This three-year project will leverage a unique, recently collected set of data entitled Pediatric Imaging, Neurocognition, and Genetics (PING), which includes neuroimaging, cognitive, demographic, behavioral, and genome-wide genotyping data for over 1,200 children and adolescents ranging from 3 to 20 years of age. This is the largest source of neuroimaging, genomics, and cognitive data across the developmental age span assembled to date and was created as a resource to the scientific community. We will conduct the first comprehensive and well-powered study of cognitive development and state-of-the-art neural architectural phenotypes and genome-wide genotyping in a large typically developing pediatric sample to advance the understanding of the neurobehavioral development of executive functions. Our preliminary studies have demonstrated that the measures of brain morphology, diffusivity, and signal intensity show varying contributions to the prediction of developmental phase at different ages in this sample, reflecting a dynamic cascade of biological changes within different tissue types. Results from the NIH Toolbox Cognitive Battery show that these measures are sensitive to neurodevelopmental effects and provide rich information about a variety of important cognitive functions. Our research project has four Specific Aims designed to link individual variability in executive function performance to typically developing neural systems and genetic influences, using cutting-edge nonlinear multidimensional statistical modeling and a novel polygenic risk scores approach for assessing aggregate genetic influence. We predict that these results will enhance our understanding of how cognitive dimensions change and emerge with changing neural phenotypes, and the impact of individual sociodemographic variation. This is critical to understanding variability in behavioral and neuropsychiatric outcomes and developing important prevention and intervention efforts.

Public Health Relevance

This three-year project will leverage the Pediatric Imaging, Neurocognition, and Genetics (PING) database to advance our understanding of the development of executive functions and their neurobiological and genetic underpinnings. These functions play a critical role in multiple cognitive skills and school success and are affected in variety of developmental disorders. This study will significantly advance our scientific knowledge about human neurobehavioral development, and this characterization of typical development will thus provide a rich context for better understanding variations in developmental trajectories.

National Institute of Health (NIH)
National Institute on Drug Abuse (NIDA)
Research Project (R01)
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Study Section
Child Psychopathology and Developmental Disabilities Study Section (CPDD)
Program Officer
Boyce, Cheryl A
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University of California San Diego
Schools of Medicine
La Jolla
United States
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Fan, Chun Chieh; Schork, Andrew J; Brown, Timothy T et al. (2018) Williams Syndrome neuroanatomical score associates with GTF2IRD1 in large-scale magnetic resonance imaging cohorts: a proof of concept for multivariate endophenotypes. Transl Psychiatry 8:114
Wierenga, Lara M; van den Heuvel, Martijn P; Oranje, Bob et al. (2018) A multisample study of longitudinal changes in brain network architecture in 4-13-year-old children. Hum Brain Mapp 39:157-170
Akshoomoff, Natacha; Brown, Timothy T; Bakeman, Roger et al. (2018) Developmental differentiation of executive functions on the NIH Toolbox Cognition Battery. Neuropsychology 32:777-783
Schork, A J; Brown, T T; Hagler, D J et al. (2018) Polygenic risk for psychiatric disorders correlates with executive function in typical development. Genes Brain Behav :e12480
Fan, Chun Chieh; Brown, Timothy T; Bartsch, Hauke et al. (2017) Williams syndrome-specific neuroanatomical profile and its associations with behavioral features. Neuroimage Clin 15:343-347
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Jernigan, Terry L; Brown, Timothy T; Hagler Jr, Donald J et al. (2016) The Pediatric Imaging, Neurocognition, and Genetics (PING) Data Repository. Neuroimage 124:1149-54
Fan, Chun Chieh; Bartsch, Hauke; Schork, Andrew J et al. (2015) Modeling the 3D geometry of the cortical surface with genetic ancestry. Curr Biol 25:1988-92