History dependence of human muscle-fiber conduction velocity during voluntary isometric contractions

Electromyography-Force Relation and Muscle Fiber Conduction Velocity Affected by Spinal Cord Injury

A surface electromyography (EMG) analysis was performed in this study to examine central neural and peripheral muscle changes after a spinal cord injury (SCI). A linear electrode array was used to record surface EMG signals from the biceps brachii (BB) in 15 SCI subjects and 14 matched healthy control subjects as they performed elbow flexor isometric contractions from 10% to 80% maximum voluntary contraction. Muscle fiber conduction velocity (MFCV) and BB EMG-force relation were examined. MFCV was found to be significantly slower in the SCI group than the control group, evident at all force levels. The BB EMG-force relation was well fit by quadratic functions in both groups. All healthy control EMG-force relations were best fit with positive quadratic coefficients. In contrast, the EMG-force relation in eight SCI subjects was best fit with negative quadratic coefficients, suggesting impaired EMG modulation at high forces. The alterations in MFCV and EMG-force relation after SCI suggest complex neuromuscular changes after SCI, including alterations in central neural drive and muscle properties.

Multiscale modeling of the neuromuscular system: Coupling neurophysiology and skeletal muscle mechanics

Mathematical models and computer simulations have the great potential to substantially increase our understanding of the biophysical behavior of the neuromuscular system. This, however, requires detailed multiscale, and multiphysics models. Once validated, such models allow systematic in silico investigations that are not necessarily feasible within experiments and, therefore, have the ability to provide valuable insights into the complex interrelations within the healthy system and for pathological conditions. Most of the existing models focus on individual parts of the neuromuscular system and do not consider the neuromuscular system as an integrated physiological system. Hence, the aim of this advanced review is to facilitate the prospective development of detailed biophysical models of the entire neuromuscular system. For this purpose, this review is subdivided into three parts. The first part introduces the key anatomical and physiological aspects of the healthy neuromuscular system necessary for modeling the neuromuscular system. The second part provides an overview on state-of-the-art modeling approaches representing all major components of the neuromuscular system on different time and length scales. Within the last part, a specific multiscale neuromuscular system model is introduced. The integrated system model combines existing models of the motor neuron pool, of the sensory system and of a multiscale model describing the mechanical behavior of skeletal muscles. Since many sub-models are based on strictly biophysical modeling approaches, it closely represents the underlying physiological system and thus could be employed as starting point for further improvements and future developments. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models.

Surface electromyographic amplitude does not identify differences in neural drive to synergistic muscles

Surface electromyographic (EMG) signal amplitude is typically used to compare the neural drive to muscles. We experimentally investigated this association by studying the motor unit (MU) behavior and action potentials in the vastus medialis (VM) and vastus lateralis (VL) muscles. Eighteen participants performed isometric knee extensions at four target torques [10, 30, 50, and 70% of the maximum torque (MVC)] while high-density EMG signals were recorded from the VM and VL. The absolute EMG amplitude was greater for VM than VL ( P < 0.001), whereas the EMG amplitude normalized with respect to MVC was greater for VL than VM ( P < 0.04). Because differences in EMG amplitude can be due to both differences in the neural drive and in the size of the MU action potentials, we indirectly inferred the neural drives received by the two muscles by estimating the synaptic inputs received by the corresponding motor neuron pools. For this purpose, we analyzed the increase in discharge rate from recruitment to target torque for motor units matched by recruitment threshold in the two muscles. This analysis indicated that the two muscles received similar levels of neural drive. Nonetheless, the size of the MU action potentials was greater for VM than VL ( P < 0.001), and this difference explained most of the differences in EMG amplitude between the two muscles (~63% of explained variance). These results indicate that EMG amplitude, even following normalization, does not reflect the neural drive to synergistic muscles. Moreover, absolute EMG amplitude is mainly explained by the size of MU action potentials.

NEW & NOTEWORTHY Electromyographic (EMG) amplitude is widely used to compare indirectly the strength of neural drive received by synergistic muscles. However, there are no studies validating this approach with motor unit data. Here, we compared between-muscles differences in surface EMG amplitude and motor unit behavior. The results clarify the limitations of surface EMG to interpret differences in neural drive between muscles.

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

AIM

Motor units are recruited in an orderly manner according to the size of motor neurones. Moreover, because larger motor neurones innervate fibres with larger diameters than smaller motor neurones, motor units should be recruited orderly according to their conduction velocity (MUCV). Because of technical limitations, these relations have been previously tested either indirectly or in small motor unit samples that revealed weak associations between motor unit recruitment threshold (RT) and MUCV. Here, we analyse the relation between MUCV and RT for large samples of motor units.

METHODS

Ten healthy volunteers completed a series of isometric ankle dorsiflexions at forces up to 70% of the maximum. Multi-channel surface electromyographic signals recorded from the tibialis anterior muscle were decomposed into single motor unit action potentials, from which the corresponding motor unit RT, MUCV and action potential amplitude were estimated. Established relations between muscle fibre diameter and CV were used to estimate the fibre size.

