About the Project
Professor Jie Sui (University of Aberdeen)
Dr Dewei Yi (University of Aberdeen)
The ageing process is often accompanied with cognitive decline. Despite considerable work in cognitive ageing, there are fewer studies that link work of cognitive ageing to changes in social functions as people age (is cognitive capacity affected by social factors, e.g., understanding other people’s perspective or self-perception?), even though this enables the build-up of a more holistic understanding of healthy ageing . Recent research has shown that self-reference facilitates cognitive performance across the lifespan, and it links to specific neural circuits. This raises the issue of whether self-reference can be used to remediate cognitive decline, a significant challenge in healthy ageing.
To address this challenge it is essential to understand whether self-reference acts as a buffer against the deterioration of cognitive decline in older people, whether performance boosted by self-reference is maintained in older people by the same processes as found in young people, or whether there is recruitment of additional, compensatory processes. Neuropsychological and clinical examinations have revealed different levels of cognitive decline, e.g., reductions in memory, executive functions, and processing speed. In this project, we will focus on the first of these using behavioural and Electroencephalography (EEG) techniques: discover the rules of self-reference in bolstering age-related memory.
Recent methodological advances that we have developed now provide objective measures of self-processing that are uncontaminated by effects of familiarity and generate large biases in behaviour and also associated brain activity . The prospective student will use the new experimental procedures in combination with cutting-edge analysis technologies including time-frequency analysis and AI approaches  for a dataset with various memory tasks and multiple scales (behavioural, EEG, and self-reported measures), (i) testing if enhanced memory in healthy older adults stems from ultra-fast neural responses to self-related stimuli, which feed-back to influence perception and binding functions in memory, or whether there are stronger top-down processes that help to overcome any reduction in fast, early responses; and (ii) training offline EEG data based on these neural circuits for driving self-referential memory, adjusted by sex, age and environmental factors, and then using this classifier to decode real-time EEG data for prediction. The latter will open up the possibility of incorporating AI technology and new sensitive measures of self-processing into healthy ageing practice.
The project is inherently interdisciplinary and involves strong integration between behavioural neuroscience, computing science, and experimental psychology. The student will join a well-funded group: Sui (expert in social cognition) and Yi (expert in AI-based applications). The student will be supported throughout the PhD by the excellent collaborative team of researchers in the schools of Psychology and Natural & Computing Sciences at the University of Aberdeen. The project includes a clear opportunity for the student to flourish within the unique strengths of our interdisciplinary AI and healthy ageing environment.
Please send your completed EASTBIO application form, along with academic transcripts to Alison McLeod at [Email Address Removed]. Two references should be provided by the deadline using the EASTBIO reference form. Please advise your referees to return the reference form to [Email Address Removed].
Candidates should have (or expect to achieve) a minimum of a 2:1 UK Honours degree, or the equivalent qualifications gained outside the UK, in a relevant subject.
 Sui, J., et al. (2015). Trends in Cogn Sci, 19, 719-728.
 Yi, D., et al. (2019). Transp Res Part C: Emerg Technol, 105, 241-261.
Based on your current searches we recommend the following search filters.
Based on your current search criteria we thought you might be interested in these.