vibration. This increase in spinal excitability suggests that the performance benefits of imperceptible noise stimulation may have a rapid onset, on the order of 10-20 milliseconds, in contrast to cortical mechanisms which are greater than 100 milliseconds. Determining which motor centers mediate the behavioral response to noise stimulation, and to what degree, will help define the optimal parameters for the application of noise stimulation.

Tremor severity in Parkinson's disease and cortical changes of areas controlling movement sequencing: A preliminary study.

There remains much to learn about the changes in cortical anatomy that are associated with tremor severity in Parkinson's disease (PD). For this reason, we used a combination of structural neuroimaging to measure cortical thickness and neurophysiological studies to analyze whether PD tremor was associated with cortex integrity. Magnetic resonance imaging and neurophysiological assessment were performed in 13 nondemented PD patients (9 women, 69.2%) with a clearly tremor-dominant phenotype. Cortical reconstruction and volumetric segmentation were performed with the Freesurfer image analysis software. Assessment of tremor was performed by means of high-density surface electromyography (hdEMG) and inertial measurement units (IMUs). Individual motor unit discharge patterns were identified from surface hdEMG and tremor metrics quantifying motor unit synchronization from IMUs. Increased motor unit synchronization (i.e., more severe tremor) was associated with cortical changes (i.e., atrophy) in wide-spread cortical areas, including caudal middle frontal regions bilaterally (dorsal premotor cortices), left inferior parietal lobe (posterior parietal cortex), left lateral orbitofrontal cortex, cingulate cortex bilaterally, left posterior and transverse temporal cortex, and left occipital lobe, as well as reduced left middle temporal volume. Given that the majority of these areas are involved in controlling movement sequencing, our results support Albert's classic hypothesis that PD tremor may be the result of an involuntary activation of a program of motor behavior used in the genesis of rapid voluntary alternating movements.

The Importance of Muscular Strength: Training Considerations.

This review covers underlying physiological characteristics and training considerations that may affect muscular strength including improving maximal force expression and time-limited force expression. Strength is underpinned by a combination of morphological and neural factors including muscle cross-sectional area and architecture, musculotendinous stiffness, motor unit recruitment, rate coding, motor unit synchronization, and neuromuscular inhibition. Although single- and multi-targeted block periodization models may produce the greatest strength-power benefits, concepts within each model must be considered within the limitations of the sport, athletes, and schedules. Bilateral training, eccentric training and accentuated eccentric loading, and variable resistance training may produce the greatest comprehensive strength adaptations. Bodyweight exercise, isolation exercises, plyometric exercise, unilateral exercise, and kettlebell training may be limited in their potential to improve maximal strength but are still relevant to strength development by challenging time-limited force expression and differentially challenging motor demands. Training to failure may not be necessary to improve maximum muscular strength and is likely not necessary for maximum gains in strength. Indeed, programming that combines heavy and light loads may improve strength and underpin other strength-power characteristics. Multiple sets appear to produce superior training benefits compared to single sets; however, an athlete's training status and the dose-response relationship must be considered. While 2- to 5-min interset rest intervals may produce the greatest strength-power benefits, rest interval length may vary based an athlete's training age, fiber type, and genetics. Weaker athletes should focus on developing strength before emphasizing power-type training. Stronger athletes may begin to emphasize power-type training while maintaining/improving their strength. Future research should investigate how best to implement accentuated eccentric loading and variable resistance training and examine how initial strength affects an athlete's ability to improve their performance following various training methods.

Robust estimation of average twitch contraction forces of populations of motor units in humans

The characteristics of motor unit force twitch profiles provide important information for the understanding of the muscle force generation. The twitch force is commonly estimated with the spike-triggered averaging technique, which, despite the many limitations, has been important for clarifying central issues in force generation. In this study, we propose a new technique for the estimation of the average twitch profile of populations of motor units with uniform contractile properties. The method encompasses a model-based deconvolution of the force signal using the identified discharge times of a population of motor units. The proposed technique was validated using simulations and tested on signals recorded during voluntary activation. The results of the simulations showed that the proposed method provides accurate estimates (relative error <25%) of the main parameters of the average twitch force when the number of identified motor units is between 5% and 15% of the total number of active motor units. It is discussed that current detection and decomposition methods of multi-channel surface EMG signals allow decoding this relative sample of the active motor unit pool. However, even when this condition is not met, our results show that the estimates provided by the new method are anyway always superior to those obtained by the spike triggered average approach, especially for high motor unit synchronization levels and when a relatively small number of triggers is available. In conclusion, we present a new method that overcome the main limitations of the spike-triggered average for the study of contractile properties of individual motor units. The method provides a new reliable tool for the investigation of the determinants of muscle force.

