An implemented predictive coding model of lexico-semantic processing explains the dynamics of univariate and multivariate activity within the left ventromedial temporal lobe during reading comprehension.

ABSTRACT: During language comprehension, the larger neural response to unexpected versus expected inputs is often taken as evidence for predictive coding-a specific computational architecture and optimization algorithm proposed to approximate probabilistic inference in the brain. However, other predictive processing frameworks can also account for this effect, leaving the unique claims of predictive coding untested. In this study, we used MEG to examine both univariate and multivariate neural activity in response to expected and unexpected inputs during word-by-word reading comprehension. We further simulated this activity using an implemented predictive coding model that infers the meaning of words from their orthographic form. Consistent with previous findings, the univariate analysis showed that,

SUBMITTER: Wang L 

PROVIDER: S-EPMC11894502 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature