SUMMARYFoot pressure distributions during locomotion have causal links with the anatomical and structural configurations of the foot tissues and the mechanics of locomotion. Elephant feet have five toes bound in a flexible pad of fibrous tissue (digital cushion). Does this specialized foot design control peak foot pressures in such giant animals? And how does body size, such as during ontogenetic growth, influence foot pressures? We addressed these questions by studying foot pressure distributions in elephant feet and their correlation with body mass and centre of pressure trajectories, using statistical parametric mapping (SPM), a neuroimaging technology. Our results show a positive correlation between body mass and peak pressures, with the highest pressures dominated by the distal ends of the lateral toes (digits 3, 4 and 5). We also demonstrate that pressure reduction in the elephant digital cushion is a complex interaction of its viscoelastic tissue structure and its centre of pressure trajectories, because there is a tendency to avoid rear ʻheelʼ contact as an elephant grows. Using SPM, we present a complete map of pressure distributions in elephant feet during ontogeny by performing statistical analysis at the pixel level across the entire plantar/palmar surface. We hope that our study will build confidence in the potential clinical and scaling applications of mammalian foot pressures, given our findings in support of a link between regional peak pressures and pathogenesis in elephant feet. Supplementary material available online at

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Finite element analysis (FEA) is a commonly used tool in musculoskeletal biomechanics and vertebrate paleontology. The accuracy and precision of finite element models (FEMs) are reliant on accurate data on bone geometry, muscle forces, boundary conditions and tissue material properties. Simplified modeling assumptions, due to lack of in vivo experimental data on material properties and muscle activation patterns, may introduce analytical errors in analyses where quantitative accuracy is critical for obtaining rigorous results. A subject-specific FEM of a rhesus macaque mandible was constructed, loaded and validated using in vivo data from the same animal. In developing the model, we assessed the impact on model behavior of variation in (i) material properties of the mandibular trabecular bone tissue and teeth; (ii) constraints at the temporomandibular joint and bite point; and (iii) the timing of the muscle activity used to estimate the external forces acting on the model. The best match between the FEA simulation and the in vivo experimental data resulted from modeling the trabecular tissue with an isotropic and homogeneous Young’s modulus and Poisson’s value of 10 GPa and 0.3, respectively; constraining translations along X,Y, Z axes in the chewing (left) side temporomandibular joint, the premolars and the m1; constraining the balancing (right) side temporomandibular joint in the anterior-posterior and superior-inferior axes, and using the muscle force estimated at time of maximum strain magnitude in the lower lateral gauge. The relative strain magnitudes in this model were similar to those recorded in vivo for all strain locations. More detailed analyses of mandibular strain patterns during the power stroke at different times in the chewing cycle are needed.