Mechanical Engineering


Visual system vulnerability in dementia: from detection to determinants

A fully funded PhD studentship at the EPSRC Centre for Doctoral Training in Digital Health Technologies

 Visual system vulnerability in dementia: from detection to determinants

Key information

Lead supervisors: Dr Keir Yong and Dr Andre Altmann
Application deadline: 21 July 2024
Project start date: 01 October 2024
Project duration: 4 years
Studentship funding: Home tuition fees (currently £6,035/year) and maintenance stipend (currently £22,237/year) for 4 years


The challenges for healthcare systems are unprecedented, exacerbated by the burdens of infectious and chronic disease, ageing populations, inequalities, fragmented systems and workforce shortages. New technological approaches are needed to harness the potential of routine and novel health data and digital solutions to enable transformational improvement of care pathways and outcomes.

Our doctoral training programme http://www.tech4health.co.uk will address this deficit by creating a new coordinated training curriculum, partnering world-leading academic and NHS organisations and industry, such that graduates can co-create and ideate, design, develop, evaluate and implement evidence-based digital health technologies.

PhD project description

Cortical visual impairments (‘brainsight’, not eyesight loss) are disabling consequences of dementia associated with particular diagnostic and management needs. Such impairments have been reported in the majority of people with Alzheimer’s disease, particularly in posterior cortical atrophy (‘visual-led dementia’) where these symptoms precede loss of memory, language and insight.

People with dementia-related visual impairment are usually seen first by eye health professionals. They are frequently misdiagnosed with eye or psychological conditions, repeatedly change glasses or undergo surgery before determining their visual loss arises from cortical, rather than ocular deficits. Tests of cortical visual function are used rarely except by highly specialised neurology/neuro-ophthalmology diagnostic services. These diagnostic scenarios often delay diagnosis and treatment for years.

Key knowledge gaps and significance:

  • There is a lack of tests to detect brainsight loss and distinguish this from eyesight loss.
  • There is a gap in evidence-based tests to diagnose brainsight loss caused by dementia. There is a gap in tests suitable across eye and dementia clinic settings.
  • The reasons behind why some people with dementia are more susceptible to brainsight loss are largely unknown.

Determining the causes and consequences of visual system vulnerability in dementia has important fundamental and translational implications for understanding variable disease onset and progression.

Project outcomes include promoting equitable access to novel disease-modifying therapies targeting Alzheimer’s disease (the most common atypical form of Alzheimer’s disease is visual-, not memory-led).

Project aims and objectives

Aim 1: Improve detection of visual-led dementia
Objective: Develop a test to detect dementia-related visual impairment in eye and dementia clinics

Aim 2: Evaluate factors associated with cortical visual function in UK Biobank
Objective: Derive a cortical visual factor in UK Biobank and evaluate candidate associated risk factors

Aim 3: Evaluate factors associated with visual system vulnerability in dementia
Objective: Compare genetic variants associated with cortical visual functioning and visual-led dementia

This studentship will incorporate neuropsychological and visual psychophysics, statistical and imaging genetics methodologies across three Projects:

Project 1: Developing and validating a cortical visual test
We have developed a digital test (Graded Incomplete Letter Test [GILT]) to rapidly detect and distinguish cortical visual from ocular losses. The GILT is adapted from standard tests to diagnose cortical visual impairment but is optimised for sensitivity and specificity. You will support validation of the GILT in ageing cohorts (UKB n=60,000) and dementia and eye clinic patients (National Hospital of Neurology and Neurosurgery, Moorfields Eye Hospital). You will relate GILT performance to clinical diagnoses and MRI and evaluate approaches to increase GILT sensitivity to damage to visual cortex.

Project 2: Confirmatory factor analysis
You will derive a cortical visual factor score in UK Biobank using confirmatory factor analysis. This factor will index cortical visual integrity by incorporating visual tests (similar to a ‘language factor’ incorporating tests of vocabulary, comprehension and reading speed) and MRI measures. Analyses will be informed by separate confirmatory factor analysis of existing visual and MRI UCL patient data. You will evaluate relationships between this cortical visual factor score, Alzheimer’s disease risk factors and UK Biobank measures of functional status (e.g. time spent driving, walking pace).

Project 3: Discovery analysis
You will conduct a genetic analysis (known as genome wide association analysis or GWAS) to discover genetic markers (known as SNPs) associated with the Project 2 factor score. You will compare SNP effects with genetic profiles of visual-led dementia using adjusted logistic and linkage disequilibrium score regression. Visual-led dementia groups will include the posterior cortical atrophy sample at UCL and Alzheimer’s disease patients with predominant visual loss participating in data-sharing initiatives.

Person specification

  • Applicants are preferred to have a first-class undergraduate and/or master’s degree (or equivalent) in a numerate discipline, preferably in mathematical, computational, biological, engineering or physical sciences subjects or a related discipline, with an interest in using technology to solve health problems.
  • Excellent organisational, interpersonal and communication skills, along with an interest in interdisciplinary research, are essential.
  • Experience in computer programming is essential.
  • Fluency and clarity in spoken English as well as good written English in accordance with UCL English requirements (TOEFL>92 or IELTS>6.5).


Please note that the available funding supports tuition fees at the Home/UK rate (currently £6,035 per year). Students who are eligible to pay fees at the UK rate are welcome to apply (e.g. UK students or EEA or Swiss nationals who are “settled” or “pre-settled” within the UK in accordance with the EU Settlement Scheme). Please refer to our website for further information about Home tuition fee eligibility.

Applicants whose first language is not English are required to meet UCL's English language entry requirements.

Please refer to this webpage for full eligibility criteria: Mechanical Engineering MPhil/PhD

How to apply

Eligible applicants should submit a formal PhD application via the UCL website. You will need a CV, academic transcript, contact details of at least two academic referees, and a personal statement giving your reasons for applying and an outline of your research interests.

  • Please select: ‘Year of entry: 2024-2025 and ‘Research Degree: Mechanical Engineering’
  • The duration of the PhD is four years
  • The funding for this studentship is the ‘tech4health programme’
  • You do not need to upload a ‘research proposal’
  • Please write ‘Dr Keir Yong’ in the ‘proposed supervisor’ box on the application form

The supervisory team will arrange interviews for short-listed candidates.