RESULTS

Within individual subjects, the distributions of MUCV and fibre diameters were unimodal and did not show distinct populations. MUCV was strongly correlated with RT (mean (SD) R²  = 0.7 (0.09), P < 0.001; 406 motor units), which supported the hypothesis that fibre diameter is associated with RT.

CONCLUSION

The results provide further evidence for the relations between motor neurone and muscle fibre properties for large samples of motor units. The proposed methodology for motor unit analysis has also the potential to open new perspectives in the study of chronic and acute neuromuscular adaptations to ageing, training and pathology.

Influence of timing variability between motor unit potentials on M-wave characteristics

The transient enlargement of the compound muscle action potential (M wave) after a conditioning contraction is referred to as potentiation. It has been recently shown that the potentiation of the first and second phases of a monopolar M wave differed drastically; namely, the first phase remained largely unchanged, whereas the second phase underwent a marked enlargement and shortening. This dissimilar potentiation of the first and second phases has been suggested to be attributed to a transient increase in conduction velocity after the contraction. Here, we present a series of simulations to test if changes in the timing variability between motor unit potentials (MUPs) can be responsible for the unequal potentiation (and shortening) of the first and the second M-wave phases. We found that an increase in the mean motor unit conduction velocity resulted in a marked enlargement and narrowing of both the first and second M-wave phases. The enlargement of the first phase caused by a global increase in motor unit conduction velocities was apparent even for the electrode located over the innervation zone and became more pronounced with increasing distance to the innervation zone, whereas the potentiation of the second phase was largely independent of electrode position. Our simulations indicate that it is unlikely that an increase in motor unit conduction velocities (accompanied or not by changes in their distribution) could account for the experimental observation that only the second phase of a monopolar M wave, but not the first, is enlarged after a brief contraction. However, the combination of an increase in the motor unit conduction velocities and a spreading of the motor unit activation times could potentially explain the asymmetric potentiation of the M-wave phases.

M-wave potentiation after voluntary contractions of different durations and intensities in the tibialis anterior

The study was undertaken to provide insight into the mechanisms underlying the potentiation of the muscle compound action potential (M wave) after conditioning contractions. M waves were evoked in the tibialis anterior before and after isometric maximal voluntary contractions (MVC) of 1, 3, 6, 10, 30, and 60 s, and after 3-s contractions at 10, 30, 50, 70, 90, and 100% MVC. The amplitude, duration, and area of the first and second phases of the M wave, together with the median frequency (Fmedian) and muscle fiber conduction velocity (MFCV) were recorded. Furthermore, twitch force, muscle fascicle length, and pennation angle were measured at rest, before, and 1 s after the conditioning contractions. The results indicate that only the amplitude of the second phase of the M wave was significantly increased after conditioning contractions. The extent of this potentiation was similar for MVC durations ranging from 1 to 10 s and augmented progressively with contraction intensity from 30 to 70% MVC. After these conditioning contractions, the duration and area of the two M-wave phases decreased ( P < 0.05), whereas MFCV and Fmedian increased ( P < 0.05). For all of these parameters, the greatest changes occurred 1 s after the conditioning contraction. Changes in MFCV after the contractions were correlated with those in M-wave second-phase amplitude ( r2 = 0.42; P < 0.05) and Fmedian ( r2 = 0.53; P < 0.05). In contrast, fascicle length and pennation angle did not change after the conditioning contractions. It is concluded that the potentiation of the second phase of the M wave is mainly due to an increased MFCV.

The extraction of neural strategies from the surface EMG: an update

A surface EMG signal represents the linear transformation of motor neuron discharge times by the compound action potentials of the innervated muscle fibers and is often used as a source of information about neural activation of muscle. However, retrieving the embedded neural code from a surface EMG signal is extremely challenging. Most studies use indirect approaches in which selected features of the signal are interpreted as indicating certain characteristics of the neural code. These indirect associations are constrained by limitations that have been detailed previously (Farina D, Merletti R, Enoka RM. J Appl Physiol 96: 1486-1495, 2004) and are generally difficult to overcome. In an update on these issues, the current review extends the discussion to EMG-based coherence methods for assessing neural connectivity. We focus first on EMG amplitude cancellation, which intrinsically limits the association between EMG amplitude and the intensity of the neural activation and then discuss the limitations of coherence methods (EEG-EMG, EMG-EMG) as a way to assess the strength of the transmission of synaptic inputs into trains of motor unit action potentials. The debated influence of rectification on EMG spectral analysis and coherence measures is also discussed. Alternatively, there have been a number of attempts to identify the neural information directly by decomposing surface EMG signals into the discharge times of motor unit action potentials. The application of this approach is extremely powerful, but validation remains a central issue.

Assessment of the electrophysiological properties of the muscle fibers of a transplanted hand

BACKGROUND

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.

METHODS

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]).

RESULTS

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).

CONCLUSIONS

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.