Two hemispheres-two networks: A computational model explaining hemispheric asymmetries while reading ambiguous words

Orna Peleg, Larry Manevitz, Hananel Hazan, Zohar Eviatar

Research output: Contribution to journalArticlepeer-review

Abstract

A computational model for reading that takes into account the different processing abilities of the two cerebral hemispheres is presented. This dual hemispheric reading model closely follows the original computational lines due to Kowamoto (J Mem Lang 32:474-516, 1993) but postulates a difference in architecture between the right and left hemispheres. Specifically it is assumed that orthographic, phonological and semantic units are completely connected in the left hemisphere, while there are no direct connections between phonological and orthographic units in the right hemisphere. It is claimed that this architectural difference results in hemisphere asymmetries in resolving lexical ambiguity and more broadly in the processing of written words. Simulation results bear this out. First, we show that the two networks successfully simulate the time course of lexical selection in the two cerebral hemispheres. Further, we were able to see a computational advantage of two separate networks, when information is transferred from the right hemisphere network to the left hemisphere network. Finally, beyond reproducing known empirical data, this dual hemispheric reading model makes novel and surprising predictions that were found to be consistent with new human data.

Original languageEnglish
Pages (from-to)125-147
Number of pages23
JournalAnnals of Mathematics and Artificial Intelligence
Volume59
Issue number1
DOIs
StatePublished - Jun 2010
Externally publishedYes

Keywords

  • Brain hemispheres
  • Corpus collusum
  • Disambiguation of natural language
  • Modeling
  • Neural networks
  • Simulation

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