Comparative evaluation of motor unit architecture models

In vivo 3D imaging of human motor units in upper and lower limb muscles

OBJECTIVE

To assess in-vivo cross-sectional and 3D morphology of human motor units in hand, forearm and lower leg muscles using magnetic resonance imaging (MRI).

METHODS

Diffusion weighted MRI was used with in-scanner electrical stimulation in healthy controls to image motor units at a single slice in lower leg, forearm and hand muscles (n = 6) and multiple slices in the lower leg for 3D assessment (n = 7).

RESULTS

Motor unit cross-sectional area (CSA) and maximum Feret diameter (FD_max) did not differ between the lower leg (CSA: 22.4 ± 8.4 mm²; FD_max: 8.7 ± 2.4 mm), forearm (CSA: 23.6 ± 14.1 mm²; FD_max: 9.0 ± 3.3 mm) and hand (CSA: 26.8 ± 12.8 mm² and FD_max: 9.6 ± 2.7 mm) (ANOVA; p = 0.487 and p = 0.587, respectively). Lower leg motor units were 8.0 ± 3.8 cm long with largest CSA in the motor unit's middle section. 3D motor unit imaging revealed a complex structure with several units splitting and re-forming along their length.

CONCLUSIONS

Motor unit MRI (MUMRI) can be applied to upper limb muscles, and can reveal the 3D structure of human motor units in-vivo.

SIGNIFICANCE

MUMRI provides the first in-vivo 2D images of upper limb motor units and 3D images of lower leg motor units. 3D imaging suggest a more complex human motor unit structure than previously thought.

A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings

Scanning-EMG is an electrophysiological technique in which the electrical activity of the motor unit is recorded at multiple points along a corridor crossing the motor unit territory. Correct analysis of the scanning-EMG signal requires prior elimination of interference from nearby motor units. Although the traditional processing based on the median filtering is effective in removing such interference, it distorts the physiological waveform of the scanning-EMG signal. In this study, we describe a new scanning-EMG signal processing algorithm that preserves the physiological signal waveform while effectively removing interference from other motor units. To obtain a cleaned-up version of the scanning signal, the masked least-squares smoothing (MLSS) algorithm recalculates and replaces each sample value of the signal using a least-squares smoothing in the spatial dimension, taking into account the information of only those samples that are not contaminated with activity of other motor units. The performance of the new algorithm with simulated scanning-EMG signals is studied and compared with the performance of the median algorithm and tested with real scanning signals. Results show that the MLSS algorithm distorts the waveform of the scanning-EMG signal much less than the median algorithm (approximately 3.5 dB gain), being at the same time very effective at removing interference components.

Graphical Abstract

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.

Evaluation of motor unit placement algorithms for EMG simulation

Motor unit layout algorithms have a significant effect on motor unit fibre densities recorded. Motor unit fibre densities are affected by both the method used to place the motor unit territories, and the mechanism by which muscle fibres are assigned to motor units. The first of these should emulate the process by which separate motor neurons create overlapping territories that cover the muscle cross section, while the second should have some relation to the processes involved with axonal arborization and development of the spatial dispersion of the neuro-muscular junctions. The success of an algorithm in creating physiologically realistic motor unit layouts may be evaluated, in part, by examining the distribution of the muscle fibres assigned to the motor units. This paper examines the motor unit fibre densities found in muscles created by two recent algorithms, and explores the degree to which the concepts used by these algorithms may be shared.

A muscle architecture model offering control over motor unit fiber density distributions

The aim of this study was to develop a muscle architecture model able to account for the observed distributions of innervation ratios and fiber densities of different types of motor units in a muscle. A model algorithm is proposed and mathematically analyzed in order to obtain an inverse procedure that allows, by modification of input parameters, control over the output distributions of motor unit fiber densities. The model's performance was tested with independent data from a glycogen depletion study of the medial gastrocnemius of the rat. Results show that the model accurately reproduces the observed physiological distributions of innervation ratios and fiber densities and their relationships. The reliability and accuracy of the new muscle architecture model developed here can provide more accurate models for the simulation of different electromyographic signals.