Exploring Parallel Syntactic Processing in Reading: Insights from ERP Studies
Aaron Vandendaele1 (firstname.lastname@example.org), Sofia E. Ortega2, Philip J. Holcomb2, Katherine Midgley2, Jonathan Grainger3; 1Ghent University, 2San Diego State University, 3Aix-Marseille University
To what extent can skilled readers extract higher-order lexical information from multiple words in parallel? The answer to this question has remained controversial with regards to how our brain deals with processing incoming visual information. On the one hand, both eye-tracking and behavioral studies consistently found an effect of parafoveal stimuli on the processing of the fixated foveal stimulus. On the other, effects of higher-order lexical information such as syntax, semantics and grammar have remained elusive. In this project, I will present data from two experiments which used event-related potential (ERP) recordings to investigate the timeframe of how higher-order lexical information impacts ongoing word and sentence recognition. In the first experiment, we used the lexical flanker paradigm in which participants had to classify foveal target words as either being a noun or an adjective. Targets were flanked by either syntactically congruent or incongruent words (e.g.; noun noun noun vs. adjective noun adjective), or syntactically compatible or incompatible words (e.g., adjective noun verb vs. verb noun adjective). The second experiment employed the same stimuli as the latter condition, with participants now tasked to judge the sentence grammaticality instead. Results showed a significantly reduced amplitude in the N400 component (thought to reflect the mapping of word identities to lexical representations) for the syntactic compatible condition and for the sentence grammaticality judgements. These indicate that our reading system can extract and process syntactic information from multiple words in a short timeframe, and that syntactic units are integrated as a single (i.e., sentence) unit.
Topic Area: LANGUAGE: Syntax
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April 13–16 | 2024