The early school age period is a time of significant developmental change in both cognitive abilities and neural systems. Yet little is known about how, specifically, these developmental processes that occur concurrently are linked to each other, or about the nature of critical interactions of biological factors with childhood experiences and environments. The proposed project takes a critical first step in addressing this problem by examining, in unprecedented detail, the development of basic cognitive processes and of the neural systems that mediate them during the child's transition to formal schooling. The design is a longitudinal study of 100 typically- developing children inducted at age 6 and assessed with behavioral measures and MRI annually on 5 occasions. The behavioral measures to be collected, of language, visuospatial processing, working memory, and cognitive control, have exhibited high sensitivity to developmental change over this age range. MR imaging of the children will involve recently developed, improved methods for image acquisition and computational modeling of the results. Diffusion parameters from specific brain fiber tracts as well as regional measures of cortical surface area and thickness will be measured. The focus of the study is on differences in the rate of fiber tract development from 6 to 10 years of age and links between this variability and the pace of cognitive development. Relationships between the neural parameters and early academic achievement will also be examined. The study is novel, not only because the imaging methods to be applied will produce more detailed information about the brains of children than is currently available, but also because of the conceptual focus of the project on the degree of concordance between trajectories of brain and behavioral development. The long-term significance of the study lies in its potential to guide us toward interventions that are more adaptive to individual differences and therefore promote positive outcomes in more children.
The research described in this application will use magnetic resonance imaging to determine how much healthy children differ from each other in the rate at which their brains develop biologically, particularly in the connecting fibers that transmit information within the brain, and how closely this mirrors the pace of their mental development. The aim of the research is to increase our understanding of differences among children so that we can use this knowledge to create more supportive environments for all children, and also to guide us toward interventions that may allow us to prevent some mental illnesses.
|Schork, Andrew J; Wang, Yunpeng; Thompson, Wesley K et al. (2016) New statistical approaches exploit the polygenic architecture of schizophrenia--implications for the underlying neurobiology. Curr Opin Neurobiol 36:89-98|
|Newman, Erik; Jernigan, Terry L; Lisdahl, Krista M et al. (2016) Go/No Go task performance predicts cortical thickness in the caudal inferior frontal gyrus in young adults with and without ADHD. Brain Imaging Behav 10:880-92|
|Newman, Erik; Thompson, Wesley K; Bartsch, Hauke et al. (2016) Anxiety is related to indices of cortical maturation in typically developing children and adolescents. Brain Struct Funct 221:3013-25|
|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|
|Jernigan, Terry L; Brown, Timothy T; Bartsch, Hauke et al. (2016) Toward an integrative science of the developing human mind and brain: Focus on the developing cortex. Dev Cogn Neurosci 18:2-11|
|Desikan, R S; Schork, A J; Wang, Y et al. (2015) Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus. Mol Psychiatry 20:1588-95|
|Noble, Kimberly G; Houston, Suzanne M; Brito, Natalie H et al. (2015) Family income, parental education and brain structure in children and adolescents. Nat Neurosci 18:773-8|
|Reppe, Sjur; Wang, Yunpeng; Thompson, Wesley K et al. (2015) Genetic Sharing with Cardiovascular Disease Risk Factors and Diabetes Reveals Novel Bone Mineral Density Loci. PLoS One 10:e0144531|
|Desikan, Rahul S; Schork, Andrew J; Wang, Yunpeng et al. (2015) Polygenic Overlap Between C-Reactive Protein, Plasma Lipids, and Alzheimer Disease. Circulation 131:2061-9|
|Rosen, Ori; Thompson, Wesley K (2015) Bayesian semiparametric copula estimation with application to psychiatric genetics. Biom J 57:468-84|
Showing the most recent 10 out of 19 publications