Neural mechanisms of rapid sensitivity to syntactic anomaly

Frontiers in Psychology

Phillip M. Gilley¹  Albert E. Kim¹ 

[1] University of Colorado;

关键词: sentence comprehension;    prediction;    syntactic;    P1;    N170;    posterior cingulate;   

DOI  :  10.3389/fpsyg.2013.00045

来源: DOAJ

【 摘 要 】

Recent psycholinguistic models hypothesize that anticipatory processing can speed the response to linguistic input during language comprehension by pre-activating representations necessary for word recognition. We investigated the neurocognitive mechanisms of anticipatory processing by recording event-related brain responses (ERPs) to syntactically anomalous (The thief was caught by for police) and well-formed (e.g., The thief was caught by the police) sentences.One group of participants saw anomalies elicited by the same word in every instance (e.g., for; low-variability stimuli), providing high affordances for predictions about the word-form appearing in the critical position. A second group saw anomalies elicited by seven different prepositions (at, of, on, for, from, over, with; high-variability stimuli) across the study, creating a more difficult prediction task. Syntactic category anomalies enhanced the occipital-temporal N170 component of the ERP, indicating rapid sensitivity—within 200 ms of word onset—to syntactic anomaly.For low-variability but not the high-variability stimuli, syntactic anomaly also enhanced the earlier occipital-temporal P1 component, around 130 ms after word-onset, indicating that affordances for prediction engendered earlier sensitivity to syntactic anomaly. Independent components analysis revealed three sources within the ERP signal whose functional dynamics were consistent with predictive processing and early responses to syntactic anomaly. Distributed neural source modeling (sLORETA) of these early-active sources produced a candidate network for early responses to words during reading in the right posterior-occipital, left occipital-temporal, and medial parietal cortex.

【 授权许可】

Unknown