What Underlies the Deficit in Rapid Automatized Naming (RAN) in Adults with Dyslexia? Evidence from Eye Movements

ABSTRACT

This eye-tracking study explored how phonological encoding and speech production planning for successive words are coordinated in adult readers with dyslexia (N = 22) and control readers (N = 25) during rapid automatized naming (RAN). Using an object-RAN task, we orthogonally manipulated the word-form frequency and phonological neighborhood density of the object names and assessed the effects on speech and eye movements and their temporal coordination. In both groups, there was a significant interaction between word frequency and neighborhood density: shorter fixations for dense than for sparse neighborhoods were observed for low- but not for high-frequency words. This finding does not suggest a specific difficulty in lexical phonological access in dyslexia. However, in readers with dyslexia only, these lexical effects percolated to the late processing stages, indicated by longer offset eye-speech lags. We close by discussing potential reasons for this finding, including suboptimal specification of phonological representations and deficits in attention control or in multi-item coordination.

Acknowledgments

The first author and this work were supported by IF 2015 Program of the Portuguese Foundation for Science and Technology, FCT (ref. IF/00533/2015) and by the Research Center for Psychological Science at Universidade de Lisboa (CICPSI). Many thanks are due to anonymous reviewers for their helpful comments on earlier drafts of this article.

Conflict of Interest

The authors declare no conflict of interest.

Disclosure statement

The authors declare no conflict of interest.

Data sharing

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1. Regarding the eye-voice span (EVS) and articulation time (AT) measures, the amount of data sample that was entered into the analysis was smaller because of recording problems; yet, the analyses on these measures were still based on a substantial number of items (In total, 5,460 and 5,447 observations contributed to the EVS and ET analyses, respectively).

Additional information

Funding

This work was supported by the Portuguese Foundation for Science and Technology [IF/00533/2015].