Word recognition is affected by the meaning of orthographic neighbours: Evidence from semantic decision tasks

Abstract

Many models of word recognition predict that neighbours of target words will be activated during word processing. Cascaded models can make the additional prediction that semantic features of those neighbours get activated before the target has been uniquely identified. In two semantic decision tasks neighbours that were congruent (i.e., from the same category) or incongruent (i.e., from the opposite category) were presented in a long-term priming paradigm. Performance to targets was better if they were primed by congruent neighbours than if they were primed by incongruent neighbours. The same effect was found for rhyming and nonrhyming primes. The results support cascaded models that allow semantic information to become activated before lexical selection has finished.

Acknowledgements

This research was supported by a grant from the Netherlands Organization for Scientific Research (NWO) to Diane Pecher. We would like to thank René Zeelenberg for useful discussions.

Notes

¹There are other types of orthographic similarity such as subsets and letter exchanges (Bowers, Davis, & Hanley, 2005; Perea & Lupker, 2003, 2004) but for the present purposes we assume that these all behave in similar ways.

²These features are given only as illustration. Of course, such a decision process may use more primitive features. At present, no word recognition model explicitly specifies what semantic features are used to represent meaning.

³With all the restrictions that were placed on item selection it was impossible to have the exact same number of items in each condition and still have a reasonable number of items. However, the critical comparisons (congruency and rhyme) have approximately equal numbers in each condition.

⁴Although item analyses are not required for counterbalanced designs (Raaijmakers, 2003; Raaijmakers, Schrijnemakers, & Gremmen, 1999) we provide the results of an additional ANOVA by items for the interested reader.