Computational Models of Retrieval Processes in Sentence Processing. Issue 11 (November 2019)

• Record Type: Journal Article
• Authors: Vasishth, Shravan; Nicenboim, Bruno; Engelmann, Felix; Burchert, Frank
• Is Part Of: Trends in cognitive sciences. Volume 23:Issue 11(2019)
• Page Start: 968
• Page End: 982
• Publication Date: 2019-11
• Subjects: cue-based retrieval -- retrieval interference -- comprehension impairments in aphasia -- individual differences; Cognitive science -- Periodicals; Cognitive neuroscience -- Periodicals; 153.05
• DOI: 10.1016/j.tics.2019.09.003
• Languages: English
• ISSNs: 1364-6613

Abstract

Abstract : Sentence comprehension requires that the comprehender work out who did what to whom. This process has been characterized as retrieval from memory. This review summarizes the quantitative predictions and empirical coverage of the two existing computational models of retrieval and shows how the predictive performance of these two competing models can be tested against a benchmark data-set. We also show how computational modeling can help us better understand sources of variability in both unimpaired and impaired sentence comprehension. Highlights: Sentence comprehension requires that a comprehender work out who did what to whom. This process, known as dependency completion, involves linking together words or phrases that belong together linguistically. Experiments have demonstrated that when the search for a particular word is carried out in memory, retrieval interference is observed when multiple words have features that match the retrieval cues. Recently, two computational models specifying the specific processes supporting dependency completion have been proposed: the activation model and the direct-access model. Both models predict retrieval interference, but they assume that different underlying processes lead to the observed interference effects.