Using Cognitive Neuroscience to Predict Dyslexia Among Kindergarten Children

The long-term objective of this research is to understand the brain basis of developmental dyslexia, one of the most common specific learning disabilities, and to advance early identification of dyslexia so that early intervention can minimize the documented negative influence of dyslexia on student achievement, self-perception, and long-term life outcomes. Dyslexia typically results from a deficit in phonological awareness (the ability to manipulate speech sounds of language) that precedes and impairs learning to read, but the underlying cause of this deficit has not yet been determined. Neuroimaging methods, including event-related potentials (ERPs), functional magnetic resonance imaging (fMRI), and diffusion tensor imaging (DTI), have identified brain differences in children with dyslexia. Nearly all of these studies, however, involve older children with demonstrated reading failure, so two essential questions remain unanswered. First, what brain differences lead to dyslexia (i.e., are present in 5-year-old kindergartners prior to reading instruction in the 1st grade)? Second, can brain measures significantly enhance our ability to predict which pre-reading children at risk for dyslexia in kindergarten actually go on to become dyslexic by second grade? To answer these questions, we propose a longitudinal study that involves (1) screening 1000 pre-reading kindergartners to identify 120 children at risk for dyslexia and 60 children not at risk; (2) perform MRI, fMRI, DTI, and ERP experiments in these 180 kindergartners to identify brain differences in children with versus without risk for dyslexia; (3) longitudinally follow the language and reading development of these children to discover which at-risk children actually progress to dyslexia at the end of 2nd grade; and (4) use various statistical methods, including multivariate statistics, to improve the accuracy with pre-reading kindergartners can be identified as being at true risk for dyslexia. This study is novel in its multimodal imaging with young children, its longitudinal follow-up, and its translational health aim of developing methods to accurately identify young children at true risk for dyslexia so that such children can be offered early intervention to minimize their learning difficulties.