The structure and statistics of language jointly shape cross-frequency neural dynamics during spoken language comprehension.

ABSTRACT: Humans excel at extracting structurally-determined meaning from speech despite inherent physical variability. This study explores the brain's ability to predict and understand spoken language robustly. It investigates the relationship between structural and statistical language knowledge in brain dynamics, focusing on phase and amplitude modulation. Using syntactic features from constituent hierarchies and surface statistics from a transformer model as predictors of forward encoding models, we reconstructed cross-frequency neural dynamics from MEG data during audiobook listening. Our findings challenge a strict separation of linguistic structure and statistics in the brain, with both aiding neural signal reconstruction. Syntactic features have a more temporally spread impact, and both word

SUBMITTER: Weissbart H 

PROVIDER: S-EPMC11471778 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature