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Neural control of synergist muscles is not well understood. Presumably, each muscle in a synergistic group receives some unique neural drive and some drive that is also shared in common with other muscles in the group. In this investigation, we sought to characterize the strength, frequency spectrum, and force dependence of the neural drive to the human vastus lateralis and vastus medialis muscles during the production of isometric knee extension forces at 10 and 30% of maximum voluntary effort. High-density surface electromyography recordings were decomposed into motor unit action potentials to examine the neural drive to each muscle. Motor unit coherence analysis was used to characterize the total neural drive to each muscle and the drive shared between muscles. Using a novel approach based on partial coherence analysis, we were also able to study specifically the neural drive unique to each muscle (not shared). The results showed that the majority of neural drive to the vasti muscles was a cross-muscle drive characterized by a force-dependent strength and bandwidth. Muscle-specific neural drive was at low frequencies (<5 Hz) and relatively weak. Frequencies of neural drive associated with afferent feedback (6 - 12 Hz) and with descending cortical input (similar to 20 Hz) were almost entirely shared by the two muscles, whereas low-frequency (<5 Hz) drive comprised shared (primary) and muscle-specific (secondary) components. This study is the first to directly investigate the extent of shared versus independent control of synergist muscles at the motor neuron level.
A new method is proposed for tracking individual motor units (MUs) across multiple experimental sessions on different days. The technique is based on a novel decomposition approach for high-density surface electromyography and was tested with two experimental studies for reliability and sensitivity. Experiment I (reliability): ten participants performed isometric knee extensions at 10, 30, 50 and 70% of their maximum voluntary contraction (MVC) force in three sessions, each separated by 1 week. Experiment II (sensitivity): seven participants performed 2 weeks of endurance training (cycling) and were tested pre-post intervention during isometric knee extensions at 10 and 30% MVC. The reliability (Experiment I) and sensitivity (Experiment II) of the measured MU properties were compared for the MUs tracked across sessions, with respect to all MUs identified in each session. In Experiment I, on average 38.3% and 40.1% of the identified MUs could be tracked across two sessions (1 and 2 weeks apart), for the vastus medialis and vastus lateralis, respectively. Moreover, the properties of the tracked MUs were more reliable across sessions than those of the full set of identified MUs (intra-class correlation coefficients ranged between 0.63-0.99 and 0.39-0.95, respectively). In Experiment II, similar to 40% of the MUs could be tracked before and after the training intervention and training-induced changes in MU conduction velocity had an effect size of 2.1 (tracked MUs) and 1.5 (group of all identified motor units). These results show the possibility of monitoring MU properties longitudinally to document the effect of interventions or the progression of neuromuscular disorders.
We investigated the possibility to identify motor units (MUs) with high-density surface electromyography (HDEMG) over experimental sessions in different days. 10 subjects performed submaximal knee extensions across three sessions in three days separated by one week, while EMG was recorded from the vastus medialis muscle with high-density electrode grids. The shapes of the MU action potentials (MUAPs) over multiple channels extracted from HDEMG decomposition were matched across sessions by cross-correlation. Forty and twenty percent of the MUs decomposed could be tracked across two and three sessions, respectively (average cross correlation 0.85 +/- 0.04). The estimated properties of the matched motor units were similar across the sessions. For example, mean discharge rate and recruitment thresholds were measured with an intra-class correlation coefficient (ICCs) > 0.80. These results strongly suggest that the same MUs were indeed identified across sessions. This possibility will allow monitoring changes in MU properties following interventions or during the progression of neuromuscular disorders.
Purpose Using a novel technique of high-density surface EMG decomposition and motor unit (MU) tracking, we compared changes in the properties of vastus medialis and vastus lateralis MU after endurance (END) and high-intensity interval training (HIIT). Methods Sixteen men were assigned to the END or the HIIT group (n = 8 each) and performed six training sessions for 14 d. Each session consisted of 8-12 x 60-s intervals at 100% peak power output separated by 75 s of recovery (HIIT) or 90-120 min continuous cycling at similar to 65% VO2peak (END). Pre- and postintervention, participants performed 1) incremental cycling to determine VO2peak and peak power output and 2) maximal, submaximal (10%, 30%, 50%, and 70% maximum voluntary contraction [MVC]), and sustained (until task failure at 30% MVC) isometric knee extensions while high-density surface EMG signals were recorded from the vastus medialis and vastus lateralis. EMG signals were decomposed (submaximal contractions) into individual MU by convolutive blind source separation. Finally, MU were tracked across sessions by semiblind source separation. Results After training, END and HIIT improved VO2peak similarly (by 5.0% and 6.7%, respectively). The HIIT group showed enhanced maximal knee extension torque by similar to 7% (P = 0.02) and was accompanied by an increase in discharge rate for high-threshold MU (50% knee extension MVC) (P < 0.05). By contrast, the END group increased their time to task failure by similar to 17% but showed no change in MU discharge rates (P > 0.05). Conclusions HIIT and END induce different adjustments in MU discharge rate despite similar improvements in cardiopulmonary fitness. Moreover, the changes induced by HIIT are specific for high-threshold MU. For the first time, we show that HIIT and END induce specific neuromuscular adaptations, possibly related to differences in exercise load intensity and training volume.