Less common synaptic input between muscles from the same group allows for more flexible coordination strategies during a fatiguing task

Abstract

This study aimed to determine whether neural drive is redistributed between muscles during a fatiguing isometric contraction, and if so, whether the initial level of common synaptic input between these muscles constrains this redistribution. We studied two muscle groups: triceps surae (14 participants) and quadriceps (15 participants). Participants performed a series of submaximal isometric contractions and a torque-matched contraction maintained until task failure. We used high-density surface electromyography to identify the behavior of 1874 motor units from the soleus, gastrocnemius medialis (GM), gastrocnemius lateralis(GL), rectus femoris, vastus lateralis (VL), and vastus medialis(VM). We assessed the level of common drive between muscles in absence of fatigue using a coherence analysis. We also assessed the redistribution of neural drive between muscles during the fatiguing contraction through the correlation between their cumulative spike trains (index of neural drive). The level of common drive between VL and VM was significantly higher than that observed for the other muscle pairs, including GL-GM. The level of common drive increased during the fatiguing contraction, but the differences between muscle pairs persisted. We also observed a strong positive correlation of neural drive between VL and VM during the fatiguing contraction (r=0.82). This was not observed for the other muscle pairs, including GL-GM, which exhibited differential changes in neural drive. These results suggest that less common synaptic input between muscles allows for more flexible coordination strategies during a fatiguing task, i.e., differential changes in neural drive across muscles. The role of this flexibility on performance remains to be elucidated.

Inter-muscular networks of synchronous muscle fiber activation

“…Thus, investigations on inter-muscular interactions in the frequency domain have utilized inter-muscular coherence approaches to estimate the amount of common neural input between two muscles during voluntary motor tasks (Ushiyama and Ushiba, 2013), and to quantify the degree of shared neural inputs from cortical, subcortical and spinal influences (Grosse et al, 2002). While spectral coherence approaches have led to important findings relating activity in specific frequency bands to the role of motor cortex (Baker et al, 1997;Chang et al, 2012), impact of movement and fatigue on inter-muscular coordination among distinct muscles (Boonstra et al, 2008, Boonstra et al, 2019Kattla and Lowery, 2010;Kerkman et al, 2018, Kerkman et al, 2020Maillet et al, 2022;Rossato et al, 2022), or coherence modulation with maturation (Kerkman et al, 2022), coherencebased measures reflect linear aspects of interactions between same frequency band (iso-frequency coupling between muscle pairs), and cannot quantify nonlinear dynamic coupling across frequencies (Yang et al, 2018). Thus, crucial information regarding the coupling between distinct types of muscle fibers with different firing rates across muscles is ignored.…”

Handedness is associated with less common input to spinal motor neurons innervating different hand muscles

“…Furthermore, even though cross talk can greatly affect interferential EMG signals (Germer et al ., 2021), it is not a major issue when identifying motor units. Indeed, only a small proportion (< 1%) of motor units were identified as ‘cross-talk’ units in previous studies that verified that the identified motor units did originate from the target muscles on which the grid was placed and did not originate from crosstalk from a neighbouring muscle (Hug et al ., 2021c; Rossato et al ., 2022). Second, despite the fact that we identified a similar (or even a higher) number of motor units than in previous HDsEMG studies that targeted the same muscles (Del Vecchio et al ., 2019; Tanzarella et al ., 2021), we failed to perform each analysis for all of our participants.…”

Handedness is associated with less common input to spinal motor neurons innervating different hand muscles

“…As mentioned above, this lower level of common input may allow more flexibility in the recruitment of motor units and, therefore, in mechanical outputs. In this way, Rossato et al (2022) observed a redistribution of neural drive across synergist muscles during a fatiguing task, but this was only observed between muscles that shared a low level of common drive. In addition, our results are well in line with previous work, which investigated handedness in precision tasks from force signals, and which showed that the thumb and index finger of the dominant hand might be more independently controlled by the central nervous system than the non-dominant digits (Reilly & Hammond, 2004;Li et al, 2015).…”

“…Furthermore, even though cross talk can greatly affect interferential EMG signals (Germer et al, 2021), it is not a major issue when identifying motor units. Indeed, only a small proportion (< 1%) of motor units were identified as 'cross-talk' units in previous studies that verified that the identified motor units did originate from the target muscles on which the grid was placed and did not originate from crosstalk from a neighbouring muscle (Hug et al, 2021c;Rossato et al, 2022). Second, despite the fact that we identified a similar (or even a higher) number of motor units than in previous HDsEMG studies that targeted the same muscles (Del Vecchio et al, 2019;Tanzarella et al, 2021), we failed to perform each analysis for all of our participants.…”