[2603.29617] Convergent Representations of Linguistic Constructions in Human and Artificial Neural Systems

Quantitative Biology > Neurons and Cognition arXiv:2603.29617 (q-bio) [Submitted on 31 Mar 2026] Title:Convergent Representations of Linguistic Constructions in Human and Artificial Neural Systems Authors:Pegah Ramezani, Thomas Kinfe, Andreas Maier, Achim Schilling, Patrick Krauss View a PDF of the paper titled Convergent Representations of Linguistic Constructions in Human and Artificial Neural Systems, by Pegah Ramezani and 4 other authors View PDF HTML (experimental) Abstract:Understanding how the brain processes linguistic constructions is a central challenge in cognitive neuroscience and linguistics. Recent computational studies show that artificial neural language models spontaneously develop differentiated representations of Argument Structure Constructions (ASCs), generating predictions about when and how construction-level information emerges during processing. The present study tests these predictions in human neural activity using electroencephalography (EEG). Ten native English speakers listened to 200 synthetically generated sentences across four construction types (transitive, ditransitive, caused-motion, resultative) while neural responses were recorded. Analyses using time-frequency methods, feature extraction, and machine learning classification revealed construction-specific neural signatures emerging primarily at sentence-final positions, where argument structure becomes fully disambiguated, and most prominently in the alpha band. Pairwise classification...