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Daniel Anderson, George Mason University
The human retina is a thin, light-sensitive tissue at the back of the eye whose role is to convert light into electrochemical signals that get sent to the brain via the optic nerve; for healthy eyes, the result is visual recognition. For our purposes we shall think of the retina as composed of two types of photoreceptors -- rods and cones -- as well as an underlying retinal pigment epithelium (RPE). For humans, as well as primates such as Rhesus Monkeys, the rod and cone spatial distribution along the retina has been measured and differ significantly between these two photoreceptor populations. Also, recent data has shown how the photoreceptors outer segment (OS) length varies along the retina. Data for quantities such as RPE density and the thickness of the retina as a whole also exist. Recent mathematical models have begun to give predictions for the spatial dependence of photoreceptor OS thickness. The goal of this modeling project is to investigate these ideas and develop new models and solutions that may allow the incorporation of additional details such as RPE density and/or retinal thickness into photoreceptor OS length predictions. Opportunities for modeling using ordinary and partial differential equations, asymptotic approximation, and computation are likely part of this project.
