Distributional reinforcement learning in prefrontal cortex
Timothy Müller, James L. Butler, Sebastijan Veselič, Bruno Miranda, Joni D. Wallis, Peter Dayan, Timothy E.J. Behrens, Zeb Kurth‐Nelson, Steven W. Kennerley
Abstract
The prefrontal cortex is crucial for learning and decision-making. Classic reinforcement learning (RL) theories center on learning the expectation of potential rewarding outcomes and explain a wealth of neural data in the prefrontal cortex. Distributional RL, on the other hand, learns the full distribution of rewarding outcomes and better explains dopamine responses. In the present study, we show that distributional RL also better explains macaque anterior cingulate cortex neuronal responses, suggesting that it is a common mechanism for reward-guided learning.
Topics & Concepts
Prefrontal cortexNeuroscienceReinforcement learningReinforcementPsychologyMacaqueAnterior cingulate cortexDopamineConsumer neuroscienceCognitive psychologyCognitionComputer scienceArtificial intelligenceSocial psychologyNeural and Behavioral Psychology StudiesNeural dynamics and brain functionNeurotransmitter Receptor Influence on Behavior