Abstract

What are the genetic and neural components that support adaptive learning from positive and negative outcomes? Here, we show with genetic analyses that three independent dopaminergic mechanisms contribute to reward and avoidance learning in humans. A polymorphism in the DARPP-32 gene, associated with striatal dopamine function, predicted relatively better probabilistic reward learning. Conversely, the C957T polymorphism of the DRD2 gene, associated with striatal D2 receptor function, predicted the degree to which participants learned to avoid choices that had been probabilistically associated with negative outcomes. The Val/Met polymorphism of the COMT gene, associated with prefrontal cortical dopamine function, predicted participants' ability to rapidly adapt behavior on a trial-to-trial basis. These findings support a neurocomputational dissociation between striatal and prefrontal dopaminergic mechanisms in reinforcement learning. Computational maximum likelihood analyses reveal independent gene effects on three reinforcement learning parameters that can explain the observed dissociations.