How motor unit recruitment speed and discharge rates determine the rate of force development

The degree of neural activation of a muscle is composed of (i) the number of activated motor units (MUs) (recruitment) and (ii) the discharge rate at which these MUs fire (rate coding). The speed of MU recruitment and the discharge rate determine the rate of force development. The quicker the recruitment and the faster the discharge rate, the more force per time is developed. Information about how recruitment and discharge rates develop over the time course of a contraction is crucial for the understanding of neural mechanisms underlying rapid force production. The study of Del Vecchio et al. (2019b), published in this issue of The Journal of Physiology, substantially contributes to this knowledge.

In this study, twenty human subjects performed isometric explosive ankle dorsal flexions up to a target force of 75% of their maximal voluntary force, with a subsequent 3 s holding period. The authors exploited novel multi‐channel electrode recordings in combination with advanced signal processing algorithms to determine discharge times of single MUs. Thus, high‐density surface electromyography (HDsEMG) was administered over the tibialis anterior muscle that enabled the authors to non‐invasively record electrical muscle potentials from 64 channels. Using advanced decomposition algorithms (blind source separation methods) (Farina et al. 2016), the authors were able to track a sample of 242 MUs, with an average of 12.1 ± 5.7 (mean ± standard deviation) per subject. Statistical validity and reliability analyses performed in this and a companion study (Del Vecchio et al. 2019a) suggest that the method is feasible to track discharge times of MUs within and across multiple sessions.

The results of Del Vecchio et al. (2019b) indicate that the recruitment of all tracked MUs is accomplished within a relatively short time window (54.5 ± 30.8 ms) after initiation of the contraction. Even though a large variability in the maximal discharge rates was observed across all subjects (range 8.56–227.7 pulses s⁻¹), maximal discharge rates were fully reached during the initial neuromechanical delay phase, and the discharge rates mitigated during the steady plateau phase. Interestingly, the maximal and averaged discharge rate in the first 35 ms of the contraction predicted the magnitude of the produced rapid force, while discharge rates calculated in the time window after the initial 40 ms did not. The speed of MU recruitment was further positively correlated to mean and maximal discharge rates, indicating that subjects with faster MU recruitment also had higher discharge rates.

The data suggest that the neural drive produced in the initial phase of an explosive contraction is crucial for the rate of force development. It is likely that this neural drive originates from supraspinal structures rather than spinal reflex circuities. Proprioceptive feedback would require at least 30 ms in the lower leg muscles to reach the spinal cord and contribute to MU recruitment. Two previous studies provided evidence that short‐latency corticospinal connections originating from the primary motor cortex may be substantial for MU recruitment in the initial phase of an explosive contraction. In a study testing human participants (Nielsen & Petersen, 1995), excitability of short‐latency corticospinal pathways was greatest at the beginning of an explosive isometric plantarflexion, while it abruptly attenuated 50 ms after contraction onset. The excitability of short‐latency corticospinal pathways at the onset of the contraction was further positively correlated with the speed of the contraction (Nielsen & Petersen, 1995). In a second study performed in non‐human primates, recordings from neurons in the motor cortex with direct connections to spinal motor neurons showed increased firing rates before and at the onset of a contraction, while their discharge rates decreased after movement onset (Cheney & Fetz, 1980).

To conclude, the study by Del Vecchio et al. (2019b) published in The Journal of Physiology reveals important information concerning the neural control of explosive muscular contractions. By exploiting developments in electrode technology and signal processing algorithms, the authors propose a powerful method with which large numbers of MUs can be tracked within and across multiple sessions in humans (see also Del Vecchio et al. 2019a). This approach surpasses previous methods that are limited by the invasive nature of intramuscular wire/needle electrode recordings and the restricted number of MUs that can be discriminated (Farina et al. 2016). In the future, the method could be validated for other muscles, e.g. muscles of the forearm involved in the control of dexterous movements of the hand. Decoding the discharge characteristics of MU populations from different muscles may be a promising avenue for future questions related to motor control, which might include (i) assessment of functional MU changes accompanying motor practice/learning or (ii) the antagonistic and synergist MU interplay in distinct movements (coordinated activation of MUs). Moreover, it remains to be shown whether the approach can be applied to questions concerning the interaction of spinal motor neurons and cortical motor areas. Future studies could tackle this issue by combining HDsEMG recordings with electroencephalography, which allows assessment of corticomuscular coupling using coherence analyses. Another possible approach is to combine HDsEMG recordings with neuromodulation techniques such as transcranial magnetic stimulation or transcranial direct current stimulation, which have been shown to induce neuroplasticity at the corticospinal level and improve functional parameters such as motor learning ability. Lastly, as the present study was carried out with recreationally active individuals, HDsEMG could be used in further studies in order to validate these findings in older individuals or patients suffering from movement disabilities. Identifying alterations in neural drive in these populations might contribute to the understanding of human deconditioning with ageing and the consequences of different diseases on MU function.

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Competing interests

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