Elizabeth S. Norton

Rapid Automatized Naming (RAN) and Reading Fluency: Implications for Understanding and Treatment of Reading Disabilities

Fluent reading depends on a complex set of cognitive processes that must work together in perfect concert. Rapid automatized naming (RAN) tasks provide insight into this system, acting as a microcosm of the processes involved in reading. In this review, we examine both RAN and reading fluency and how each has shaped our understanding of reading disabilities. We explore the research that led to our current understanding of the relationships between RAN and reading and what makes RAN unique as a cognitive measure. We explore how the automaticity that supports RAN affects reading across development, reading abilities, and languages, and the biological bases of these processes. Finally, we bring these converging areas of knowledge together by examining what the collective studies of RAN and reading fluency contribute to our goals of creating optimal assessments and interventions that help every child become a fluent, comprehending reader.

Tracking the Roots of Reading Ability: White Matter Volume and Integrity Correlate with Phonological Awareness in Prereading and Early-Reading Kindergarten Children

Developmental dyslexia, an unexplained difficulty in learning to read, has been associated with alterations in white matter organization as measured by diffusion-weighted imaging. It is unknown, however, whether these differences in structural connectivity are related to the cause of dyslexia or if they are consequences of reading difficulty (e.g., less reading experience or compensatory brain organization). Here, in 40 kindergartners who had received little or no reading instruction, we examined the relation between behavioral predictors of dyslexia and white matter organization in left arcuate fasciculus, inferior longitudinal fasciculus, and the parietal portion of the superior longitudinal fasciculus using probabilistic tractography. Higher composite phonological awareness scores were significantly and positively correlated with the volume of the arcuate fasciculus, but not with other tracts. Two other behavioral predictors of dyslexia, rapid naming and letter knowledge, did not correlate with volumes or diffusion values in these tracts. The volume and fractional anisotropy of the left arcuate showed a particularly strong positive correlation with a phoneme blending test. Whole-brain regressions of behavioral scores with diffusion measures confirmed the unique relation between phonological awareness and the left arcuate. These findings indicate that the left arcuate fasciculus, which connects anterior and posterior language regions of the human brain and which has been previously associated with reading ability in older individuals, is already smaller and has less integrity in kindergartners who are at risk for dyslexia because of poor phonological awareness. These findings suggest a structural basis of behavioral risk for dyslexia that predates reading instruction.

Brain Basis of Phonological Awareness for Spoken Language in Children and Its Disruption in Dyslexia

Phonological awareness, knowledge that speech is composed of syllables and phonemes, is critical for learning to read. Phonological awareness precedes and predicts successful transition from language to literacy, and weakness in phonological awareness is a leading cause of dyslexia, but the brain basis of phonological awareness for spoken language in children is unknown. We used functional magnetic resonance imaging to identify the neural correlates of phonological awareness using an auditory word-rhyming task in children who were typical readers or who had dyslexia (ages 7-13) and a younger group of kindergarteners (ages 5-6). Typically developing children, but not children with dyslexia, recruited left dorsolateral prefrontal cortex (DLPFC) when making explicit phonological judgments. Kindergarteners, who were matched to the older children with dyslexia on standardized tests of phonological awareness, also recruited left DLPFC. Left DLPFC may play a critical role in the development of phonological awareness for spoken language critical for reading and in the etiology of dyslexia.

Neurobiology of Dyslexia

Dyslexia is one of the most common learning disabilities, yet its brain basis and core causes are not yet fully understood. Neuroimaging methods, including structural and functional magnetic resonance imaging, diffusion tensor imaging, and electrophysiology, have significantly contributed to knowledge about the neurobiology of dyslexia. Recent studies have discovered brain differences before formal instruction that likely encourage or discourage learning to read effectively, distinguished between brain differences that likely reflect the etiology of dyslexia versus brain differences that are the consequences of variation in reading experience, and identified distinct neural networks associated with specific psychological factors that are associated with dyslexia.

Reading Abilities: Importance of Visual-Spatial Attention

Children with dyslexia may read poorly for several reasons. Recent research suggests that in addition to skills with language sounds, visual-spatial attention may be an important predictor of reading abilities.

Integrating MRI brain imaging studies of pre-reading children with current theories of developmental dyslexia: A review and quantitative meta-analysis.

The neurobiological substrates that cause people with dyslexia to experience difficulty in acquiring accurate and fluent reading skills are still largely unknown. Although structural and functional brain anomalies associated with dyslexia have been reported in adults and school-age children, these anomalies may represent differences in reading experience rather than the etiology of dyslexia. Conducting MRI studies of pre-readers at risk for dyslexia is one approach that enables us to identify brain alterations that exist before differences in reading experience emerge. The current review summarizes MRI studies that examine brain differences associated with risk for dyslexia in children before reading instruction and meta-analyzes these studies. In order to link these findings with current etiological theories of dyslexia, we focus on studies that take a modular perspective rather than a network approach. Although some of the observed differences in pre-readers at risk for dyslexia may still be shaped by language experiences during the first years of life, such studies underscore the existence of reading-related brain anomalies prior to reading onset and could eventually lead to earlier and more precise diagnosis and treatment of dyslexia.

