Abstract

Rewards induce learning (positive reinforcement), approach behaviour, economic decisions and positive emotions (pleasure, desire). We investigate basic neuronal reward signals during learning and decision-making, using behavioural and neurophysiological methods.

The phasic dopamine reward prediction error signal is composed of two components, resembling two-component responses in main sensory neurons. The early dopamine response component detects events indiscriminately and is influenced by physical impact, novelty, reward generalisation and reward context. The second component codes reward value. Although the first component detects punishers by their physical impact, none of the components shows an activation that reflects the aversive nature of punishers.

Our behavioural studies reveal that monkeys are risk seeking with small rewards and risk neutral and then risk avoiders with larger rewards. The animals’ choices are meaningful in satisfying first, second and third order stochastic dominance, which defines rational choices governed by value, symmetric (variance) risk and skewness risk, respectively. The forms of the behavioural utility function allow us to assess the relationship of dopamine prediction error responses to economic utility. Indeed, the dopamine responses satisfy first- and second-order stochastic dominance and code utility. These data unite concepts from animal learning theory and economic decision theory at the level of single reward neurons.