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Keywords:

  • Neural networks;
  • Perception;
  • Reading;
  • Visual word recognition;
  • Hemispheric lateralization

Abstract

Through computational modeling, here we examine whether visual and task characteristics of writing systems alone can account for lateralization differences in visual word recognition between different languages without assuming influence from left hemisphere (LH) lateralized language processes. We apply a hemispheric processing model of face recognition to visual word recognition; the model implements a theory of hemispheric asymmetry in perception that posits low spatial frequency biases in the right hemisphere and high spatial frequency (HSF) biases in the LH. We show two factors that can influence lateralization: (a) Visual similarity among words: The more similar the words in the lexicon look visually, the more HSF/LH processing is required to distinguish them, and (b) Requirement to decompose words into graphemes for grapheme-phoneme mapping: Alphabetic reading (involving grapheme-phoneme conversion) requires more HSF/LH processing than logographic reading (no grapheme-phoneme mapping). These factors may explain the difference in lateralization between English and Chinese orthographic processing.