Language comprehension models at different levels of explanation. Issue 1 (15th January 2020)

• Record Type: Journal Article
• Authors: Colvin, Michelle; Warren, Tessa
• Is Part Of: Language and linguistics compass. Volume 14:Issue 1(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-01-15
• Subjects: Language and languages -- Periodicals; Linguistics -- Periodicals; Applied linguistics -- Periodicals; Linguistique -- Périodiques; Linguistique appliquée -- Périodiques; Langage et langues -- Périodiques; 400
• DOI: 10.1111/lnc3.12362
• Languages: English
• ISSNs: 1749-818X

Abstract

Abstract: This paper reviews two recent models of language comprehension, the RI‐Val model (Cook & O'Brien, 2014; O'Brien & Cook, 2016b) and the dynamic generative framework (Kuperberg, 2016). Both of these models have been heavily informed by research on the processing of semantic anomalies, but they have arisen in different literatures. The RI‐Val model has roots in the text processing literature and focuses primarily on bottom–up aspects of comprehension; the dynamic generative framework has roots in the event‐related brain potential (ERP)/sentence processing literature and focuses more heavily on top–down aspects of comprehension. Relating these models to each other and considering the findings in the semantic anomaly literature that support each one pushes us to consider the possibility that these models might be describing the comprehension system at different levels of explanation (Marr, 1982). This view has a few important consequences. First, it provides new ways of thinking about, and consequently increases the importance of, the small literature about anomaly detection in fictional contexts. It also opens the door for beginning to speculate about potential mappings between these two models of language comprehension. Our hope is that by bringing together and highlighting potential connections between models from different traditions, we will provoke bigger picture points of view that raise new questions and spur new ideas for research.