A computational model of neural activation, force generation and intracellular bioenergetics during muscle fatigue

Abstract

Muscle fatigue, an acute decrease in force‐generating capacity in response to repeated or prolonged activation, is a process whose mechanisms are difficult to discern due to the complicated nature of in vivo voluntary muscle force development. Computational modeling has been used to gain insight into the mechanisms of similarly complicated systems. The neuromuscular response to repeated voluntary activation is an attractive target for this approach. Here, we present a comprehensive model of neuromuscular activation, torque generation, bioenergetics and fatigue that provides a theoretical framework by which hypotheses related to the mechanisms of fatigue might be tested. A series of modular components were formulated, each representing a component of neuromuscular function. Multiple simulations were run to confirm accurate contractile and metabolic predictions when compared with in vivo data. A simulation that emulated a contraction protocol in the literature was run to evaluate the ability of the model to predict fatigue. Overall, the model predicted intracellular metabolic responses similar to in vivo data. Fatigue predicted by the model was within 6.6% of the reference data‐set from the literature, validating this model as a powerful tool for investigating the mechanisms of fatigue in voluntary isometric contractions.