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The role of letter features on the consonant-bias effect: Evidence from masked priming.

Authors
  • Soares, Ana Paula1
  • Velho, Mariana2
  • Oliveira, Helena Mendes2
  • 1 Human Cognition Lab, CIPsi, School of Psychology, University of Minho, Braga, Portugal.. Electronic address: [email protected] , (Portugal)
  • 2 Human Cognition Lab, CIPsi, School of Psychology, University of Minho, Braga, Portugal. , (Portugal)
Type
Published Article
Journal
Acta psychologica
Publication Date
Oct 01, 2020
Volume
210
Pages
103171–103171
Identifiers
DOI: 10.1016/j.actpsy.2020.103171
PMID: 32891854
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Recent research has shown an advantage of consonants at early stages of visual word recognition (C-bias), although the locus of this effect remains elusive. Here we examine whether the C-bias is affected by the consonant letters' features. Skilled readers performed a masked priming lexical decision task in which target words containing only either consonants without any ascending/descending features (flat words, canino[canine]) or consonants with ascending/descending features (non-flat words, palito[toothpick]) were preceded by briefly (50 ms) presented primes that could preserve the same consonants of the targets (cenune-CANINO, pelute-PALITO), the same vowels of the targets (raxizo-CANINO, fajibo-PALITO), or, as controls, unrelated (ruxuze-CANINO, fejube-PALITO) and identity primes (canino-CANINO, palito-PALITO). The case in which prime-target pairs were presented was also manipulated (lower-upper vs. upper-lower). Results showed that in both case conditions flat words were recognized faster than non-flat words. Evidence for the C-bias was observed both for flat and non-flat words in the lower-upper condition, in which a vowel inhibitory priming effect was also observed for non-flat words. In the upper-lower condition, however, the C-bias was restricted to flat words. These findings suggest that letter features play a role in the C-bias and ask for amendments in current models of visual word recognition. Copyright © 2020 Elsevier B.V. All rights reserved.

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