Contributions of Letter-Speech Sound Learning and Visual Print Tuning to Reading Improvement: Evidence from Brain Potential and Dyslexia Training Studies

Abstract

We use a neurocognitive perspective to discuss the contribution of learning letter-speech sound (L-SS) associations and visual specialization in the initial phases of reading in dyslexic children. We review findings from associative learning studies on related cognitive skills important for establishing and consolidating L-SS associations. Then we review brain potential studies, including our own, that yielded two markers associated with reading fluency. Here we show that the marker related to visual specialization (N170) predicts word and pseudoword reading fluency in children who received additional practice in the processing of morphological word structure. Conversely, L-SS integration (indexed by mismatch negativity (MMN)) may only remain important when direct orthography to semantic conversion is not possible, such as in pseudoword reading. In addition, the correlation between these two markers supports the notion that multisensory integration facilitates visual specialization. Finally, we review the role of implicit learning and executive functions in audiovisual learning in dyslexia. Implications for remedial research are discussed and suggestions for future studies are presented.

Simulating reading acquisition: The link between reading outcome and multimodal brain signatures of letter–speech sound learning in prereaders

“…This result is in line with the finding that dyslexic children perform worse than normal readers when matching graphemes of an artificial-letter script with phonemes under time pressure 41 . Our findings in prereaders provide support for the assumption that impaired reading fluency in dyslexic readers is not caused by the inability to acquire letter–speech sound correspondences per se, but rather by a lack of automatization and fluency in these correspondences 14 , 33 , 34 .…”

“…Therefore, next to the behavioural precursor RAN, the rate at which prereaders learned artificial letter–speech sound correspondences correlated highly with later reading fluency. Interestingly, the novel precursor derived from the artificial-letter training represents a direct measure of automatization when learning associations between letters and speech sounds; such automatization is a key feature of successful reading acquisition 14 , 33 , 34 .…”

Atypical White Matter Connectivity in Dyslexic Readers of a Fairly Transparent Orthography

“…To this end, we investigate structural white matter connectivity by analyzing DWI data in both TR ( n = 13) and dyslexic children ( n = 15). The sample consisted of 8- to 11-year-old children, as previous work of our group showed the strongest developmental changes in the neural reading network, and more specifically in the cross-modal integration of letters and speech sounds, in the age-period of 8 to 11 years: from hardly any signs of cross-modal integration after 1 year of formal reading education (∼8 years of age) to almost adult-like neural processing after 4 years of education (∼11 years of age) ( Froyen et al, 2009 ; Blomert, 2011 ; Žarić et al, 2014 ; Fraga González et al, 2017 ). Our age-range represents a vital stage in the developmental path toward fluent reading, and from the perspective of dyslexia as a developmental disorder, thus zooms in at a stage where normal and abnormal pathways are expected to deviate.…”

Brain Responses to Letters and Speech Sounds and Their Correlations With Cognitive Skills Related to Reading in Children

“…It was found that the N1 and the VWFA activation in these kindergarteners significantly improved the prediction of reading skills in second grade over behavioral data alone and together with the behavioral measures they explained up to 88% of the variance in reading ( Bach et al, 2013 ). Therefore, visual N1 is considered as a sensitive index of visual letter string processing reflecting important processes for reading fluency ( Fraga González et al, 2014 , 2017 ).…”