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LEAD SUPERVISOR:  Prof Hannah Smithson, Department of Experimental Psychology

Co-supervisor: Prof Martin Booth, Department of Engineering Science

Commercial partner: Imagine Eyes, Orsay, France

 

Background: The retina has long been recognised as a window to the brain and vasculature. In fact, neurological diseases have been shown to have detectable correlates in the eye. Consequently, retinal imaging techniques have the potential to provide a low cost readily accessible alternative to technologies such as (f)MRI. However, current clinical retinal imaging technology cannot image individual cells, and so different diseases manifest in gross anatomical changes that lack specificity. Our overarching goal – funded through the EPSRC Transformative Healthcare Technologies theme – is to develop a non-invasive optical instrument, capable of imaging and testing the function of individual retinal cells, for sensitive and specific detection of these diseases, for use in a routine eye exam. A key challenge when imaging the retina at such exquisite detail is the motion of the living human eye due to so-called fixational eye movements (FEMs), which can blur the retinal image. The dynamic properties of these FEMs are linked to a host of cognitive functions and are adversely affected in neurological disease. Consequently they have the potential to be used in diagnosis of such diseases.

Specific Aims: The proposed DPhil is to measure and correct these eye movements, to enable robust imaging in clinical populations. The solution will require innovation in optical engineering, data processing, and modelling system-level biological processes. The aims for the DPhil student are:

(i) Create a representative data set of FEMs in target patient groups (Q4 2022 – Q1 2023): The student will use a state-of-the-art adaptive optics scanning laser ophthalmoscope to record eye movements in patient groups such as those with Parkinson’s disease. Access to such patients will be provided by our existing collaboration with the NIHR Oxford Health Biomedical Research Centre. Comparative data will be collected in patient groups with no underlying neurological disease.

(ii) Develop predictive model of FEMs (Q2 – Q4 2023, Q1 – Q4 2024): The student will use FEM data, machine learning, AI and control theory to develop a model of eye movements in different patient groups to generate predictive models of movement to improve AO system performance.

(iii) Develop hardware and software solutions for improved image registration (Q1 – Q3 2025): The student will test and demonstrate the improvement in retinal image quality when using a predictive model of FEMs.

It is anticipated that the above aims will overlap somewhat.

Relevance to MRC Remit: The work carried out provides training in the MRC priority skills of quantitative, interdisciplinary and whole organ/organism research, and aligns with the industrial strategy priority topics of translational development and precision healthcare diagnostics.

Collaboration Benefit: The interdisciplinary partnership between the Departments of Experimental Psychology and Engineering Science, and Imagine Eyes will allow for two-way knowledge transfer between academia and industry: cutting edge knowledge of FEMs will be transferred to industry and knowledge of the commercialisation process of clinical instrumentation will be transferred to academia. This knowledge transfer will be facilitated by the student spending at least three months at Imagine Eyes spread across each of the aims.

 

Apply using course: DPhil in Experimental Psychology

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