Evidence that rapid naming skill is associated with reading ability has become increasingly prevalent in recent years. However, there is considerable variation in the literature concerning the magnitude of this relationship. The objective of the present study was to provide a comprehensive analysis of the evidence on the relationship between rapid automatized naming (RAN) and reading performance. To this end, we conducted a meta-analysis of the correlational relationship between these 2 constructs to (a) determine the overall strength of the RAN-reading association and (b) identify variables that systematically moderate this relationship. A random-effects model analysis of data from 137 studies (857 effect sizes; 28,826 participants) indicated a moderate-to-strong relationship between RAN and reading performance (r ϭ .43, I 2 ϭ 68.40). Further analyses revealed that RAN contributes to the 4 measures of reading (word reading, text reading, non-word reading, and reading comprehension), but higher coefficients emerged in favor of real word reading and text reading. RAN stimulus type and type of reading score were the factors with the greatest moderator effect on the magnitude of the RAN-reading relationship. The consistency of orthography and the subjects' grade level were also found to impact this relationship, although the effect was contingent on reading outcome. It was less evident whether the subjects' reading proficiency played a role in the relationship. Implications for future studies are discussed.

a b s t r a c tThis ERP study investigated the cognitive nature of the P1-N1 components during orthographic processing. We used an implicit reading task with various types of stimuli involving different amounts of sublexical or lexical orthographic processing (words, pseudohomophones, pseudowords, nonwords, and symbols), and tested average and dyslexic readers. An orthographic regularity effect (pseudowords-nonwords contrast) was observed in the average but not in the dyslexic group. This suggests an early sensitivity to the dependencies among letters in word-forms that reflect orthographic structure, while the dyslexic brain apparently fails to be appropriately sensitive to these complex features. Moreover, in the adults the N1-response may already reflect lexical access: (i) the N1 was sensitive to the familiar vs. less familiar orthographic sequence contrast; (ii) and early effects of the phonological form (words-pseudohomophones contrast) were also found. Finally, the later N320 component was attenuated in the dyslexics, suggesting suboptimal processing in later stages of phonological analysis.

In this study, event related potentials (ERPs) were used to investigate the extent to which dyslexics (aged 9-13 years) differ from normally reading controls in early ERPs, which reflect prelexical orthographic processing, and in late ERPs, which reflect implicit phonological processing. The participants performed an implicit reading task, which was manipulated in terms of letter-specific processing, orthographic familiarity, and phonological structure. Comparing consonant- and symbol sequences, the results showed significant differences in the P1 and N1 waveforms in the control but not in the dyslexic group. The reduced P1 and N1 effects in pre-adolescent children with dyslexia suggest a lack of visual specialization for letter-processing. The P1 and N1 components were not sensitive to the familiar vs. less familiar orthographic sequence contrast. The amplitude of the later N320 component was larger for phonologically legal (pseudowords) compared to illegal (consonant sequences) items in both controls and dyslexics. However, the topographic differences showed that the controls were more left-lateralized than the dyslexics. We suggest that the development of the mechanisms that support literacy skills in dyslexics is both delayed and follows a non-normal developmental path. This contributes to the hemispheric differences observed and might reflect a compensatory mechanism in dyslexics.

No abstract

No abstract