Neuronal reward mechanisms

We investigate neuronal reward and economic decision signals in behavioural tasks with designs from animal learning and economic decision theories, supplemented by selected, closely related human neuroimaging experiments. We study the main components of the brain's reward system, including dopamine neurons (reward prediction error), orbitofrontal cortex (economic decision variables), striatum (so far insufficiently characterised reward signals) and amygdala (short- and long-term rewards). We search for reward and decision signals that provide explanations and hardware implementations for the constructs of reward and economic theories. We need to know these fundamental neuronal signals before focussing on cellular and molecular mechanisms, which differs from work on sensory and motor systems whose signals are better characterised. We state three aims: Aim 1: We characterise neuronal processing of skewness-risk, arguably the most frequent risk form. Aim 2: We identify neuronal signals for utility and test formal axioms for utility maximisation, which is supposedly the goal of 'rational' agents. Utility is THE basic economic decision variable that explains most economic choices. Aim 3: We assess neuronal representations of preferences, and bridge the gap between biologically necessary rewards and tradable economic goods, by testing basic assumptions of revealed preference theory.