Comparison between the degree of motor unit short-term synchronization and recurrence quantification analysis of the surface EMG in two human muscles

Effect of synchronization of firings of different motor unit types on the force variability in a model of the rat medial gastrocnemius muscle

The synchronized firings of active motor units (MUs) increase the oscillations of muscle force, observed as physiological tremor. This study aimed to investigate the effects of synchronizing the firings within three types of MUs (slow—S, fast resistant to fatigue–FR, and fast fatigable–FF) on the muscle force production using a mathematical model of the rat medial gastrocnemius muscle. The model was designed based on the actual proportion and physiological properties of MUs and motoneurons innervating the muscle. The isometric muscle and MU forces were simulated by a model predicting non-synchronized firing of a pool of 57 MUs (including 8 S, 23 FR, and 26 FF) to ascertain a maximum excitatory signal when all MUs were recruited into the contraction. The mean firing frequency of each MU depended upon the twitch contraction time, whereas the recruitment order was determined according to increasing forces (the size principle). The synchronization of firings of individual MUs was simulated using four different modes and inducing the synchronization of firings within three time windows (± 2, ± 4, and ± 6 ms) for four different combinations of MUs. The synchronization was estimated using two parameters, the correlation coefficient and the cross-interval synchronization index. The four scenarios of synchronization increased the values of the root-mean-square, range, and maximum force in correlation with the increase of the time window. Greater synchronization index values resulted in higher root-mean-square, range, and maximum of force outcomes for all MU types as well as for the whole muscle output; however, the mean spectral frequency of the forces decreased, whereas the mean force remained nearly unchanged. The range of variability and the root-mean-square of forces were higher for fast MUs than for slow MUs; meanwhile, the relative values of these parameters were highest for slow MUs, indicating their important contribution to muscle tremor, especially during weak contractions.

The synchronization of firings of motor units (MUs), the smallest functional elements of skeletal muscle increases fluctuations in muscle force, known as physiological tremor, which can disturb high-precision movements. In this study, we adopted a recently proposed muscle model consisting of MUs of three different types (fast fatigable, fast resistant to fatigue, and slow) to study four different scenarios of MU synchronization during a steady level of excitatory input to motoneurons. The discharge patterns were synchronized between pairs of MUs by shifting in time individual pulses, which occurred within a short time interval, and a degree of synchronization was then estimated. The increased synchronization index resulted in increased force variability for all MU types as well as for the whole muscle output; however, the mean force levels remained nearly unchanged, whereas the frequencies of the force oscillations were decreased. The absolute range of force variability was higher for fast than for slow MUs, indicating their dominant influence on muscle tremor at strong contractions, but the highest relative increase in force variability was observed for synchronized slow MUs, indicating their significant contribution to tremor during weak contractions, in which only slow MUs are active.

Coupled Gluteus Maximus and Gluteus Medius Recruitment Patterns Modulate Hip Adduction Variability During Single-Limb Step-Downs: A Cross-Sectional Study

CONTEXT

Examining the coordinated coupling of muscle recruitment patterns may provide insight into movement variability in sport-related tasks.

OBJECTIVE

The purpose of this study was to examine the relationship between coupled gluteus maximus and medius recruitment patterns and hip-adduction variability during single-limb step-downs.

DESIGN

Cross-sectional.

SETTING

Biomechanics laboratory.

PARTICIPANTS

Forty healthy adults, including 26 women and 14 men, mean age 23.8 (1.6) years, mean body mass index 24.2 (3.1) kg/m2, participated.

INTERVENTIONS

Lower-extremity kinematics were acquired during 20 single-limb step-downs from a 19-cm step height. Electromyography (EMG) signals were captured with surface electrodes. Isometric hip-extension strength was obtained.

MAIN OUTCOME MEASURES

Hip-adduction variability, measured as the SD of peak hip adduction across 20 repetitions of the step-down task, was measured. The mean amplitudes of gluteus maximus and gluteus medius EMG recruitment were examined. Determinism and entropy of the coupled EMG signals were computed with cross-recurrence quantification analyses.

RESULTS

Hip-adduction variability correlated inversely with determinism (r = -.453, P = .018) and positively with entropy (r = .409, P = .034) in coupled gluteus maximus/medius recruitment patterns but not with hip-extensor strength nor with magnitudes of mean gluteus maximus or medius recruitment (r = -.003, .081, and .035; P = .990, .688, and .864, respectively).

CONCLUSION

Hip-adduction variability during single-limb step-downs correlated more strongly with measures of coupled gluteus maximus and medius recruitment patterns than with hip-extensor strength or magnitudes of muscle recruitment. Examining coupled recruitment patterns may provide an alternative understanding of the extent to which hip neuromuscular control modulates lower-extremity kinematics beyond examining muscle strength or EMG recruitment magnitudes.

