Using Neural Network Models to Model Cerebral Hemispheric Differences in Processing Ambiguous Words
نویسندگان
چکیده
Neuropsychological studies have shown that both cerebral hemispheres process orthographic, phono-logical and semantic aspects of written words, al-beit in different ways. The Left Hemisphere (LH) is more influenced by the phonological aspect of written words whereas lexical processing in the Right Hemisphere (RH) is more sensitive to visual form. We explain this phenomenon by postulating that in the Left Hemisphere (LH) orthography, phonology and semantics are interconnected while in the Right Hemisphere (RH), phonology is not connected directly to orthography and hence its influence must be mitigated by semantical processing. We test this hypothesis by complementary human psychophysical experiments and by dual (one RH and one LH) computational neural network model architecturally modified from Kowa-moto's [1993] model to follow our hypothesis. In this paper we present the results of the computational model and show that the results obtained are analogous to the human experiments.
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