The Temporal Dynamics of the Labeling Algorithm During Natural Language Comprehension: Neural Evidence for Phrase Grammatical Type Generation

Abstract Language, as a uniquely human faculty, combines words into hierarchical phrases with diverse syntactic-semantic relations (e.g., subject–predicate and modifier–head phrases). These phrase types are theoretically generated through the labeling algorithm at the syntax-semantics interface. Nevertheless, previous research has focused predominantly on the syntactic system, whereas the neural basis and temporal dynamics of labeling remain poorly understood. To address this gap, we developed the Head-Anchored Labeling Manipulation (HALM) approach. This method manipulates labeling by embedding the same Mandarin noun–verb dual-category words as heads in tightly controlled modifier–head constructions, where the head alone determines the phrase’s grammatical type. The representational similarity analysis (RSA) of EEG data revealed that labeling representations emerged during both the early and middle stages: 192–227 ms, 290–318 ms, 330–360 ms, and 385–416 ms following the dual-category word. Labeling emerged as early as ∼200 ms, concurrent with syntactic Merge, and continued into the N400 window. These results demonstrate that labeling dynamically links syntax to conceptual–intentional system and generates phrase types by determining the constituent head. Its early engagement challenges syntax-first models and supports parallel interactive accounts. Moreover, combinability representations (520–596 ms and 604–632 ms), together with a late ERP negativity (420–700 ms) elicited by the dual-category word in the baseline condition, reflect increased difficulty in reconciling semantic associations with atypical syntactic configurations. Together, these findings provide clear electrophysiological evidence for the temporal dynamics of labeling and elucidate the processes at the syntax-semantics interface.