The 81st Annual Meeting of the American Association of Physical Anthropologists (2012)


Making functional and dietary inferences using FEA: approximations in modelling

PAUL O'HIGGINS1, MICHAEL J. FAGAN2, MIGUEL PRÔA1 and LAURA C. FITTON1.

1Centre for Anatomical & Human Sciences, Hull York Medical School, University of York, UK, 2Department of Engineering, University of Hull, UK

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Finite elements analysis (FEA) is increasingly applied to fossils to infer function and so, aspects of ecology. Reliable assessment of masticatory system functioning and inferences about diet depend upon several things, including; quality of reconstruction of fossil material, correct construction of FE models, use of appropriate model parameters and, importantly, subsequent appropriate interpretation.

Here we assess the consequences for the functioning of FE models simulating biting in a macaque of modelling approximations and applied muscle forces. Previous FEA has shown the model predicts strains that closely replicate measured in vitro strains over the zygoma and infraorbital region. Using a novel combination of strain maps and geometric morphometric analyses of large-scale model deformations under loads we assess the impact of common approximations in model construction, constraints and loading. They show, for the most part, that the approximations are within acceptable limits and, where they are not, their effects are somewhat predictable. As such, they can be taken into account in assessing and comparing general patterns of deformation arising from FEA.

Thus, FEA is a robust and reliable tool for predicting general patterns of deformation of this model during biting. The same is likely to pertain for other primates, including fossils, and so we can have confidence that comparative FEA studies of biting simulations among living and fossil primates may indeed reflect reality. However, a major challenge is to develop better understanding of what differences in masticatory load resistance among species might mean in terms of ecology and feeding behaviour.

The work has been supported by research grants from The Leverhulme Trust (F/00224), BBSRC (BB/E013805; BB/E009204), and by EVAN (MRTN CT-2005-019564). MP was funded by the Fundação para a Ciência e a Tecnologia (Portugal), through the PhD Programme in Computational Biology, Instituto Gulbenkian de Ciência (Portugal).

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