A Computational Cognitive Model of Syntactic Priming

• Published in: Cognitive science 2011-05, Vol.35 (4), p.587-637
• Main Authors: Reitter, David, Keller, Frank, Moore, Johanna D.
• Format: Article
• Language: English
• Subjects: ACT‐R; Adaptation; Algorithms; Association Learning; Biological and medical sciences; Categorial grammar; Choice Behavior; Cognition; Cognition & reasoning; Cognitive architectures; Computer Simulation; Concept Formation; Decision Making; Effects; Fundamental and applied biological sciences. Psychology; Humans; Incrementality; Language; Learning; Mental Recall; Miscellaneous; Models, Theoretical; Neural Networks (Computer); Psycholinguistics; Psychology. Psychoanalysis. Psychiatry; Psychology. Psychophysiology; Semantics; Simulation; Syntactic priming; Verbal Behavior; Verbal Learning
• ISSN: 0364-0213; 1551-6709
• DOI: 10.1111/j.1551-6709.2010.01165.x

The psycholinguistic literature has identified two syntactic adaptation effects in language production: rapidly decaying short‐term priming and long‐lasting adaptation. To explain both effects, we present an ACT‐R model of syntactic priming based on a wide‐coverage, lexicalized syntactic theory that explains priming as facilitation of lexical access. In this model, two well‐established ACT‐R mechanisms, base‐level learning and spreading activation, account for long‐term adaptation and short‐term priming, respectively. Our model simulates incremental language production and in a series of modeling studies, we show that it accounts for (a) the inverse frequency interaction; (b) the absence of a decay in long‐term priming; and (c) the cumulativity of long‐term adaptation. The model also explains the lexical boost effect and the fact that it only applies to short‐term priming. We also present corpus data that verify a prediction of the model, that is, that the lexical boost affects all lexical material, rather than just heads.