Tactile feedback from the foot sole is crucial for control of balance and during gait. Mechanoreceptors, responsible for translating local strain patterns into neural activity, are embedded in a mechanical environment that is unique across the body: the foot sole experiences the highest loads anywhere on the body and as a result exhibits specific mechanical properties, such as increased stiffness. However, how the complex mechanical environment interacts with mechanoreceptors to support high neural responsiveness across a wide dynamic range is currently not well understood.
This project combines mechanical measurements, histology, and computational modelling and analysis to investigate how mechanical loading of the foot sole acts on the tactile receptors embedded within the skin of the foot sole. Specifically, the student will investigate how large force impacts on the heel and metatarsal region of the foot sole propagate through the different skin layers to result in localized strain patterns at the level of mechanoreceptors and ultimately determine neural response patterns. Outcomes will inform the design of assistive devices, be useful for rehabilitation and prevention, and have implications for designing better sensors in soft robotics.
The project consists of three main objectives, whose outcomes will inform each other.
1) Quantification of large-scale normal and shear force patterns across the foot sole during gait. This part of the project aims to map the shear patterns on the plantar surface and large-scale deformation of the load-bearing areas of the foot during walking and other activities. The student will adapt an existing setup that allows for precise optical under-foot measurements of shear strain on the foot sole and extend it for stereo measurements to allow a three-dimensional reconstruction of the foot sole.
2) Measurement of sub-surface skin strains at the level of mechanoreceptors. Having determined the typical normal and shear forces acting on the foot sole, we will investigate how these forces cause local deformations within the different skin layers across the foot sole. The student will use optical coherence tomography (OCT) to image different skin layers in vivo and non-invasively, as the foot sole is put under load.
3) Measurement of morphology and tactile sensory innervation of the foot sole in order to link mechanics with neural response properties. The final part of the project will link local sub-surface skin strains with the locations of mechanoreceptors embedded within the foot sole. The student will make use of cadaveric tissue from the foot sole to undertake dynamic mechanical testing to determine the functional behaviour of the tissues and, using immunohistochemistry3, reconstruct the position of Merkel cell clusters and Meissner corpuscles with respect to morphological features of the skin layers.
The student will have training in all equipment and be assigned a lab-buddy in each research laboratory. The project combines mechanical engineering and neuroscience and the student will be engaged in weekly lab meetings and have regular opportunities to discuss their work and present updates to the wider group. Both supervisors and student will be based in the Pam Liversidge Building. The student will be encouraged to engage in public and patient involvement events. Other career development opportunities will be shaped by the student, including opportunities to be involved with teaching, engage with clinicians and industry, and develop translational professional skills.
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Please see this link for information on how to apply: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying. Please include the name of the first supervisor and the title of the PhD project within your application. Please state Division of Neuroscience as the division of your project, regardless of where your supervisor sits.
Interviews will be held late November/early December. Students must be able to start in February 2024.
Applications are open to home students only. We would expect applicants to have an excellent undergraduate degree in a relevant discipline. We would also expect applicants to have completed or be undertaking a relevant master’s degree to a similar very high standard (or have equivalent research experience).
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