Pronoun resolution via reinstatement of referent-related activity in the delta band

Abstract

Human language offers a variety of ways to create meaning, one of which is referring to entities, objects, or events in the world. One such meaning maker is understanding to whom or to what a pronoun in a discourse refers to. To understand a pronoun, the brain must access matching entities or concepts that have been encoded in memory from previous linguistic context. Models of language processing propose that internally stored linguistic concepts, accessed via exogenous cues such as phonological input of a word, are represented as (a)synchronous activities across a population of neurons active at specific frequency bands. Converging evidence suggests that delta band activity (1-3Hz) is involved in temporal and representational integration during sentence processing. Moreover, recent advances in the neurobiology of memory suggest that recollection engages reinstatement of neural dynamics that occurred during memory encoding. Integrating from these two research lines, we here predicted that neural dynamic patterns, especially in delta frequency range, underlying referential meaning representation would be reinstated during pronoun resolution. By leveraging neural decoding techniques (i.e., representation similarity analysis) on a magnetoencephalogram (MEG) dataset acquired during a naturalistic story-listening task, we provide evidence that delta-band activity underlies referential meaning representation. Our findings suggest that, during spoken language comprehension, endogenous linguistic representations such as referential concepts may be retrieved and represented via reinstatement of dynamic neural patterns.

Shared neural computations for syntactic and morphological structures: evidence from Mandarin Chinese

“…Topographical similarity analysis (i.e., representational similarity analysis, spatial similarity analysis) is an analysis for comparing the topographical distribution of ERP responses that is free from bias in electrode selection (Tian & Huber, 2008; Murray, Brunet & Michel, 2008; Tian, Poeppel & Huber, 2010; Wang, Zhu & Tian, 2019). Quantifying topographical similarity with this method has been used to hallmark similarity in the underlying neural processes in many language comprehension studies (Yang, Cai & Tian, 2020; Wang et al, 2020; Wang & Kuperberg, 2023; Hubbard & Federmeier, 2021; Wei et al, 2023; Zhao et al, 2023; Huang, Feng & Qu, 2023; Ding, ten Oever & Martin, 2023).…”

A brain-rhythm based computational framework for semantic context and acoustic signal integration in speech processing

“…The delta rhythm, being the slowest rhythm observed in the auditory cortex during speech processing, may be a plausible carrier of contextual top-down predictions [52]. Studies suggest that the functions of the delta rhythm include tracking of prosody [53][54][55][56][57], chunking of words and phrases [5,58], error resolution [59,60], multiscale integration [51,61], top-down modulation of speech processing [46,62,63], as well as top-down prediction of temporal information [64,65]. However, existing models primarily employ the delta rhythm as a mechanism for chunking words and phrases [66,67], overlooking its potential role in top-down contextual influence.…”

“…As a key conceptual proposition in this paper, we suggest that a top-down predictive information flow modulated by delta rhythm can mitigate the deterioration of speech signals and improve processing reliability in acoustically challenging environments [45–50]. More specifically, we hypothesize that the information from multiple syllables is predictively combined into a semantic contextual representation (e.g., a word or a prosodic phrase) via a process indelibly intertwined with the delta rhythm [51]. Nevertheless, the computational mechanisms governing the formation of such predictive representations and how this process distinctly contributes to speech processing in the brain remain open questions.…”