Correlation between discharge timings of pairs of motor units reveals the presence but not the proportion of common synaptic input to motor neurons.

We investigated whether correlation measures derived from pairs of motor unit (MU) spike trains are reliable indicators of the degree of common synaptic input to motor neurons. Several 50-s isometric contractions of the biceps brachii muscle were performed at different target forces ranging from 10 to 30% of the maximal voluntary contraction relying on force feedback. Forty-eight pairs of MUs were examined at various force levels. Motor unit synchrony was assessed by cross-correlation analysis using three indexes: the output correlation as the peak of the cross-histogram (ρ) and the number of synchronous spikes per second (CIS) and per trigger (E). Individual analysis of MU pairs revealed that ρ, CIS, and E were most often positively associated with discharge rate (87, 85, and 76% of the MU pairs, respectively) and negatively with interspike interval variability (69, 65, and 62% of the MU pairs, respectively). Moreover, the behavior of synchronization indexes with discharge rate (and interspike interval variability) varied greatly among the MU pairs. These results were consistent with theoretical predictions, which showed that the output correlation between pairs of spike trains depends on the statistics of the input current and motor neuron intrinsic properties that differ for different motor neuron pairs. In conclusion, the synchronization between MU firing trains is necessarily caused by the (functional) common input to motor neurons, but it is not possible to infer the degree of shared common input to a pair of motor neurons on the basis of correlation measures of their output spike trains.NEW & NOTEWORTHY The strength of correlation between output spike trains is only poorly associated with the degree of common input to the population of motor neurons. The synchronization between motor unit firing trains is necessarily caused by the (functional) common input to motor neurons, but it is not possible to infer the degree of shared common input to a pair of motor neurons on the basis of correlation measures of their output spike trains.

New Perspectives for Computer-Aided Discrimination of Parkinson’s Disease and Essential Tremor

Pathological tremor is a common but highly complex movement disorder, affecting ~5% of population older than 65 years. Different methodologies have been proposed for its quantification. Nevertheless, the discrimination between Parkinson’s disease tremor and essential tremor remains a daunting clinical challenge, greatly impacting patient treatment and basic research. Here, we propose and compare several movement-based and electromyography-based tremor quantification metrics. For the latter, we identified individual motor unit discharge patterns from high-density surface electromyograms and characterized the neural drive to a single muscle and how it relates to other affected muscles in 27 Parkinson’s disease and 27 essential tremor patients. We also computed several metrics from the literature. The most discriminative metrics were the symmetry of the neural drive to muscles, motor unit synchronization, and the mean log power of the tremor harmonics in movement recordings. Noteworthily, the first two most discriminative metrics were proposed in this study. We then used decision tree modelling to find the most discriminative combinations of individual metrics, which increased the accuracy of tremor type discrimination to 94%. In summary, the proposed neural drive-based metrics were the most accurate at discriminating and characterizing the two most common pathological tremor types.

Using Computational Neuroscience to Define Common Input to Spinal Motor Neurons.

Common input is a widely used concept in motor neurophysiology. It embodies the notion that inputs to individual spinal motor neurons (MNs) are not unique, but partly shared across MNs, and is considered the main explanation for synchronized activity of MNs (Bremner et al., 1991; Farmer et al., 1993; Boonstra and Breakspear, 2012; Farina and Negro, 2015). Motor-unit synchronization was first observed in the time domain using cross-correlation histograms from pairs of MNs (Sears and Stagg, 1976). This was later extended to the frequency domain by estimating coherence between spike trains to reveal the frequency content of common input (Farmer et al., 1993). In addition to measurements of individual MNs, coherence can also be estimated between the surface EMG of different muscles—referred to as intermuscular coherence—to assess common input shared across motor-unit pools (Boonstra and Breakspear, 2012). Common input is considered relevant for motor control as it may provide a mechanism to reduce the dimensionality of the control signal, thereby simplifying motor control (Farmer, 1998).