Using Neural Network Models to Model Cerebral Hemispheric Differences in Processing Ambiguous Words

3rd International Workshop on Neural-Symbolic Learning and Reasoning

Orna Peleg ; Zohar Eviatar ; Larry Manevitz ; Hananel Hazan

Others  :  http://CEUR-WS.org/Vol-230/08-peleg.pdf
PID  :  12505

来源: CEUR

【 摘 要 】

Neuropsychological studies have shown that both cerebral hemispheres process orthographic, phonologicaland semantic aspects of written words, albeit 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 Kowamoto's [1993] model to follow our hypothesis. In this paper we present the results of the computationalmodel and show that the results obtained are analogous to the human experiments.