An influential concept in contemporary computational neuroscience is the reward prediction error hypothesis of phasic dopaminergic function. It maintains that midbrain dopaminergic neurons signal the occurrence of unpredicted reward, which is used in appetitive learning to reinforce existing actions that most often lead to reward. However, the availability of limited afferent sensory processing and the precise timing of dopaminergic signals suggest that they might instead have a central role in identifying which aspects of context and behavioural output are crucial in causing unpredicted events.