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.

Increased EMG intermuscular coherence and reduced signal complexity in Parkinson's disease

OBJECTIVES

To investigate differences in surface electromyography (EMG) features in individuals with idiopathic Parkinson's disease (PD) and aged-matched controls.

METHODS

Surface EMG was recorded during isometric leg extension in PD patients prior to, and after undergoing a locomotor training programme, and in aged-matched controls. Differences in EMG structure were quantified using determinism (%DET), sample entropy (SampEn) and intermuscular coherence.

RESULTS

%DET was significantly higher, and SampEn significantly lower, in PD patients. Intermuscular coherence was also significantly higher in the PD group in theta, alpha and beta frequency bands. %DET increased and SampEn decreased with increasing Movement-Disorder-Society UPDRS scores, while theta band coherence was significantly correlated with total MDS-UPDRS scores and torque variance. Neither %DET, SampEn nor intermuscular coherence changed in response to training.

CONCLUSIONS

The differences observed are consistent with increased synchrony among motor units within and across leg muscles in PD. Differences between EMG signals recorded from the PD and control groups persisted post-therapy, after improvements in walking capacity occurred.

SIGNIFICANCE

These results provide insight into changes in motoneuron activity in PD, demonstrate increased beta band intramuscular coherence in PD for the first time, and support the development of quantitative biomarkers for PD based on advanced surface EMG features.

The human motor neuron pools receive a dominant slow-varying common synaptic input

KEY POINTS

Motor neurons in a pool receive both common and independent synaptic inputs, although the proportion and role of their common synaptic input is debated. Classic correlation techniques between motor unit spike trains do not measure the absolute proportion of common input and have limitations as a result of the non-linearity of motor neurons. We propose a method that for the first time allows an accurate quantification of the absolute proportion of low frequency common synaptic input (<5 Hz) to motor neurons in humans. We applied the proposed method to three human muscles and determined experimentally that they receive a similar large amount (>60%) of common input, irrespective of their different functional and control properties. These results increase our knowledge about the role of common and independent input to motor neurons in force control.

ABSTRACT

Motor neurons receive both common and independent synaptic inputs. This observation is classically based on the presence of a significant correlation between pairs of motor unit spike trains. The functional significance of different relative proportions of common input across muscles, individuals and conditions is still debated. One of the limitations in our understanding of correlated input to motor neurons is that it has not been possible so far to quantify the absolute proportion of common input with respect to the total synaptic input received by the motor neurons. Indeed, correlation measures of pairs of output spike trains only allow for relative comparisons. In the present study, we report for the first time an approach for measuring the proportion of common input in the low frequency bandwidth (<5 Hz) to a motor neuron pool in humans. This estimate is based on a phenomenological model and the theoretical fitting of the experimental values of coherence between the permutations of groups of motor unit spike trains. We demonstrate the validity of this theoretical estimate with several simulations. Moreover, we applied this method to three human muscles: the abductor digiti minimi, tibialis anterior and vastus medialis. Despite these muscles having different functional roles and control properties, as confirmed by the results of the present study, we estimate that their motor pools receive a similar and large (>60%) proportion of common low frequency oscillations with respect to their total synaptic input. These results suggest that the central nervous system provides a large amount of common input to motor neuron pools, in a similar way to that for muscles with different functional and control properties.

Influence of common synaptic input to motor neurons on the neural drive to muscle in essential tremor

Tremor in essential tremor (ET) is generated by pathological oscillations at 4-12 Hz, likely originating at cerebello-thalamo-cortical pathways. However, the way in which tremor is represented in the output of the spinal cord circuitries is largely unknown because of the difficulties in identifying the behavior of individual motor units from tremulous muscles. By using novel methods for the decomposition of multichannel surface EMG, we provide a systematic analysis of the discharge properties of motor units in nine ET patients, with concurrent recordings of EEG activity. This analysis allowed us to infer the contribution of common synaptic inputs to motor neurons in ET. Motor unit short-term synchronization was significantly greater in ET patients than in healthy subjects. Furthermore, the strong association between the degree of synchronization and the peak in coherence between motor unit spike trains at the tremor frequency indicated that the high synchronization levels were generated mainly by common synaptic inputs specifically at the tremor frequency. The coherence between EEG and motor unit spike trains demonstrated the presence of common cortical input to the motor neurons at the tremor frequency. Nonetheless, the strength of this input was uncorrelated to the net common synaptic input at the tremor frequency, suggesting a contribution of spinal afferents or secondary supraspinal pathways in projecting common input at the tremor frequency. These results provide the first systematic analysis of the neural drive to the muscle in ET and elucidate some of its characteristics that determine pathological tremulous muscle activity.

Motor unit

Movement is accomplished by the controlled activation of motor unit populations. Our understanding of motor unit physiology has been derived from experimental work on the properties of single motor units and from computational studies that have integrated the experimental observations into the function of motor unit populations. The article provides brief descriptions of motor unit anatomy and muscle unit properties, with more substantial reviews of motoneuron properties, motor unit recruitment and rate modulation when humans perform voluntary contractions, and the function of an entire motor unit pool. The article emphasizes the advances in knowledge on the cellular and molecular mechanisms underlying the neuromodulation of motoneuron activity and attempts to explain the discharge characteristics of human motor units in terms of these principles. A major finding from this work has been the critical role of descending pathways from the brainstem in modulating the properties and activity of spinal motoneurons. Progress has been substantial, but significant gaps in knowledge remain.

Motor unit recruitment strategies and muscle properties determine the influence of synaptic noise on force steadiness

Motoneurons receive synaptic inputs from tens of thousands of connections that cause membrane potential to fluctuate continuously (synaptic noise), which introduces variability in discharge times of action potentials. We hypothesized that the influence of synaptic noise on force steadiness during voluntary contractions is limited to low muscle forces. The hypothesis was examined with an analytical description of transduction of motor unit spike trains into muscle force, a computational model of motor unit recruitment and rate coding, and experimental analysis of interspike interval variability during steady contractions with the abductor digiti minimi muscle. Simulations varied contraction force, level of synaptic noise, size of motor unit population, recruitment range, twitch contraction times, and level of motor unit short-term synchronization. Consistent with the analytical derivations, simulations and experimental data showed that force variability at target forces above a threshold was primarily due to low-frequency oscillations in neural drive, whereas the influence of synaptic noise was almost completely attenuated by two low-pass filters, one related to convolution of motoneuron spike trains with motor unit twitches (temporal summation) and the other attributable to summation of single motor unit forces (spatial summation). The threshold force above which synaptic noise ceased to influence force steadiness depended on recruitment range, size of motor unit population, and muscle contractile properties. This threshold was low (<10% of maximal force) for typical values of these parameters. Results indicate that motor unit recruitment and muscle properties of a typical muscle are tuned to limit the influence of synaptic noise on force steadiness to low forces and that the inability to produce a constant force during stronger contractions is mainly attributable to the common low-frequency oscillations in motoneuron discharge rates.

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.

Low-frequency oscillations of the neural drive to the muscle are increased with experimental muscle pain

We investigated the influence of nociceptive stimulation on the accuracy of task execution and motor unit spike trains during low-force isometric contractions. Muscle pain was induced by infusion of hypertonic saline into the abductor digiti minimi muscle of 11 healthy men. Intramuscular EMG signals were recorded from the same muscle during four isometric contractions of 60-s duration at 10% of the maximal force [maximal voluntary contraction (MVC)] performed before injection (baseline), after injection of isotonic (control) or hypertonic saline (pain), and 15 min after pain was no longer reported. Each contraction was preceded by three 3-s ramp contractions from 0% to 10% MVC. The low-frequency oscillations of motor unit spike trains were analyzed by the first principal component of the low-pass filtered spike trains [first common component (FCC)], which represents the effective neural drive to the muscle. Pain decreased the accuracy of task performance [coefficient of variation (CoV) for force: baseline, 2.8 ± 1.8%, pain, 3.9 ± 1.8%; P < 0.05] and reduced motor unit discharge rates [11.6 ± 2.3 pulses per second (pps) vs. 10.7 ± 1.7 pps; P < 0.05]. Motor unit recruitment thresholds (2.2 ± 1.2% MVC vs. 2.4 ± 1.6% MVC), interspike interval variability (18.4 ± 4.9% vs. 19.1 ± 5.4%), strength of motor unit short-term synchronization [common input strength (CIS) 1.02 ± 0.44 vs. 0.83 ± 0.22], and strength of common drive (0.47 ± 0.08 vs. 0.47 ± 0.06) did not change across conditions. The FCC signal was correlated with force (R = 0.45 ± 0.06), and the CoV for FCC increased in the painful condition (5.69 ± 1.29% vs. 7.83 ± 2.61%; P < 0.05). These results indicate that nociceptive stimulation increased the low-frequency variability in synaptic input to motoneurons.

Decorrelation of cortical inputs and motoneuron output

Oscillations in the primary motor cortex are transmitted through the corticospinal tract to the motoneuron pool. This pathway is believed to produce an effective and direct command from the motor cortex to the spinal motoneurons for the modulation of the force output. In this study, we used a computational model of a population of motoneurons to investigate the factors that can influence the transmission of the cortical input to the output of motoneurons, since it can be quantified by coherence analysis. The simulations demonstrated that, despite the nonlinearity of the motoneurons, oscillations present in the cortical input are transmitted to the output of the motoneuron pool at the same frequency. However, the interference introduced by the nonlinearity of the system increases the variability of the oscillations in output, introducing spectral lines whose frequency depends on the input frequencies and the motoneuron discharge rates. Moreover, an additional source of synaptic input common to all motoneurons but independent from the corticospinal component decorrelates the cortical input and motoneuron output and, thus, decreases the magnitude of the estimated coherence, even if the effective cortical drive does not change. These results indicate that the corticospinal input can effectively be sampled by a small population of motoneurons. However, the transmission of a corticospinal drive to the motoneuron pool is influenced by the nonlinearity of the spiking processes of the active motoneurons and by synaptic inputs common to the motoneuron population but independent from the cortical input.

Neuromuscular adjustments that constrain submaximal EMG amplitude at task failure of sustained isometric contractions

The amplitude of the surface EMG does not reach the level achieved during a maximal voluntary contraction force at the end of a sustained, submaximal contraction, despite near-maximal levels of voluntary effort. The depression of EMG amplitude may be explained by several neural and muscular adjustments during fatiguing contractions, including decreased net neural drive to the muscle, changes in the shape of the motor unit action potentials, and EMG amplitude cancellation. The changes in these parameters for the entire motor unit pool, however, cannot be measured experimentally. The present study used a computational model to simulate the adjustments during sustained isometric contractions and thereby determine the relative importance of these factors in explaining the submaximal levels of EMG amplitude at task failure. The simulation results indicated that the amount of amplitude cancellation in the simulated EMG (∼ 40%) exhibited a negligible change during the fatiguing contractions. Instead, the main determinant of the submaximal EMG amplitude at task failure was a decrease in muscle activation (number of muscle fiber action potentials), due to a reduction in the net synaptic input to motor neurons, with a lesser contribution from changes in the shape of the motor unit action potentials. Despite the association between the submaximal EMG amplitude and reduced muscle activation, the deficit in EMG amplitude at task failure was not consistently associated with the decrease in neural drive (number of motor unit action potentials) to the muscle. This indicates that the EMG amplitude cannot be used as an index of neural drive.

Spike sorting by stochastic simulation

The decomposition of multiunit signals consists of the restoration of spike trains and action potentials in neural or muscular recordings. Because of the complexity of automatic decomposition, semiautomatic procedures are sometimes chosen. The main difficulty in automatic decomposition is the resolution of temporally overlapped potentials. In a previous study , we proposed a Bayesian model coupled with a maximum a posteriori (MAP) estimator for fully automatic decomposition of multiunit recordings and we showed applications to intramuscular EMG signals. In this study, we propose a more complex signal model that includes the variability in amplitude of each unit potential. Moreover, we propose the Markov Chain Monte Carlo (MCMC) simulation and a Bayesian minimum mean square error (MMSE) estimator by averaging on samples that converge in distribution to the joint posterior law. We prove the convergence property of this approach mathematically and we test the method representatively on intramuscular multiunit recordings. The results showed that its average accuracy in spike identification is greater than 90% for intramuscular signals with up to 8 concurrently active units. In addition to intramuscular signals, the method can be applied for spike sorting of other types of multiunit recordings.

Reliability of EMG determinism to detect changes in motor unit synchrony and coherence during submaximal contraction

The determinism (DET) is a parameter used in nonlinear analysis to quantify the occurrence of recurrent patterns in a signal. Applied to the electromyographic activity (EMG), DET has been proposed as an index of motor unit synchrony in human. We have recently shown that the amount of motor unit synchronous firings above chance level was enhanced with stronger submaximal muscle contraction. Using these data, we aimed at determining if (1) EMG DET and motor unit synchrony varied in the same way and (2) EMG DET was more specifically related to the degree of oscillatory coupling between motor unit discharges. Cross-correlation and coherence analyses were applied to the discharges of 30 motor unit pairs tested at various force levels to assess the amount of synchronous impulses and the strength of oscillatory coupling in the time and frequency domains, respectively. Recurrent quantification analysis was applied to EMG activity to extract its DET. Overall, changes in EMG DET were poorly explained by changes in motor unit synchronous impulse probability (6%) and frequency (5%), and by changes in motor unit coherence in the 6-12Hz (5%) and 25-40Hz (8%) bands. Moreover, the comparison of the data obtained at the weakest and the strongest contraction levels tested with each motor unit pair showed that EMG DET remained unaltered with stronger contraction despite the occurrence of consistent changes in motor unit synchrony in both time and frequency domains. This speaks strongly against the reliability of DET in evaluating changes in motor unit synchronization during submaximal muscle contraction.