Precise computational modelling of the brain-skull interface is necessary for the prediction, prevention and treatment of acquired brain-injuries. The brain-skull interface comprises complex layers including the osseous cranial tissues, meninges, sub-arachnoidal space and tissues, cerebrospinal fluid (CSF), pia mater and the gray and white cerebral matter. While the tissue properties of the brain-skull interface are known, there is no consensus on how these layers interact during head impact. To generate computational models of the brain-skull interface with greater accuracy, knowing the boundary conditions or constraints is necessary. Previous experimental studies have relied on modelling the deformation of the brain-skull interface using neural density targets (NDTs) implanted into the cadaver brain, collecting information on tissue displacement during front and rear impact in motor vehicle crash-tests.
Wang et al. (2018) utilized computational bio-mechanics and finite element analysis (FEA), placing nodes in the 3D model in close approximation to the position of the experimental NDTs. Four hypotheses of the brain-skull interface were modeled, each approach placing different boundary conditions to model deformation during simulated head impact. All analyses were validated against previous experimental studies. Results showed that how the brain-skull interface was modeled appreciably affected the results. The 3D model showing the closest agreement with the experimental data, included all tissues of the brain-skull interface, allowed for displacement without separation of the skull and brain tissues, and strongly corresponded with known neuroanatomy. This 3D model indicated that non-linear stress-strain associations between brain and skull tissues best matched experimental results. Further, this 3D model could be closely predicted using an Ogden Hyperviscoelastic Constitutive model which did not over- or under-estimate deformations during head impact. The risks of over- and under-estimating head impact during motor vehicle accidents has implications for vehicle construction and prevention of serious brain trauma during accidents. Ultimately, a better understanding of the interaction between layers of the brain-skull interface can produce more accurate predictions of the likely impact during motor vehicle accidents and prevent violent head injury. Extrapolation of this research into paleoneurology could allow investigations into the structural interaction between the brain and braincase, testing if the resistence of brain-skull tissues during deformation evolved in human species as primary adaptations or secondary adjustments such as allometric responses.