How the origins of the reading brain instruct our knowledge of reading intervention

W. Baker, Preface. P. McCardle, N. Landi, K. Pugh, Introduction. Section 1. Major Themes in the Study of the Neurobiology of Dyslexia. S. Frost, R. Sandak, W.E. Mencl, N. Landi, J.G. Rueckl, L. Katz, K. Pugh, Mapping the Word Reading Circuitry in Skilled and Disabled Readers. G. Rosen, Y. Wang, C.G. Fiondella, J.J. Lo Turco, The Brain and Developmental Dyslexia: Genes, Anatomy, and Behavior. G. Sherman, C. Cowen, From Research Lab to School Front Lines: Talents and Dilemmas in Children with Learning Differences. Section 2. Methods and Tools. D. Francis, Methodological Advances in Developmental Research. E. Mencl, S. Frost, K. Pugh, Tools for Multimodal Imaging. J. Rueckl, M. Seidenberg, Computational Modeling and the Neural Bases of Reading and Reading Disorders. E. Grigorenko, A.J. Naples, The Devil is in the Details: Decoding the Genetics of Reading. Section 3. Neurobiological, Genetic, and Cognitive Aspects. F. Ramus, G. Szenkovits, Understanding the Nature of the Phonological Deficit. P. Cornelissen, Visual Word Recognition: Insights from MEG and Implications for Developmental Dyslexia. L.E. Cutting, S.H. Eason, K. Young, A.L. Alberstadt, Reading Comprehension: Cognition and Neuroimaging. R. Olson, B. Byrne, S. Samuelsson, Reconciling Strong Genetic and Strong Environmental Influences on Individual Differences and Deficits in Reading Ability. R. Frost, Reading in Hebrew vs. Reading in English: Is there a Qualitative Difference? Section 4. Intervention. B. Foorman, S. Al Otaiba, Reading Remediation: State of the Art. L. Siegel, Remediation of Reading Difficulties in English Language Learning Students. M. Wolf, S. Gottwald, W. Galante, E. Norton, L. Miller, How the Origins of Reading Instruct our Knowledge of Reading Development and its Intervention. P. McCardle, K. Pugh, Integration of Methodologies in Cognitive Neuroscience: Research Planning and Policy.

Links between looking and speaking in autism and first-degree relatives: insights into the expression of genetic liability to autism

BackgroundRapid automatized naming (RAN; naming of familiar items presented in an array) is a task that taps fundamental neurocognitive processes that are affected in a number of complex psychiatric conditions. Deficits in RAN have been repeatedly observed in autism spectrum disorder (ASD), and also among first-degree relatives, suggesting that RAN may tap features that index genetic liability to ASD. This study used eye tracking to examine neurocognitive mechanisms related to RAN performance in ASD and first-degree relatives, and investigated links to broader language and clinical-behavioral features.MethodsFifty-one individuals with ASD, biological parents of individuals with ASD (n = 133), and respective control groups (n = 45 ASD controls; 58 parent controls) completed RAN on an eye tracker. Variables included naming time, frequency of errors, and measures of eye movement during RAN (eye-voice span, number of fixations and refixations).ResultsBoth the ASD and parent-ASD groups showed slower naming times, more errors, and atypical eye-movement patterns (e.g., increased fixations and refixations), relative to controls, with differences persisting after accounting for spousal resemblance. RAN ability and associated eye movement patterns were correlated with increased social-communicative impairment and increased repetitive behaviors in ASD. Longer RAN times and greater refixations in the parent-ASD group were driven by the subgroup who showed clinical-behavioral features of the broad autism phenotype (BAP). Finally, parent-child dyad correlations revealed associations between naming time and refixations in parents with the BAP and increased repetitive behaviors in their child with ASD.ConclusionsDifferences in RAN performance and associated eye movement patterns detected in ASD and in parents, and links to broader social-communicative abilities, clinical features, and parent-child associations, suggest that RAN-related abilities might constitute genetically meaningful neurocognitive markers that can help bridge connections between underlying biology and ASD symptomatology.

The relationship between socioeconomic status and white matter microstructure in pre-reading children: A longitudinal investigation

Reading is a learned skill crucial for educational attainment. Children from families of lower socioeconomic status (SES) tend to have poorer reading performance and this gap widens across years of schooling. Reading relies on the orchestration of multiple neural systems integrated via specific white‐matter pathways, but there is limited understanding about whether these pathways relate differentially to reading performance depending on SES background. Kindergarten white‐matter FA and second‐grade reading outcomes were investigated in an SES‐diverse sample of 125 children. The three left‐hemisphere white‐matter tracts most associated with reading, and their right‐hemisphere homologs, were examined: arcuate fasciculus (AF), superior longitudinal fasciculus (SLF), and inferior longitudinal fasciculus (ILF). There was a significant and positive association between SES and fractional anisotropy (FA) in the bilateral ILF in kindergarten. SES moderated the association between kindergarten ILF and second grade reading performance, such that it was positive in lower‐SES children, but not significant in higher‐SES children. These results have implications for understanding the role of the environment in the development of the neural pathways that support reading.