The research group focuses on computational psychiatry and affective decision-making processes. Using behavioural experiments, computational models, and neuroimaging, the group investigates how psychiatric symptoms emerge from disrupted brain computations. The research examines how the brain forms expectations, learns from reward, and regulates motivation, and how individual differences in these processes relate to affective disorders, particularly recurrent depression and bipolar disorder.
By combining longitudinal digital assessments with mechanistic modelling, the group develops quantitative cognitive phenotypes and investigates how these can improve diagnosis, predict illness trajectories, and guide personalised treatment.