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Cognitive and neural predictors of comorbidity between reading and attention problems

$410,336R15FY2016HDNIH

University Of Denver (Colorado Seminary), Denver CO

Investigators

Linked publications, trials & patents

Abstract

Project Summary/Abstract Comorbidity is a pervasive clinical problem in developmental psychopathology and is an important predictor of key academic and functional outcomes, including school failure and treatment response. However, little is known about the cognitive and neural mechanisms that increase a child's risk for multiple disorders. In this proposal, we aim to identify cognitive and neural factors that predict comorbidity between reading disability (RD) and attention-deficit/hyperactivity disorder (ADHD), both highly prevalent disorders (5-10%) with a high comorbidity rate (25-40%). Typical analytic methods are insufficient to directly test predictors of comorbidity, but emerging ?multiple deficit models? of developmental disorders can address this limitation. This proposal adopts a multiple deficit framework to identify cognitive and neural predictors of the relationship (or covariance) between RD and ADHD, rather than the more common approach of predicting the individual disorders. The work of our group and others suggests that processing speed (PS) and aspects of executive dysfunction are potential shared cognitive deficits of RD and ADHD. Despite these leads, very few studies have directly tested a multiple deficit model of comorbidity at the cognitive and neural levels of analysis (Aim 1 & 3), and none have tried to bridge these levels (Aim 3) or to examine the developmental unfolding of shared deficits associated with comorbidity (Aim 2). To accomplish these aims, this proposal will use two large (N~400-5000), population-based, pediatric datasets of children 6-18 years. Both datasets included cognitive and behavioral assessments and structural brain imaging, and one of the datasets included longitudinal follow-up over time. Aim 1 will determine which cognitive correlates of reading and attention are shared and can account for a portion of their relationship. Aim 2 will utilize the longitudinal data to determine the developmental sequence of changes in shared cognitive risk factors in relation to changes in reading and attention, establishing whether shared cognitive correlates are more likely to be a cause or consequence of reading and attention problems. Aim 3 will use structural brain imaging data to determine which neural correlates of reading and attention overlap and whether this overlap is associated with shared cognitive risk factors. The overall goal of this work is to link shared neural risk factors to shared cognitive risk factors for reading and attention in order to develop a comprehensive account of this comorbidity across levels of analysis. A better understanding of this comorbidity will guide new approaches to early identification and intervention for this vulnerable group of children. Consistent with AREA goals, this project will provide research training for undergraduate and graduate students in child neuropsychology, developmental neuroimaging, and advanced statistics and provide valuable experience working across multiple levels of analysis.

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