Dementia affects over 55 million people worldwide (World Health Organization, 2024) and significantly impacts wellbeing and healthcare systems such as the NHS. Mild Cognitive Impairment (MCI) is often a precursor to dementia and carries a high risk of progression within eight years (Dang et al., 2019). Early detection during this stage could reduce burden and improve patient outcomes.

This PhD aims to digitalise diagnostic tools for individuals with MCI and Alzheimer’s disease by exploring a behavioural recognition memory task. Previous work grounded in Wagner’s (1981) model proposes two distinct priming mechanisms which are self-generated and retrieval-generated priming. Human eye-tracking adaptations of rodent recognition memory tasks, specifically relative recency and object-in-place, provide behavioural evidence for these mechanisms and can dissociate their contributions to recognition memory (Nitka et al., 2020). Building on this framework, my PhD will use these tasks to examine how self- and retrieval-generated priming operate in healthy adults and individuals with Mild Cognitive Impairment and Alzheimer’s disease, with the longer-term aim of developing a sensitive behavioural marker of early cognitive change.

To address this, this PhD will refine these tasks using more visually similar stimuli (e.g., variations of the moon) to better isolate priming effects measured through relative recency and object-in-place performance. The goal is to provide a purer measure of recognition memory and identify which type of priming is selectively impaired in early cognitive decline. This task will therefore be conducted with healthy older adults, people with MCI, and people with Alzheimer’s disease. This PhD will compare performance from this task with widely used cognitive assessments such as the ACE-III and predictive tools such as CANTAB, to evaluate its utility as a diagnostic and prognostic tool.