Summation Priming and Coarse Semantic Coding in the Right Hemisphere

  • Beeman M
  • Friedman R
  • Grafman J
 et al. 
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Abstract

Abstract There are now numerous observations of subtle right hemisphere (RH) contributions to language comprehension. It has been suggested that these contributions reflect coarse semantic coding in the RH. That is, the RH weakly activates large semantic fields-including concepts distantly related to the input word-whereas the left hemisphere (LH) strongly activates small semantic fields-limited to concepts closely related to the input (Beeman, 1993a,b). This makes the RH less effective at interpreting single words, but more sensitive to semantic overlap of multiple words. To test this theory, subjects read target words preceded by either "Summation" primes (three words each weakly related to the target) or Unrelated primes (three unrelated words), and target exposure duration was manipulated so that subjects correctly named about half the target words in each hemifield. In Experiment 1, subjects benefited more from Summation primes when naming target words presented to the left visual field-RH (Ivf-RH) than when naming target words presented to the right visual field-LH (rvf-LH), suggesting a RH advantage in coarse semantic coding. In Experiment 2, with a low proportion of related prime-target trials, subjects benefited more from "Direct" primes (one strong associate flanked by two unrelated words) than from Summation primes for rvf-LH target words, indicating that the LH activates closely related information much more strongly than distantly related information. Subjects benefited equally from both prime types for Ivf-RH target words, indicating that the RH activates closely related information only slightly more strongly, at best, than distantly related information. This suggests that the RH processes words with relatively coarser coding than the LH, a conclusion consistent with a recent suggestion that the RH coarsely codes visual input (Kosslyn, Chabris, Mar-solek, & Koenig, 1992).

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Authors

  • Mark Beeman

  • Rhonda B. Friedman

  • Jordan Grafman

  • Enrique Perez

  • Sherri Diamond

  • Miriam Beadle Lindsay

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