Temporal neural dynamics of understanding communicative intentions from speech prosody

Abstract

Understanding the correct intention of a speaker is critical for social interaction. Speech prosody is an important source for understanding speakers' intentions during verbal communication. However, the neural dynamics by which the human brain translates the prosodic cues into a mental representation of communicative intentions in real time remains unclear. Here, we recorded EEG (electroencephalograph) while participants listened to dialogues. The prosodic features of the critical words at the end of sentences were manipulated to signal either suggestion, warning, or neutral intentions. The results showed that suggestion and warning intentions evoked enhanced late positive event-related potentials (ERPs) compared to the neutral condition. Linear mixed-effects model (LMEM) regression and representational similarity analysis (RSA) analyses revealed that these ERP effects were distinctively correlated with prosodic acoustic analysis, emotional valence evaluation, and intention interpretation in different time windows; The onset latency significantly increased as the processing level of abstractness and communicative intentionality increased. Neural representations of intention and emotional information emerged and parallelly persisted over a long time window, guiding the correct identification of communicative intention. These results provide new insights into understanding the structural components of intention processing and their temporal neural dynamics underlying communicative intention comprehension from speech prosody in online social interactions.