This research program leverages large-scale data from the UK Biobank to investigate how mental illness emerges from the interaction of brain biology, environmental adversity, and genetic risk across the lifespan. Using multimodal data from over 500,000 individuals, including neuroimaging, mental health, lifestyle, and genetic information, we aim to identify population-level mechanisms of vulnerability and resilience.
This project investigates the role of the ventral tegmental area (VTA), a key hub in the brain's reward system, in depression. Using large-scale neuroimaging data, we examine how structural variation in the VTA relates to depressive symptoms and diagnosis, with a particular focus on imaging markers sensitive to neuroinflammation.
By focusing on a core dopaminergic region and its white matter connections, implicated in motivation, reward processing, and anhedonia, this work aims to clarify how disruptions in reward circuitry contribute to depression at a population level.
This project establishes an up-to-date roadmap for neuroimaging research in mental health using the UK Biobank dataset. As the UK Biobank continues to expand with repeated imaging and longitudinal mental health assessments, the increasing complexity of the dataset presents both opportunities and challenges for large-scale analyses.
Using multimodal imaging-derived phenotypes (IDPs) and a broad range of mental health phenotypes (MHPs), this project systematically quantifies associations across thousands of brain–behaviour pairs. We compute and validate effect sizes for cross-sectional relationships, as well as repeated-measures correlations to capture within-individual associations across time.
By creating a comprehensive, data-driven reference framework of brain–mental health associations, this work provides a foundation for future hypothesis-driven studies, longitudinal modelling, and biomarker discovery in population mental health.