Characterising the neurocomputational basis of motivated behaviour in anhedonic depression

Depression is a highly prevalent and debilitating psychiatric disorder. Reduced motivation for pleasurable activities, or anhedonia, is a core depressive symptom. Motivational states are driven by environmental and internal reinforcers with their own reward values, which are perturbed in patients with anhedonic depression. Although preclinical research implicates the dopamine system in modulating motivation/anhedonia, translation of these findings to humans remains limited by traditional neuroimaging and behavioural measures. This project will extend my prior work in developing ultra-high-field MRI sequences and novel computational methods to not only measure but also directly modulate neural activity in dopaminergic circuits that underlies motivation/anhedonia in patients with anhedonic depression. In doing so, I will generate a comprehensive cognitive-computational framework of motivated action in anhedonia, and for the first time, probe the causal link between dopamine circuit function and motivation for distinct reinforcers, via three primary aims: 1) Optimise computational methods to measure cognitive processes underlying anhedonia. 2) Leverage ultra-high-field 7T-MRI to generate precise measurements of dopaminergic circuit function during motivated behaviour. 3) Develop tools to modulate neural activity in order to determine the causal impact of dopaminergic activation on motivation/anhedonia in individuals with and without depression, which promises to identify novel therapeutic targets for depression.