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Using imaging spectroscopy to measure individual differences in facial expressivity in human and non-human primates
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Humans have evolved the most expressive faces of all mammals, with facial musculature capable of a wide range of subtle and complex movement (Waller et al., 2020). These facial movements can signal important social information during social interaction with others, such as emotion, intentions, motivation and potential action. However, individuals vary considerably in the extent to which they move their faces (facial expressivity), which results in differential social outcomes (Kavanagh et al., 2024). The phenotypic variation of facial expressivity likely results from interacting factors: facial anatomy, individual response to local environment and health. An interdisciplinary approach that fully integrates the multiple factors that contribute to facial expressivity is necessary to understand the causes and social/health consequences of facial expressivity.
In this PhD project you will use a novel interdisciplinary approach to measure individual differences in the facial anatomy of human and non-human primate faces.Imaging spectroscopy can record tissue oxygen saturation, lipid, protein and water content in facial tissues, thermal imaging can record temperature of the facial tissues, and therefore this multi-modal imaging approach has the potential to be used as a fine-grained indicator of neuromuscular facial muscle composition and activity. All imaging techniques mentioned here are mobile and non-invasive.
We will use multipleimaging techniques from the visible to the infrared to 1) measure individual differences in lipid, protein and oxygenation distribution in human facial soft tissue during social interaction, 2) examine how these differences relate to health and social outcomes and 3) conduct a cross-species comparison with a non-human primate model (Macaca spp: macaques) to better understand the evolutionary selection pressures. The project would suit a candidate with a background in biological/psychological sciences or physical/engineering sciences, with a strong technical component and coding experience. The supervisory team will be cross-discipline in both the social and physical sciences.
Supervisory Team
Anyone interesting in joining the team, contact us!