Speaker
Description
Traumatic spinal cord injury (SCI) in humans and many mammals is a non-regenerative condition that can lead to motor function loss and disability. Mechanical factors are increasingly recognized to be influencing spinal cord regeneration, yet accurate characterization of the mechanical behavior of spinal cord tissue is lacking. To address this gap, we employ a multimodal approach that combines indentation test data with macroscale test data conducted on the same sample. The spinal cord is a composite material with grey matter in the center surrounded by white matter, both with distinct mechanical properties. Furthermore, the mechanical behavior exhibits strong variations that are typical for biological systems. Therefore, to obtain insight into the local behavior, indentation experiments are conducted over a spatial grid that includes grey matter, white matter, and the interface between the two. Furthermore, cyclic loading in tension, compression, and torsion of the same sample informs the collective behavior of the tissue under varying large-strain loading conditions. The experiments are followed up with finite element simulations of the indentation and rheometer experiments, incorporating realistic boundary conditions and geometry. By regressing the simulated force data from all the different tests together against the experimental data, we identify the hyperelastic and viscoelastic material parameters of the spinal cord and its individual components.
