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Updated: Jul 18, 2026

Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry
Published on: September 6, 2016
On the potential importance of non-linear viscoelastic material modelling for numerical prediction of brain tissue
Dave W A Brands1, Peter H M Bovendeerd, Jac S H M Wismans
1Eindhoven University of Technology, Eindhoven, The Netherlands.
Abstract:
In current Finite Element (FE) head models, brain tissue is commonly assumed to display linear viscoelastic material behaviour. However, brain tissue behaves like a non-linear viscoelastic solid for shear strains above 1%. The main objective of this study was to study the effect of non-linear material behaviour on the predicted brain response. We used a non-linear viscoelastic constitutive model, developed on the basis of experimental shear data presented elsewere. First we tested the numerical implementation of the constitutive model by simulating the response of a silicone gel (Sylgard 572 A&B) filled cylindrical cup, subjected to a transient rotational acceleration. The experimental results could be reproduced within 9%. Subsequently, the effect of non-linear material modelling on computed brain response was investigated in an existing three-dimensional head model subjected to an eccentric rotation. At the applied external load strains in the brain were approximately ten times larger than was expected on the basis of published data. This is probably caused by the values of the shear moduli applied in the model. These are at least a factor of ten lower than the ones used in head models in literature but comparable to material data in recent literature. Non-linear material behaviour was found to influence the levels of predicted strains (+20%) and stresses (-11%) but not their temporal and spatial distribution. The pressure response was independent of non-linear material behaviour. In fact it could be predicted by the equilibrium of momentum, and thus it is independent of the choice of the brain constitutive model.
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