Computational and neural mechanisms for the effect of dopamine on effort and reward learning

The capacity to motivate oneself or be motivated is an important determinant of quality of life and optimal decision-making. Impairments in this are associated with many neuropsychiatric conditions. Fundamental to this process are the ability to learn about rewards and the effort required to achieve them. It has long been known that dopaminergic prediction error signals and reward learning are causally linked (Steinberg et al., 2013). Recent work has also identified parallel encoding of effort and reward prediction errors within distinct brain regions, with effort prediction errors expressed in dorsomedial prefrontal cortex and reward prediction errors in ventral striatum. We will investigate the effects of dopamine on this process in a between-subject, double-blind, placebo-controlled study of N=60, healthy male participants (30 placebo, 30 L-DOPA). Participants will undergo an fMRI protocol while completing an effort learning task (similar to that reported in Hauser et al., 2017). Participants will also report their beliefs about necessary effort required and likely rewards during the task, and complete self-reported questionnaires of apathy and depression. Analysis will include computational modelling of effort and reward learning and the impact of beliefs, fMRI ROI analysis and dynamic causal modelling. Regression analyses will be used to assess the relationship between behavioural and neural parameters and reports of mood and motivation in the subclinical range.

This study forms the foundation of my PhD project which will aim to expand our understanding of the psychopharmacological, behavioural and neural basis of effort and reward learning and their relationship to apathy and mental health.