Scientific basis
Psychosis is increasingly understood as a neurodevelopmental disorder, despite its typical onset in late adolescence or early adulthood. While research into its mechanisms traditionally focuses on individuals after the onset of clinical symptoms, studying developmental cohorts can reveal early risk factors and brain-based pathways that shape vulnerability to the disorder long before illness becomes apparent. Psychotic-like experiences (PLEs) – subclinical phenomena such as perceptual anomalies or unusual beliefs – are a common early marker of risk. While elevated PLEs are associated with later psychosis, they also predict a range of other mental health outcomes. This raises a critical question: why do some young people with high PLEs go on to develop psychosis, while others show a more general or benign trajectory? The neurobiological and neurocognitive mechanisms shaping these divergent outcomes remain poorly understood.
Aims
This PhD project will investigate how neurodevelopmental risk factors and brain maturation patterns contribute to different outcomes following elevated PLEs. Using multiple large-scale longitudinal neuroimaging datasets, the project will examine whether changes in brain structural and functional connectivity explain why some young people with high PLEs go on to develop psychosis, while others show transdiagnostic symptoms. It will also explore how these changes relate to neurocognitive features such as attention, executive function, and social processing.
This project offers an exciting opportunity to uncover mechanisms that distinguish specific psychosis risk from broader psychiatric vulnerability, informing early identification and prevention strategies.
Skills
The student will gain advanced skills in longitudinal neuroimaging analysis, statistical modelling, network neuroscience, programming, open-science reporting, and develop an in-depth understanding of the developmental origins of psychosis.
Specific objectives
– Year 1 – modelling outcomes: 1) identify subgroups of young people with elevated PLEs who follow different outcome trajectories; 2) characterise cognitive and environmental profiles of these subgroups.
– Year 2 – understanding risk: Investigate whether specific constellations of cognitive, environmental, and psychosocial risk factors predict trajectory membership using multivariate modelling.
– Year 3 – understanding mechanisms: Examine whether neurocognitive or brain-based mechanisms mediate the relationship between early risk and later outcomes.
Rotation
Initial comparative analysis of behavioural and cognitive profiles linked to different outcomes following elevated PLEs. The rotation will deliver a reproducible modelling pipeline and a conference-ready poster, laying the groundwork for the deeper Year 1 analyses.