Author(s): WU, R., LIEGEY, J.1, LUO, W.2, JIANG, J.2, SHAO, C.2, CHEN, X.2, WANG, D.2, DE VITO, G.3, LOWERY, M.M.1, Institution: UNIVERSITY COLLEGE DUBLIN, Country: IRELAND, Abstract-ID: 2263

INTRODUCTION:
Muscle fatigue is a complex, multifactorial phenomenon that is accompanied by adjustments in motor unit (MU) recruitment and firing patterns [1]. Although strength- (ST) and endurance-trained (ET) individuals show distinct neuromuscular adaptations, it remains unclear whether their MU behaviour differs in response to fatigue. To date, no study has examined fatigue-induced changes in both groups with MU tracking. This study therefore investigated fatigue-related changes in MU recruitment threshold (RT), firing rate (FR) and conduction velocity (CV) in ST and ET men using high-density surface electromyography (HDsEMG) decomposition with MU tracking to enable within-unit comparisons.
METHODS:
Twelve ST (21.6 ± 2.8 yr) and 11 ET (19.6 ± 2.2 yr) men performed maximal voluntary isometric contractions (MVICs) of the knee extensors, and a trapezoidal contraction at 20%MVIC (5%MVIC·s-1 ramp-up & down) before and immediately after a sustained submaximal isometric contraction at 30% MVIC to task failure. HDsEMG was recorded from the vastus lateralis. A total of 355 MUs were decomposed from the trapezoidal contractions. The RT was determined during the ramp-up, while the mean FR and CV were calculated during the plateau. A multi-dimensional tracking algorithm was then used to track MUs in the pre- and post-fatigue trapezoidal contractions. Approximately 30% of the MUs were successfully tracked between pre and post fatigue.
RESULTS:
Pre-fatigue MVIC was 33% higher in ST than ET (p = 0.026), with no between-group differences observed in post-fatigue MVIC decline or time-to-failure (TTF). Pre-fatigue RT was higher in ST than in ET (14.1 vs. 11.8%MVIC; p = 0.047), with no pre-fatigue differences in FR or CV. At the population level, group × fatigue interactions were observed for RT (p = 0.012) and CV (p = 0.031), with post-fatigue RT (p = 0.012) and CV (p < 0.001) decreasing in ST but not in ET. FR decreased in both groups, with a smaller reduction in ST (8.9%; p = 0.003) than in ET (18.6%; p < 0.001). In tracked MUs, however, only a fatigue main effect was observed, with comparable declines in RT (p = 0.001) and CV (p = 0.01) in both groups, and no change in FR.
CONCLUSION:
Despite similar global fatigue, the population-level MU results indicated distinct neuromuscular strategies. ST exhibited post-fatigue decreases in RT and CV, whereas ET did not. This suggests a post-fatigue shift towards a greater contribution from lower-threshold MUs in ST. However, tracked MU results showed comparable within-unit declines in RT and CV in both groups, indicating similar intrinsic MU adjustments regardless of training status. Overall, the training-specific effect on population-level MUs probably reflects fatigue-related changes in the recruitment of lower-threshold MUs. This is likely due to the differences in fibre-type composition and recruitment strategy, rather than to fundamentally different fatigue responses within individuals MUs.
[1] Contessa et al., (2016)