Temporal dynamics of syllable priming effects on visual word recognition: Evidence from different prime durations

Although the syllable has been shown to play a relevant role at early stages of visual word recognition, several studies using consonant-vowel (CV) and consonant-vowel-consonant (CVC) first-syllable words have also shown that reliable effects are observed for CV but not for CVC words. Several proposals have been advanced to account for this syllable structure effect, though studies aiming to directly address this issue are scarce. Here we tested whether syllable complexity might underlie the syllable structure effect observed in several languages, by replicating the masked priming lexical decision study conducted by Campos, Oliveira, and Soares (2018) with Portuguese adult skilled readers using 50-ms pseudoword primes, but using longer (67-ms and 82-ms) prime durations. If the structure syllable effect is driven by syllable complexity, increasing prime durations should make facilitative syllable priming effects to emerge for CVC words. Furthermore, by manipulating prime durations we can also provide new insights into the temporal dynamics of syllable effects at early stages of visual word recognition. Results from linear mixed effects (lme) models analyses showed that even with increased prime durations, reliable syllable effects were still restricted to CV words. Increasing prime durations to 67 ms and 82 ms only strengthened orthographic priming effects for CVC words. Moreover, the magnitude of the priming effects for CV words remained fairly constant across these prime durations, thus suggesting that the CV advantage on visual word recognition is not a short-lived effect. Results are discussed attending to current findings in the literature.This study was conducted at the Psychology Research Centre (PSI/01662), University of Minho, and was supported by the Grants PD/BD/128464/2017 and POCI-01-0145-FEDER-028212 from the Fundacao para a Ciencia e Tecnologia (Portugal), and co-financed by FEDER through COMPETE2020 under the PT2020 Partnership Agreement