Sensitivity of muscle force response of a two-state cross-bridge model to variations in model parameters

Muscle models based on the cross-bridge theory (Huxley-type models) are frequently used to calculate muscle forces for different contractile conditions. Dynamic and nonlinear characteristics of muscle forces produced during isometric, concentric, and eccentric contractions can be represented to a limited extent by using cross-bridge models. Cross-bridge models use various parameters to simulate force responses. However, there remains uncertainty as to the effect of changes in model parameters on force responses in Huxley-type models. In this study, we aimed to analyze the sensitivity of force response to changes in model parameters in Huxley-type models. A two-state Huxley model was used to determine the cross-bridge attachment distributions and forces for shortening and lengthening contractions. Sensitivity of muscle force to changes in attachment rate, detachment rate, and cross-bridge binding distance was examined within a range of +/- 20% of the nominal value using Monte Carlo simulations. Changes in the detachment rate influenced the predicted muscle forces the most for lengthening contractions, while changes in attachment rate and binding distance affected forces the most for shortening contractions. These results show once more the asymmetry between shortening and lengthening contractions and the difficulty in using a single cross-bridge model to predict forces during shortening and elongation accurately.

Automated summary

Muscle models based on the cross-bridge theory can represent the dynamic and nonlinear characteristics of muscle forces. Sensitivity analysis of a Huxley model showed that changes in detachment rate had the greatest effect on muscle forces during lengthening contractions, while changes in attachment rate and binding distance had the greatest effect on forces during shortening contractions. These results highlight the asymmetry between shortening and lengthening contractions and the challenges of accurately predicting forces using a single cross-bridge model.