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Syntactic structure and artificial grammar learning: The learnability of embedded hierarchical structures

de Vries, Meinou H. and Monaghan, Padraic and Knecht, Stefan and Zwitserlood, Pienie (2008) Syntactic structure and artificial grammar learning: The learnability of embedded hierarchical structures. Cognition, 107 (2). pp. 763-774. ISSN 0010-0277

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Abstract

Embedded hierarchical structures, such as "the rat the cat ate was brown", constitute a core generative property of a natural language theory. Several recent studies have reported learning of hierarchical embeddings in artificial grammar learning (AGL) tasks, and described the functional specificity of Broca's area for processing such structures. In two experiments, we investigated whether alternative strategies can explain the learning success in these studies. We trained participants on hierarchical sequences, and found no evidence for the learning of hierarchical embeddings in test situations identical to those from other studies in the literature. Instead, participants appeared to solve the task by exploiting surface distinctions between legal and illegal sequences, and applying strategies such as counting or repetition detection. We suggest alternative interpretations for the observed activation of Broca's area, in terms of the application of calculation rules or of a differential role of working memory. We claim that the learnability of hierarchical embeddings in AGL tasks remains to be demonstrated. (C) 2007 Elsevier B.V. All rights reserved.

Item Type: Article
Journal or Publication Title: Cognition
Uncontrolled Keywords: artificial grammar learning ; syntax ; context free grammar ; finite-state grammar ; centre embeddings ; hierarchical structure learning ; WORKING-MEMORY ; LANGUAGE ; COMPREHENSION ; FACULTY
Subjects:
Departments: Faculty of Science and Technology > Psychology
ID Code: 52787
Deposited By: ep_importer_pure
Deposited On: 22 Feb 2012 11:38
Refereed?: Yes
Published?: Published
Last Modified: 30 Sep 2013 15:22
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/52787

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