Can a rheological muscle model predict force depression/enhancement?

Area of Science:

• Biomechanics
• Muscle Physiology
• Computational Biology

Background:

• Standard Hill-type models face computational instability on the descending limb of the force-length relation.
• Existing models struggle to accurately predict force enhancement or depression following muscle stretch or shortening.
• A need exists for a more robust phenomenological model of activated muscle.

Purpose of the Study:

• To present a new phenomenological model for activated muscle mechanics.
• To demonstrate the model's ability to reproduce experimental muscle responses.
• To highlight the advantages over conventional Hill-type models.

Main Methods:

• Developed a model combining contractile, elastic, dashpot, and spring elements.
• Derived analytical solutions for specific experimental conditions.
• Validated the model using cat soleus muscle ramp shortening and stretching data.

Main Results:

• The model accurately reproduces cat soleus muscle responses to ramp protocols.
• Computations remain stable on the descending force-length limb.
• Correctly predicts force enhancement after stretching and force depression after shortening.
• The linear version aligns with a linear force-velocity relationship as an emergent property.

Conclusions:

• Activated muscle mechanical responses can be effectively mimicked by a viscoelastic system.
• The proposed model offers improved stability and predictive accuracy compared to Hill-type models.
• This new model provides a valuable tool for studying muscle mechanics and function.