Walking and running are mechanically and energetically different locomotion modes. For selecting one or another, speed is a parameter of paramount importance. Yet, both are likely controlled by similar low-dimensional neuronal networks that reflect in patterned muscle activations called muscle synergies. Here, we challenged human locomotion by having our participants walk and run at a very broad spectrum of submaximal and maximal speeds. The synergistic activations of lower limb locomotor muscles were obtained through decomposition of electromyographic data via non-negative matrix factorization. We analyzed the duration and complexity (via fractal analysis) over time of motor primitives, the temporal components of muscle synergies. We found that the motor control of high-speed locomotion was so challenging that the neuromotor system was forced to produce wider and less complex muscle activation patterns. The motor modules, or time-independent coefficients, were redistributed as locomotion speed changed. These outcomes show that humans cope with the challenges of high-speed locomotion by adapting the neuromotor dynamics through a set of strategies that allow for efficient creation and control of locomotion.

High-speed ultrasonography has revealed that, in human locomotion, the nature of fascicle and tendon length changes varies depending on the task, contraction intensity, and the muscles involved. The findings emphasize that the active fascicles of the gastrocnemius muscle are suddenly stretched, although they are shortening. This short-lasting stretch triggers the stretch reflex, timing of which is dependent on running speed.

Aim: The specificity of muscle‐tendon and foot architecture of elite Kenyan middle‐ and long‐distance runners has been found to contribute to their superior running performance. To investigate the respective influence of genetic endowment and training on these characteristics, we compared leg and foot segmental lengths as well as muscle‐tendon architecture of Kenyans and Japanese males (i) from infancy to adulthood and (ii) non‐athletes versus elite runners.Methods: The 676 participants were divided according to their nationality (Kenyans and Japanese), age (nine different age groups for non‐athletes) and performance level in middle‐ and long‐distance races (non‐athlete, non‐elite and elite adult runners). Shank and Achilles tendon (AT) lengths, medial gastrocnemius (MG) fascicle length, pennation angle and muscle thickness, AT moment arm (MA_AT), and foot lever ratio were measured.Results: Above 8 years old, Kenyans had a longer shank and AT, shorter fascicle, greater pennation angle, thinner MG muscle as well as longer MA_AT, with lower foot lever ratio than age‐matched Japanese. Among adults of different performance levels and independently of the performance level, Kenyans had longer shank, AT and MA_AT, thinner MG muscle thickness, and lower foot lever ratio than Japanese. The decrease in MG fascicle length and increase pennation angle observed for the adult Japanese with the increase in performance level resulted in a lack of difference between elite Kenyans and Japanese.Conclusion: The specificity of muscle‐tendon and foot architecture of elite Kenyan runners could result from genetic endowment and contribute to the dominance of Kenyans in middle‐ and long‐distance races.

This study aimed to compare different ultrasound devices with magnetic resonance spectroscopy (MRS) to quantify muscle lipid content from echo intensity (EI). Four different ultrasound devices were used to measure muscle EI and subcutaneous fat thickness in four lower-limb muscles. Intramuscular fat (IMF), intramyocellular (IMCL) and extramyocellular lipids (EMCL) were measured using MRS. Linear regression was used to compare raw and subcutaneous fat thickness-corrected EI values to IMCL, EMCL and IMF. IMCL had a poor correlation with muscle EI (r = 0.17–0.32, NS), while EMCL (r = 0.41–0.84, p < 0.05–p < 0.001) and IMF (r = 0.49–0.84, p < 0.01–p < 0.001) had moderate to strong correlation with raw EI. All relationships were improved when considering the effect of subcutaneous fat thickness on muscle EI measurements. The slopes of the relationships were similar across devices, but there were some differences in the y-intercepts when raw EI values were used. These differences disappeared when subcutaneous fat thickness-corrected EI values were considered, allowing for the creation of generic prediction equations (r = 0.41–0.68, p < 0.001). These equations can be used to quantify IMF and EMCL within lower limb muscles from corrected-EI values in non-obese subjects, regardless of the ultrasound device used.

This study aimed to simultaneously examine the differences of human nerve conduction velocity (NCV) and nerve cross-sectional area (nCSA) between the upper and lower limbs and between different regions of the upper and lower limbs. Thirty healthy subjects volunteered for the study. NCV and nCSA of the ulnar and tibial nerves were measured with the dominant and non-dominant arms and the supporting and reacting legs using supramaximal electric stimulation and peripheral nerve ultrasonography at three regions for ulnar and tibial nerves, respectively. Supramaximal electric stimulation was superficially applied to the ulnar and tibial nerves at each point. These action potentials were recorded from the digiti minimi and soleus muscles for the ulnar and tibial nerves, respectively. Our results clearly showed that the NCV, nCSA, and circumference of the ulnar and tibial nerves were higher and greater in the lower limbs than in the upper limbs. The greater the circumference, the greater the nCSA for both the upper and lower limbs. However, unlike the upper limbs, the supporting leg did not have higher NCV than the reacting leg despite its greater circumference. Therefore, nCSA can be related to the circumference but not necessarily function for NCV developments of the lower limbs. These various aspects between the upper and lower limbs suggest that NCV does not depend on the nCSA sizes or upper and lower limb circumference; the results indicate the existence of limb-specific NCV but not nCSA developments.

Walking and running are mechanically and energetically different locomotion modes. For selecting one or another, speed is a parameter of paramount importance. Yet, both are likely controlled by similar low-dimensional neuronal networks that reflect in patterned muscle activations called muscle synergies. Here, we investigated how humans synergistically activate muscles during locomotion at different submaximal and maximal speeds. We analysed the duration and complexity (or irregularity) over time of motor primitives, the temporal components of muscle synergies. We found that the challenge imposed by controlling high-speed locomotion forces the central nervous system to produce muscle activation patterns that are wider and less complex relative to the duration of the gait cycle. The motor modules, or time-independent coefficients, were redistributed as locomotion speed changed. These outcomes show that robust locomotion control at challenging speeds is achieved by modulating the relative contribution of muscle activations and producing less complex and wider control signals, whereas slow speeds allow for more irregular control.