Insights into the Microstructural Origin of Brain Viscoelasticity - Reiter, Nina; Roy, Biswaroop; Paulsen, Friedrich; Budday, Silvia (Journal of Elasticity, 2021)
Mechanical aspects play an important role in brain development, function, and disease. Therefore, continuum-mechanics-based computational models are a valuable tool to advance our understanding of mechanics-related physiological and pathological processes in the brain. Currently, mainly phenomenological material models are used to predict the be- havior of brain tissue numerically. The model parameters often lack physical interpretation and only provide adequate estimates for brain regions which have a similar microstructure and age as those used for calibration. These issues can be overcome by establishing advanced constitutive models that are microstructurally motivated and account for regional heterogeneities through microstructural parameters. In this work, we perform simultaneous compressive mechanical loadings and microstruc- tural analyses of porcine brain tissue to identify the microstructural mechanisms that under- lie the macroscopic nonlinear and time-dependent mechanical response. Based on experimental insights into the link between macroscopic mechanics and cellular rearrangements, we propose a microstructure-informed finite viscoelastic constitutive model for brain tissue. We determine a relaxation time constant from cellular displacement curves and introduce hyperelastic model parameters as linear functions of the cell density, as determined through histological staining of the tested samples. The model is calibrated using a combination of cyclic loadings and stress relaxation experiments in compression. The presented consider- ations constitute an important step towards microstructure-based viscoelastic constitutive models for brain tissue, which may eventually allow us to capture regional material hetero- geneities and predict how microstructural changes during development, aging, and disease affect macroscopic tissue mechanics.
Keywords: Brain tissue; Finite viscoelasticity; Microstructure; Constitutive modeling; Parameter identification