Hierarchical Brain-LLM Alignment Reveals Layer-Specific Neural Representations of Second Language Proficiency

Abstract

Second language (L2) comprehension is thought to proceed hierarchically, from basic word recognition to complex discourse-level understanding. However, the neural mechanisms underpinning this hierarchical progression remain poorly understood. Leveraging the hierarchical nature of linguistic representations in large language models (LLMs), we investigated how L2 proficiency modulates layer-wise brain-LLM alignment. Using functional magnetic resonance imaging (fMRI) data collected during discourse listening from 54 participants with varying levels of L2 proficiency, we constructed individualized encoding models to quantify how proficiency shapes the brain-LLM representational correspondence. In high-proficiency individuals, LLM-based models reliably predicted neural responses in a distributed network comprising temporal, frontal, and medial-parietal cortices, while for low-proficiency participants, prediction performance decreased. Notably, alignment in the superior temporal sulcus (STS) showed a robust correlation with L2 proficiency at mid-to-deep LLM layers, suggesting that the STS encodes higher-level linguistic abstractions essential for advanced language comprehension. These findings indicate that L2 proficiency modulates the alignment between LLMs and the brain in a graded, layer-dependent manner, providing insights into hierarchical neural language representations.