Piper rhythm of the electromyograms of the abductor pollicis brevis muscle during isometric contractions

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

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

Effects of hand configuration on muscle force coordination, co-contraction and concomitant intermuscular coupling during maximal isometric flexion of the fingers

PURPOSE

The mechanisms governing the control of musculoskeletal redundancy remain to be fully understood. The hand is highly redundant, and shows different functional role of extensors according to its configuration for a same functional task of finger flexion. Through intermuscular coherence analysis combined with hand musculoskeletal modelling during maximal isometric hand contractions, our aim was to better understand the neural mechanisms underlying the control of muscle force coordination and agonist-antagonist co-contraction.

METHODS

Thirteen participants performed maximal isometric flexions of the fingers in two configurations: power grip (Power) and finger-pressing on a surface (Press). Hand kinematics and force/moment measurements were used as inputs in a musculoskeletal model of the hand to determine muscular tensions and co-contraction. EMG-EMG coherence analysis was performed between wrist and finger flexors and extensor muscle pairs in alpha, beta and gamma frequency bands.

RESULTS

Concomitantly with tailored muscle force coordination and increased co-contraction between Press and Power (mean difference: 48.08%; p < 0.05), our results showed muscle-pair-specific modulation of intermuscular coupling, characterized by pair-specific modulation of EMG-EMG coherence between Power and Press (p < 0.05), and a negative linear association between co-contraction and intermuscular coupling for the ECR/FCR agonist-antagonist muscle pair (r = - 0.65; p < 0.05).

CONCLUSIONS

This study brings new evidence that pair-specific modulation of EMG-EMG coherence is related to modulation of muscle force coordination during hand contractions. Our results highlight the functional importance of intermuscular coupling as a mechanism contributing to the control of muscle force synergies and agonist-antagonist co-contraction.

Intermuscular coherence reflects functional coordination

Coherence analysis has the ability to identify the presence of common descending drive shared by motor unit pools and reveals its spectral properties. However, the link between spectral properties of shared neural drive and functional interactions among muscles remains unclear. We assessed shared neural drive between muscles of the thumb and index finger while participants executed two mechanically distinct precision pinch tasks, each requiring distinct functional coordination among muscles. We found that shared neural drive was systematically reduced or enhanced at specific frequencies of interest (~10 and ~40 Hz). While amplitude correlations between surface EMG signals also exhibited changes across tasks, only their coherence has strong physiological underpinnings indicative of neural binding. Our results support the use of intermuscular coherence as a tool to detect when coactivated muscles are members of a functional group or synergy of neural origin. Furthermore, our results demonstrate the advantages of considering neural binding at 10, ~20, and >30 Hz, as indicators of task-dependent neural coordination strategies.NEW & NOTEWORTHY It is often unclear whether correlated activity among muscles reflects their neural binding or simply reflects the constraints defining the task. Using the fact that high-frequency coherence between EMG signals (>6 Hz) is thought to reflect shared neural drive, we demonstrate that coherence analysis can reveal the neural origin of distinct muscle coordination patterns required by different tasks.

Spectral properties of multiple myoelectric signals: New insights into the neural origin of muscle synergies

It is still unclear if muscle synergies reflect neural strategies or mirror the underlying mechanical constraints. Therefore, this study aimed to verify the consistency of muscle groupings between the synergies based on the linear envelope (LE) of muscle activities and those incorporating the time-frequency (TF) features of the electromyographic (EMG) signals. Twelve healthy participants performed six 20-m walking trials at a comfort and fast self-selected speed, while the activity of eleven lower limb muscles was recorded by means of surface EMG. Wavelet-transformed EMG was used to obtain the TF pattern and muscle synergies were extracted by non-negative matrix factorization. When five muscle synergies were extracted, both methods defined similar muscle groupings whatever the walking speed. When accounting the reconstruction level of the initial dataset, a new TF synergy emerged. This new synergy dissociated the activity of the rectus femoris from those of the vastii muscles (synergy #1) and from the one of the tensor fascia latae (synergy #5). Overall, extracting TF muscle synergies supports the neural origin of muscle synergies and provides an opportunity to distinguish between prescriptive and descriptive muscle synergies.

The Dynamics of Voluntary Force Production in Afferented Muscle Influence Involuntary Tremor

Voluntary control of force is always marked by some degree of error and unsteadiness. Both neural and mechanical factors contribute to these fluctuations, but how they interact to produce them is poorly understood. In this study, we identify and characterize a previously undescribed neuromechanical interaction where the dynamics of voluntary force production suffice to generate involuntary tremor. Specifically, participants were asked to produce isometric force with the index finger and use visual feedback to track a sinusoidal target spanning 5-9% of each individual's maximal voluntary force level. Force fluctuations and EMG activity over the flexor digitorum superficialis (FDS) muscle were recorded and their frequency content was analyzed as a function of target phase. Force variability in either the 1-5 or 6-15 Hz frequency ranges tended to be largest at the peaks and valleys of the target sinusoid. In those same periods, FDS EMG activity was synchronized with force fluctuations. We then constructed a physiologically-realistic computer simulation in which a muscle-tendon complex was set inside of a feedback-driven control loop. Surprisingly, the model sufficed to produce phase-dependent modulation of tremor similar to that observed in humans. Further, the gain of afferent feedback from muscle spindles was critical for appropriately amplifying and shaping this tremor. We suggest that the experimentally-induced tremor may represent the response of a viscoelastic muscle-tendon system to dynamic drive, and therefore does not fall into known categories of tremor generation, such as tremorogenic descending drive, stretch-reflex loop oscillations, motor unit behavior, or mechanical resonance. Our findings motivate future efforts to understand tremor from a perspective that considers neuromechanical coupling within the context of closed-loop control. The strategy of combining experimental recordings with physiologically-sound simulations will enable thorough exploration of neural and mechanical contributions to force control in health and disease.

Evaluation of central and peripheral fatigue in the quadriceps using fractal dimension and conduction velocity in young females

PURPOSE

Over the past decade, linear and non-linear surface electromyography descriptors for central and peripheral components of fatigue have been developed. In the current study, we tested fractal dimension (FD) and conduction velocity (CV) as myoelectric descriptors of central and peripheral fatigue, respectively. To this aim, we analyzed FD and CV slopes during sustained fatiguing contractions of the quadriceps femoris in healthy humans.

METHODS

A total of 29 recreationally active women (mean age±standard deviation: 24±4 years) and two female elite athletes (one power athlete, age 24 and one endurance athlete, age 30 years) performed two knee extensions: (1) at 20% maximal voluntary contraction (MVC) for 30 s, and (2) at 60% MVC held until exhaustion. Surface EMG signals were detected from the vastus lateralis and vastus medialis using bidimensional arrays.

RESULTS

Central and peripheral fatigue were described as decreases in FD and CV, respectively. A positive correlation between FD and CV (R=0.51, p<0.01) was found during the sustained 60% MVC, probably as a result of simultaneous motor unit synchronization and a decrease in muscle fiber CV during the fatiguing task.

CONCLUSIONS

Central and peripheral fatigue can be described as changes in FD and CV, at least in young, healthy women. The significant correlation between FD and CV observed at 60% MVC suggests that a mutual interaction between central and peripheral fatigue can arise during submaximal isometric contractions.

Ankle variability is amplified in older adults due to lower EMG power from 30-60 Hz

The purpose of this study was to determine the neuromuscular mechanisms of the involved muscles that contribute to the greater positional variability at the ankle joint in older adults compared with young adults. Eleven young adults (25.6±4.9 years) and nine older adults (76.9±5.9 years) were asked to accurately match and maintain a horizontal target line with 5° dorsiflexion of their ankle for 20 s. The loads were 5 and 15% of the one repetition maximum load (1 RM). The visual gain was kept constant at 1° for all trials. Positional variability was quantified as the standard deviation (SD) of the detrended position signal. The neural activation of the tibialis anterior and soleus muscles was quantified as the normalized EMG amplitude, power spectrum density (PSD; EMG oscillations) and coactivation of the two muscles. As expected, positional variability was greater in older adults (older: 0.11±0.06° vs. young: 0.04±0.02°; p=.003). The only significant neural difference occurred for the PSD of the tibialis anterior muscle, where young adults exhibited significantly greater power than older adults from 30-60 Hz. The amplified positional variability of ankle joint in older adults was associated with lower power from 30-60 Hz oscillations in the tibialis anterior muscle (r(2)=.3, p=.01). These results provide novel evidence that older adults exhibit greater positional variability with the ankle joint relative to young adults likely due to their inability to activate the tibialis anterior muscle from 30-60 Hz.

Muscular timing and inter-muscular coordination in healthy females while walking

The dynamic interplay between muscles surrounding the knee joint, the central nervous system and external factors require a control strategy to generate and stabilise the preferred gait pattern. The electromyographic (EMG) signal is a common measure reflecting the neuromuscular control strategies during dynamic tasks. Neuromuscular control mechanisms, found in processed EMG signals, showed a precise pacing with a pacing rhythm and a tight control of muscle activity in running and maximally contracted muscles. The purpose of this study was to provide an insight how muscles get activated during walking. The EMG power, extracted by the wavelet transform (92-395Hz), over a time period encompassing 250ms before and 250ms after heel strike was analysed. The study showed that the wavelet-based analysis of EMG signals was sufficiently sensitive to detect a synchronisation of the activation of thigh muscles while walking. The results within each single subject and within the group consisting of 10 healthy females showed that, although there was a lot of jitter in the locations of the intensity peaks, the muscle activation is controlled, on average, by a neuromuscular activity paced at about 40ms, however with variable amplitudes. Albeit the jitter of the signal, the results resolved the temporal dependency of intensity peaks within muscles surrounding the knee and provided an insight into neural control of locomotion. The methodology to assess the stabilising muscle activation pattern may provide a way to discriminate subjects with normal gait pattern form those with a deteriorated neuromuscular control strategy.