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The Missing Link between Morphemic Assemblies and Behavioral Responses:a Bayesian Information-Theoretical model of lexical processing

By Dr Fermin Moscoso del Prado Martin, Prof Aleksandar Kostic and Dusica Filipovic-Djurdjevic

Abstract

We present the Bayesian Information-Theoretical (BIT) model of lexical processing: A mathematical model illustrating a novel approach to the modelling of language processes. The model shows how a neurophysiological theory of lexical processing relying on Hebbian association and neural assemblies can directly account for a variety of effects previously observed in behavioural experiments. We develop two information-theoretical measures of the distribution of usages of a morpheme or word, and use them to predict responses in three visual lexical decision datasets investigating inflectional morphology and polysemy. Our model offers a neurophysiological basis for the effects of morpho-semantic neighbourhoods. These results demonstrate how distributed patterns of activation naturally result in the arisal of symbolic structures. We conclude by arguing that the modelling framework exemplified here, is a powerful tool for integrating behavioural and neurophysiological results

Topics: Neurolinguistics, Statistical Models, Language, Neural Modelling, Computational Linguistics, Computational Neuroscience, Semantics, Morphology, Machine Learning, Psycholinguistics, Cognitive Psychology, Neural Nets, Artificial Intelligence
Year: 2006
OAI identifier: oai:cogprints.org:4764

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