Souza de Oliveira, D. | Search bioRxiv

bioRxiv2022

Mental fatigue impairs physical performance but not the neural drive to the muscle

Mental fatigue (MF) does not only affect cognitive but also physical performance. This study aimed to explore the effects of MF on muscle endurance, rate of perceived exertion (RPE), and motor units activity. Ten healthy males participated in a randomised crossover study. The subjects attended two identical experimental sessions separated by three days with the only difference of a cognitive task (incongruent Stroop task [ST]) and a control condition (watching a documentary). Perceived MF and motivation were measured for each session at baseline and after each cognitive task. Four contractions at 20% of maximal voluntary contraction (MVIC) were performed at baseline, after each cognitive and after muscle endurance task while measuring motor units by high-density surface electromyography. Muscle endurance until failure at 50% of MVIC was measured after each cognitive task and the RPE was measured right after failure. ST significantly increased MF (p = 0.001) reduced the motivation (p = 0.008) for the subsequent physical task and also impaired physical performance (p = 0.044). However, estimates of common synaptic inputs and motor unit discharge rates as well as RPE were not affected by MF (p> 0.11). In conclusion, MF impairs muscle endurance and motivation for the physical task but not the neural drive to the muscle at any frequency bands. Although it is physiologically possible for mentally fatigued subjects to generate an optimal neuromuscular function, the altered perception and motivation seems to limit physical performance. Our results suggest that the corticospinal pathways are not affected by MF.

physiology↗

bioRxiv2022

Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units

ObjectiveHigh-density surface electromyography (HD-sEMG) allows the reliable identification of individual motor unit (MU) action potentials. Despite the accuracy in decomposition, there is a large variability in the number of identified MUs across individuals and exerted forces. Here we present a systematic investigation of the anatomical and neural factors that determine this variability. ApproachWe investigated factors of influence on HD-sEMG decomposition, such as synchronization of MU discharges, distribution of MU territories, muscle-electrode distance (MED - subcutaneous fat thickness), maximum anatomical cross-sectional area (ACSAmax), and fiber CSA. For this purpose, we recorded HD-sEMG signals, ultrasound, magnetic resonance imaging, and muscle biopsy of the biceps brachii muscle from two groups of participants - untrained-controls (UT=14) and strength-trained (>3 years of training, ST=16) - while they performed isometric ramp contractions with elbow flexors (at 15, 35, 50 and 70% maximum voluntary torque - MVT). We assessed the correlation between the number of accurately detected MUs by HD-sEMG decomposition and each measured parameter, for each target force level. Multiple regression analysis was then applied. Main resultsST subjects showed lower MED (UT: 4.8 {+/-} 1.4 vs. ST: 3.7 {+/-} 0.8 mm) associated to a greater number of identified motor units (UT: 21.3 {+/-} 10.2 vs. ST: 29.2 {+/-} 11.8 MUs/subject). Both groups showed a negative correlation between MED and the number of identified MUs at low forces (r= -0.6, p=0.002 at 15% MVT). Moreover, the number of identified MUs was positively correlated to the distribution of MU territories (r=0.56, p=0.01) and ACSAmax (r=0.48, p=0.03) at 15% MVT. By accounting for all anatomical parameters, we were able to partly predict the number of decomposed MUs at low but not at high forces. SignificanceOur results confirmed the influence of subcutaneous tissue on the quality of HD-sEMG signals and demonstrated that MU spatial distribution and ACSAmax are also relevant parameters of influence for current decomposition algorithms.

bioengineering↗