Model-free and model-based learning processes in the updating of explicit and implicit evaluations.

ABSTRACT: Evaluating stimuli along a good-bad dimension is a fundamental computation performed by the human mind. In recent decades, research has documented dissociations and associations between explicit (i.e., self-reported) and implicit (i.e., indirectly measured) forms of evaluations. However, it is unclear whether such dissociations arise from relatively more superficial differences in measurement techniques or from deeper differences in the processes by which explicit and implicit evaluations are acquired and represented. The present project (total N = 2,354) relies on the computationally well-specified distinction between model-based and model-free reinforcement learning to investigate the unique and shared aspects of explicit and implicit evaluations. Study 1 used a revaluation proced

SUBMITTER: Kurdi B 

PROVIDER: S-EPMC6442571 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature