Key points: Previous studies have indicated that several weeks of strength training is sufficient to elicit significant adaptations in the neural drive sent to the muscles. There are few data, however, on the changes elicited by strength training in the recruitment and rate coding of motor units during voluntary contractions. We show for the first time that the discharge characteristics of motor units in the tibialis anterior muscle tracked across the intervention are changed by 4 weeks of strength training with isometric voluntary contractions. The specific adaptations included significant increases in motor unit discharge rate, decreases in the recruitment‐threshold force of motor units and a similar input–output gain of the motor neurons. The findings suggest that the adaptations in motor unit function may be attributable to changes in synaptic input to the motor neuron pool or to adaptations in intrinsic motor neuron properties. The strength of a muscle typically begins to increase after only a few sessions of strength training. This increase is usually attributed to changes in the neural drive to muscle as a result of adaptations at the cortical or spinal level. We investigated the change in the discharge characteristics of large populations of longitudinally tracked motor units in tibialis anterior before and after 4 weeks of strength training the ankle‐dorsiflexor muscles with isometric contractions. The adaptations exhibited by 14 individuals were compared with 14 control subjects. High‐density electromyogram grids with 128 electrodes recorded the myoelectric activity during isometric ramp contractions to the target forces of 35%, 50% and 70% of maximal voluntary force. The motor unit recruitment and derecruitment thresholds, discharge rate, interspike intervals and estimates of synaptic inputs to motor neurons were assessed. The normalized recruitment‐threshold forces of the motor units were decreased after strength training (P < 0.05). Moreover, discharge rate increased by 3.3 ± 2.5 pps (average across subjects and motor units) during the plateau phase of the submaximal isometric contractions (P < 0.001). Discharge rates at recruitment and derecruitment were not modified by training (P < 0.05). The association between force and motor unit discharge rate during the ramp‐phase of the contractions was also not altered by training (P < 0.05). These results demonstrate for the first time that the increase in muscle force after 4 weeks of strength training is the result of an increase in motor neuron output from the spinal cord to the muscle.

Key points: We propose and validate a method for accurately identifying the activity of populations of motor neurons during contractions at maximal rate of force development in humans. The behaviour of the motor neuron pool during rapid voluntary contractions in humans is presented. We show with this approach that the motor neuron recruitment speed and maximal motor unit discharge rate largely explains the individual ability in generating rapid force contractions. The results also indicate that the synaptic inputs received by the motor neurons before force is generated dictate human potential to generate force rapidly. This is the first characterization of the discharge behaviour of a representative sample of human motor neurons during rapid contractions. During rapid contractions, motor neurons are recruited in a short burst and begin to discharge at high frequencies (up to >200 Hz). In the present study, we investigated the behaviour of relatively large populations of motor neurons during rapid (explosive) contractions in humans, applying a new approach to accurately identify motor neuron activity simultaneous to measuring the rate of force development. The activity of spinal motor neurons was assessed by high‐density electromyographic decomposition from the tibialis anterior muscle of 20 men during isometric explosive contractions. The speed of motor neuron recruitment and the instantaneous motor unit discharge rate were analysed as a function of the impulse (the time–force integral) and the maximal rate of force development. The peak of motor unit discharge rate occurred before force generation and discharge rates decreased thereafter. The maximal motor unit discharge rate was associated with the explosive force variables, at the whole population level (r² = 0.71 ± 0.12; P < 0.001). Moreover, the peak motor unit discharge and maximal rate of force variables were correlated with an estimate of the supraspinal drive, which was measured as the speed of motor unit recruitment before the generation of afferent feedback (P < 0.05). We show for the first time the full association between the effective neural drive to the muscle and human maximal rate of force development. The results obtained in the present study indicate that the variability in the maximal contractile explosive force of the human tibialis anterior muscle is determined by the neural activation preceding force generation.

Purpose: Motor unit conduction velocity (MUCV) represents the propagation velocity of action potentials along the muscle fibers innervated by individual motor neurons and indirectly reflects the electrophysiological properties of the sarcolemma. In this study, we investigated the effect of a 4-wk strength training intervention on the peripheral properties (MUCV and motor unit action potential amplitude, RMS_MU) of populations of longitudinally tracked motor units (MU).Methods: The adjustments exhibited by 12 individuals who participated in the training (INT) were compared with 12 controls (CON). Strength training involved ballistic (4 × 10) and sustained (3 × 10) isometric ankle dorsiflexions. Measurement sessions involved the recordings of maximal voluntary isometric force and submaximal isometric ramp contractions, whereas high-density surface EMG was recorded from the tibialis anterior. High-density surface EMG signals were decomposed into individual MU discharge timings, and MU was tracked across the intervention.Results: Maximal voluntary isometric force (+14.1%,P= 0.003) and average MUCV (+3.0%,P= 0.028) increased in the INT group, whereas normalized MU recruitment threshold (RT) decreased (−14.9%,P= 0.001). The slope (rate of change) of the regression between MUCV and MU RT increased only in the INT group (+32.6%,P= 0.028), indicating a progressive greater increase in MUCV for higher-threshold MU. The intercept (initial value) of MUCV did not change after the intervention (P= 0.568). The association between RMS_MUand MU RT was not altered by the training.Conclusion: The increase in the rate of change in MUCV as a function of MU RT, but not the initial value of MUCV, suggests that short-term strength training elicits specific adaptations in the electrophysiological properties of the muscle fiber membrane in high-threshold MU.

Objective. High-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. Approach . We investigated factors of influence on HD-sEMG decomposition, such as synchronization of MU discharges, distribution of MU territories, muscle-electrode distance (MED—subcutaneous adipose tissue thickness), maximum anatomical cross-sectional area (ACSA _max ), and fiber cross-sectional area. For this purpose, we recorded HD-sEMG signals, ultrasound and magnetic resonance images, and took a muscle biopsy from the biceps brachii muscle from 30 male participants drawn from two groups to ensure variability within the factors—untrained-controls (UT = 14) and strength-trained individuals (ST = 16). Participants 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 results. ST subjects showed lower MED (UT = 5.1 ± 1.4 mm; ST = 3.8 ± 0.8 mm) and a greater number of identified MUs (UT: 21.3 ± 10.2 vs ST: 29.2 ± 11.8 MUs/subject across all force levels). The entire cohort 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 ACSA _max ( 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. Significance. Our results confirmed the influence of subcutaneous tissue on the quality of HD-sEMG signals and demonstrated that MU spatial distribution and ACSA _max are also relevant parameters of influence for current decomposition algorithms.

Resistance training has been proposed as a valid practice to counteract the aging effect on body mass and its components, which can be easily evaluated though the bioelectrical impedance analysis. This study aimed to achieve a systematic review with meta-analysis on the impact of resistance training on bioelectrical proprieties in older adults.A literature review was done in four electronic databases up to 1 January 2022. The inclusion criteria were: (i) participants aged ≥ 60 years; (ii) resistance training lasted ≥ 8 weeks; (iii) measurement of raw bioelectrical parameters in randomized controlled study designs.The outcomes of the trial had to be bioelectrical phase angle (PhA), resistance (R), and reactance (Xc). The methodological quality was assessed using the Rosendal scale.Overall, seven studies with a total of 344 participants were eligible for the analysis. The quality assessment yielded a score of 71.3%. Bioelectrical PhA (0.52 degree [95%CI 0.32, 0.71], p < 0.001) and Xc (3.58 ohms [95%CI 1.97, 5.19], p < 0.001) increased, whereas R decreased (-28.50 ohms [95%CI -41.39, -15.60], p < 0.001) after the resistance training programs.In this meta-analysis, resistance training promoted increases of PhA, which result from an increase in Xc concomitant with a reduction in R. According to the bioimpedance vector analysis, resistance-trained people experienced a beneficial leftward vector displacement, whilst inactivity induced a rightward vector displacement within the R-Xc graph. In future, more sophisticated and rigorous studies that address specific criteria, methods and targeted designs are required to identify which equipment and protocols allow for an optimization of the resistance training effects.Registration code in PROSPERO: CRD42020168057.