The functional form of value normalization in human reinforcement learning.

ABSTRACT: Reinforcement learning research in humans and other species indicates that rewards are represented in a context-dependent manner. More specifically, reward representations seem to be normalized as a function of the value of the alternative options. The dominant view postulates that value context-dependence is achieved via a divisive normalization rule, inspired by perceptual decision-making research. However, behavioral and neural evidence points to another plausible mechanism: range normalization. Critically, previous experimental designs were ill-suited to disentangle the divisive and the range normalization accounts, which generate similar behavioral predictions in many circumstances. To address this question, we designed a new learning task where we manipulated, across learning context

SUBMITTER: Bavard S 

PROVIDER: S-EPMC10393293 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature