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Unifying syntactic theory and sentence processing difficulty through a connectionist minimalist parser

Gerth, S. and beim Graben, P. (2009) Unifying syntactic theory and sentence processing difficulty through a connectionist minimalist parser. Cognitive Neurodynamics, 3 (4). pp. 297-316. ISSN 1871-4080

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To link to this item DOI: 10.1007/s11571-009-9093-1


Syntactic theory provides a rich array of representational assumptions about linguistic knowledge and processes. Such detailed and independently motivated constraints on grammatical knowledge ought to play a role in sentence comprehension. However most grammar-based explanations of processing difficulty in the literature have attempted to use grammatical representations and processes per se to explain processing difficulty. They did not take into account that the description of higher cognition in mind and brain encompasses two levels: on the one hand, at the macrolevel, symbolic computation is performed, and on the other hand, at the microlevel, computation is achieved through processes within a dynamical system. One critical question is therefore how linguistic theory and dynamical systems can be unified to provide an explanation for processing effects. Here, we present such a unification for a particular account to syntactic theory: namely a parser for Stabler's Minimalist Grammars, in the framework of Smolensky's Integrated Connectionist/Symbolic architectures. In simulations we demonstrate that the connectionist minimalist parser produces predictions which mirror global empirical findings from psycholinguistic research.

Item Type:Article
Divisions:Life Sciences > School of Psychology and Clinical Language Sciences
ID Code:14051
Uncontrolled Keywords:Computational psycholinguistics, Human sentence processing, Minimalist, Grammars, Integrated Connectionist/Symbolic architecture, Fractal, tensor product representation, BRAIN POTENTIALS, VERB INFORMATION, DYNAMICAL-SYSTEM, NEURAL-NETWORKS, EYE-MOVEMENTS, LANGUAGE, BINDING, MODEL, REPRESENTATION, DEPENDENCIES

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