Cross-bridge mechanics estimated from skeletal muscles' work-loop responses to impacts in legged locomotion

Muscle wobbling mass dynamics: eigenfrequency dependencies on activity, impact strength, and ground material

In legged locomotion, muscles undergo damped oscillations in response to the leg contacting the ground (an impact). How muscle oscillates varies depending on the impact situation. We used a custom-made frame in which we clamped an isolated rat muscle (M. gastrocnemius medialis and lateralis: GAS) and dropped it from three different heights and onto two different ground materials. In fully activated GAS, the dominant eigenfrequencies were 163 Hz, 265 Hz, and 399 Hz, which were signficantly higher (p < 0.05) compared to the dominant eigenfrequencies in passive GAS: 139 Hz, 215 Hz, and 286 Hz. In general, neither changing the falling height nor ground material led to any significant eigenfrequency changes in active nor passive GAS, respectively. To trace the eigenfrequency values back to GAS stiffness values, we developed a 3DoF model. The model-predicted GAS muscle eigenfrequencies matched well with the experimental values and deviated by - 3.8%, 9.0%, and 4.3% from the passive GAS eigenfrequencies and by - 1.8%, 13.3%, and - 1.5% from the active GAS eigenfrequencies. Differences between the frequencies found for active and passive muscle impact situations are dominantly due to the attachment of myosin heads to actin.

Kinematic Modeling at the Ant Scale: Propagation of Model Parameter Uncertainties

Quadrupeds and hexapods are known by their ability to adapt their locomotive patterns to their functions in the environment. Computational modeling of animal movement can help to better understand the emergence of locomotive patterns and their body dynamics. Although considerable progress has been made in this subject in recent years, the strengths and limitations of kinematic simulations at the scale of small moving animals are not well understood. In response to this, this work evaluated the effects of modeling uncertainties on kinematic simulations at small scale. In order to do so, a multibody model of a Messor barbarus ant was developed. The model was built from 3D scans coming from X-ray micro-computed tomography. Joint geometrical parameters were estimated from the articular surfaces of the exoskeleton. Kinematic data of a free walking ant was acquired using high-speed synchronized video cameras. Spatial coordinates of 49 virtual markers were used to run inverse kinematics simulations using the OpenSim software. The sensitivity of the model’s predictions to joint geometrical parameters and marker position uncertainties was evaluated by means of two Monte Carlo simulations. The developed model was four times more sensitive to perturbations on marker position than those of the joint geometrical parameters. These results are of interest for locomotion studies of small quadrupeds, octopods, and other multi-legged animals.