Investigating the Impact of Socioeconomic Deprivation on Brain Health: Leveraging AI for Addressing Health Inequalities
Supervisors:
Dr Michele Svanera, School of Psychology & Neuroscience
Dr Frederick Ho , School of Health & Wellbeing
Dr Donald Lyall , School of Health & Wellbeing
Professor Monika Harvey , School of Psychology & Neuroscience
Summary:
Understanding the connection between socioeconomic deprivation and brain health is crucial for addressing social inequalities that negatively impact brain health over time. Despite established correlations between deprivation, intermediate factors like pollution and educational attainment, and poorer brain health, the specific pathway linking these factors remains poorly understood. This doctorate project will first establish this critical link and then explore the possible underlying mechanisms connecting socioeconomic deprivation to brain health.
The student will use the latest advancements in predictive and generative AI to compute the brain age gap (BAG) metric - the difference between an individual's chronological and predicted age - from neuroimaging data. This approach will objectively quantify brain health and, through explainable AI, identify which brain areas/other anatomical factors most strongly influence the ageing process.
By leveraging data from the UK Biobank and correlating it with multiple detailed deprivation indices, we seek to identify deprivation factors contributing to brain ageing. Understanding these mechanistic routes will provide new insights into how deprivation impacts brain health, potentially guiding public health interventions to mitigate these effects. The ideal candidate will have prior experience in Machine Learning or a related field.