Poster B67, Sunday, March 26, 8:00 – 10:00 am, Pacific Concourse
ERP correlates of early phonological processing in deaf and hearing readers: Do they reflect the same underlying mechanisms?
Eva Gutierrez1,2, Marta Vergara1, Eva Rosa3, Ana Marcet1, Amelia Maña1, Manuel Perea1; 1University of Valencia, Spain, 2University College London, 3Catholic University of Valencia San Vicente Mártir
The poor reading skills often found in deaf readers are typically explained on the basis of underspecified print-to-sound mapping, and the accompanying poorer use of spoken phonology. Studies using explicit phonological tasks have shown that deaf readers can use phonological codes when required. However, studies investigating the automatic use of phonological codes have not provided a clear answer of whether deaf and hearing readers use these codes in the same manner. The present ERP study used a masked sandwich priming technique to maximize the chance of detecting an automatic pseudohomophone effect in a group of deaf readers. Data from a group of hearing readers of similar age, socioeconomic variables and reading habits was also collected. EEG was recorded while participants performed a lexical decision to targets (CORAL) preceded by a pseudohomophone (koral) or an orthographic control (toral). Behavioral and electrophysiological effects of phonological priming were found in both groups. In line with previous research, hearing participants exhibited lower amplitudes for the pseudohomophone condition in both N250 (left anterior) and N400 (widely distributed) components. Deaf participants showed a difference in the same direction, but the phonological effect had a right-frontal distribution in both components. Furthermore, the N400 was shorter. These findings reveal that deaf readers use phonological codes early during visual-word recognition, but they might use them in a different manner than hearing readers. We will discuss the nature of these phonological influences and their relationships to reading ability in the context of current models of lexical access.
Topic Area: LANGUAGE: Other