The Computational Development of Reinforcement Learning during Adolescence.

ABSTRACT: Adolescence is a period of life characterised by changes in learning and decision-making. Learning and decision-making do not rely on a unitary system, but instead require the coordination of different cognitive processes that can be mathematically formalised as dissociable computational modules. Here, we aimed to trace the developmental time-course of the computational modules responsible for learning from reward or punishment, and learning from counterfactual feedback. Adolescents and adults carried out a novel reinforcement learning paradigm in which participants learned the association between cues and probabilistic outcomes, where the outcomes differed in valence (reward versus punishment) and feedback was either partial or complete (either the outcome of the chosen option only, or th

SUBMITTER: Palminteri S 

PROVIDER: S-EPMC4920542 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature