Meta-analysis of human prediction error for incentives, perception, cognition, and action.

ABSTRACT: Prediction errors (PEs) are a keystone for computational neuroscience. Their association with midbrain neural firing has been confirmed across species and has inspired the construction of artificial intelligence that can outperform humans. However, there is still much to learn. Here, we leverage the wealth of human PE data acquired in the functional neuroimaging setting in service of a deeper understanding, using an MKDA (multi-level kernel-based density) meta-analysis. Studies were identified with Google Scholar, and we included studies with healthy adult participants that reported activation coordinates corresponding to PEs published between 1999-2018. Across 264 PE studies that have focused on reward, punishment, action, cognition, and perception, consistent with domain-general theoreti

SUBMITTER: Corlett PR 

PROVIDER: S-EPMC9117315 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature