The purpose of our study was to identify the low-dimensional latent components, defined hereafter as motor unit modes, underlying the discharge rates of the motor units in two knee extensors (vastus medialis and lateralis, eight men) and two hand muscles (first dorsal interossei and thenars, seven men and one woman) during submaximal isometric contractions. Factor analysis identified two independent motor unit modes that captured most of the covariance of the motor unit discharge rates. We found divergent distributions of the motor unit modes for the hand and vastii muscles. On average, 75% of the motor units for the thenar muscles and first dorsal interosseus were strongly correlated with the module for the muscle in which they resided. In contrast, we found a continuous distribution of motor unit modes spanning the two vastii muscle modules. The proportion of the muscle-specific motor unit modes was 60% for vastus medialis and 45% for vastus lateralis. The other motor units were either correlated with both muscle modules (shared inputs) or belonged to the module for the other muscle (15% for vastus lateralis). Moreover, coherence of the discharge rates between motor unit pools was explained by the presence of shared synaptic inputs. In simulations with 480 integrate-and-fire neurons, we demonstrate that factor analysis identifies the motor unit modes with high levels of accuracy. Our results indicate that correlated discharge rates of motor units that comprise motor unit modes arise from at least two independent sources of common input among the motor neurons innervating synergistic muscles.SIGNIFICANCE STATEMENTIt has been suggested that the nervous system controls synergistic muscles by projecting common synaptic inputs to the engaged motor neurons. In our study, we reduced the dimensionality of the output produced by pools of synergistic motor neurons innervating the hand and thigh muscles during isometric contractions. We found two neural modules, each representing a different common input, that were each specific for one of the muscles. In the vastii muscles, we found a continuous distribution of motor unit modes spanning the two synergistic muscles. Some of the motor units from the homonymous vastii muscle were controlled by the dominant neural module of the other synergistic muscle. In contrast, we found two distinct neural modules for the hand muscles.

Objective Public life restrictions associated with the COVID-19 pandemic caused reductions in physical activity (PA) and decreases in mental and somatic health. Considering the interplay between these factors, we investigated the effects of digital home exercise (DHE) during government-enforced lockdowns. Methods A multicentre randomised controlled trial was performed allocating healthy individuals from nine countries (N=763; 523 female) to a DHE or an inactive control group. During the 4-week main intervention, DHE members engaged in live-streamed multicomponent home exercise. Subsequently, both groups had access to prerecorded workouts for an additional 4 weeks. Outcomes, assessed weekly, included PA level (Nordic Physical Activity Questionnaire-Short), anxiety (Generalized Anxiety Disorder Scale-7), mental well-being (WHO-5 Questionnaire), sleep quality (Medical Outcome Study Sleep Scale), pain/disability (Chronic Pain Grade Scale) and exercise motivation (Self-Concordance Scale). Mixed models were used for analysis. Results Live-streamed DHE consistently increased moderate PA (eg, week 1: 1.65 times more minutes per week, 95% CI 1.40 to 1.94) and vigorous PA (eg, week 1: 1.31 times more minutes per week, 95% CI 1.08 to 1.61), although the effects decreased over time. In addition, exercise motivation, sleep quality and anxiety were slightly improved for DHE in the 4-week live streaming period. The same applied to mental well-being (mean difference at week 4: +0.99, 95% CI 0.13 to 1.86), but an inverted trend was observed after live streaming was substituted by prerecorded exercise. Conclusions Live-streamed DHE represents an efficacious method to enhance PA and selected markers of health during pandemic-related public life restrictions. However, research on implementation is warranted to reduce dropout rates. Trial Registration number DRKS00021273.

Because of the biophysical relation between muscle fibre diameter and the propagation velocity of action potentials along the muscle fibres, motor unit conduction velocity could be a non‐invasive index of muscle fibre size in humans. However, the relation between motor unit conduction velocity and fibre size has been only assessed indirectly in animal models and in human patients with invasive intramuscular EMG recordings, or it has been mathematically derived from computer simulations. By combining advanced non‐invasive techniques to record motor unit activity in vivo, i.e. high‐density surface EMG, with the gold standard technique for muscle tissue sampling, i.e. muscle biopsy, here we investigated the relation between the conduction velocity of populations of motor units identified from the biceps brachii muscle, and muscle fibre diameter. We demonstrate the possibility of predicting muscle fibre diameter (R² = 0.66) and cross‐sectional area (R² = 0.65) from conduction velocity estimates with low systematic bias (∼2% and ∼4% respectively) and a relatively low margin of individual error (∼8% and ∼16%, respectively). The proposed neuromuscular interface opens new perspectives in the use of high‐density EMG as a non‐invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling. The non‐invasive nature of high‐density surface EMG for the assessment of muscle fibre size may be useful in studies monitoring child development, ageing, space and exercise physiology, although the applicability and validity of the proposed methodology need to be more directly assessed in these specific populations by future studies. image Key points: Because of the biophysical relation between muscle fibre size and the propagation velocity of action potentials along the sarcolemma, motor unit conduction velocity could represent a potential non‐invasive candidate for estimating muscle fibre size in vivo. This relation has been previously assessed in animal models and humans with invasive techniques, or it has been mathematically derived from simulations. By combining high‐density surface EMG with muscle biopsy, here we explored the relation between the conduction velocity of populations of motor units and muscle fibre size in healthy individuals. Our results confirmed that motor unit conduction velocity can be considered as a novel biomarker of fibre size, which can be adopted to predict muscle fibre diameter and cross‐sectional area with low systematic bias and margin of individual error. The proposed neuromuscular interface opens new perspectives in the use of high‐density EMG as a non‐invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling.

This study aimed at: (1) Reporting COVID‐19 symptoms and duration in professional football players; (2) comparing players’ pulmonary function before and after COVID‐19; (3) comparing players’ metabolic power (P_met) before and after COVID‐19. Thirteen male players (Age: 23.9 ± 4.0 years, V̇O_2peak: 49.7 ± 4.0 mL/kg/min) underwent a medical screening and performed a running incremental step test and a spirometry test after COVID‐19. Spirometric data were compared with the ones collected at the beginning of the same season. Players’ mean P_met of the 10 matches played before COVID‐19 was compared with mean P_met of the 10 matches played after COVID‐19. Players completed a questionnaire on COVID‐19 symptoms and duration 6 months following the disease. COVID‐19 positivity lasted on average 15 ± 5 days. “General fatigue” and “muscle fatigue” symptoms were reported by all players during COVID‐19 and persisted for 77% (general fatigue) and 54% (muscle fatigue) of the players for 37 ± 28 and 38 ± 29 days after the disease, respectively. No significant changes in spirometric measurements were found after COVID‐19, even though some impairments at the individual level were observed. Conversely, a linear mixed‐effects model analysis showed a significant reduction of P_met (−4.1 ± 3.5%) following COVID‐19 (t = −2.686, p < 0.05). “General fatigue” and “muscle fatigue” symptoms may persist for several weeks following COVID‐19 in professional football players and should be considered for a safer return to sport. Players’ capacity to compete at high intensities might be compromised after COVID‐19.