This application for an NIMH Mentored Research Scientist Career Development (K01) award seeks support to develop a program of research focused on characterizing the development of white matter and working memory in children who are typically developing and in children who are at genetic high-risk for schizophrenia from 1 to 8 years of age. An additional aim of this program is to conduct a pilot study with typical children to determine the feasibility of measuring experience-dependent structural plasticity in white matter, following training with a standardized adaptive working memory program. The candidate seeks career development training in three areas to support her long-term career goals: 1) Advance her neuroimaging background with novel instruction in joint analysis of structural (sMRI) and diffusion tensor imaging (DTI) across multiple stages of early brain development, 2) Develop a strong knowledge base for the biostatistical methods used in longitudinal and multivariate analyses important for examining developmental trajectories, structure-function relationships, and subtle brain changes over time, and 3) Gain experience in the design, planning and implementation of neurocognitive interventions in young children. This program of training and research will improve current understanding of early brain development in typical and high-risk children in relation to an early emerging and formative cognitive skill, working memory. Results from the proposed research will be used to identify early biomarkers of risk, which can be used to inform the design of targeted preventive intervention strategies for high-risk children. Schizophrenia is a debilitating disease with early neurodevelopmental origins that impact the structure, function and connectivity of the brain. Impairments in network connectivity are likely responsible for many of the core features of schizophrenia, including poor working memory. By the time clinical symptoms present, in late adolescence or adulthood, the underlying pathologic brain development has already occurred and is most likely irreversible. Neuroimaging studies have consistently shown that patients had reduced gray matter (GM) volumes and increased lateral ventricles, prior to the onset of psychosis. Likewise, DTI studies suggest that white matter (WM) integrity is also reduced early in schizophrenia. Therefore the importance of identifying early indicators or biomarkers of risk is critical for determining who is at-risk and how to design targeted preventive interventions. Relatively little is known about how the brain develops during one of the most dynamic and critical periods of maturation, from birth to 6 years of age. As a consequence, our understanding of structure-function relationships during this developmental period is limited as well. Working memory emerges in infancy and serves as a cognitive building block for the formation of other executive functions. Poor working memory is a core feature of schizophrenia that is typically present in childhood, long before the onset of psychosis. Therefore, improving our understanding of brain development in relation to cognitive functions is critical for advancing our ability to identify individuals at-risk early in development and for promoting healthy long-term outcomes. Until recently, technological and methodological limitations prevented researchers from non- invasively characterizing these early periods of human brain development. Our multidisciplinary research team at the University of North Carolina, Chapel Hill has pioneered recent advances in noninvasive neuroimaging (sMRI and DTI), and has also developed innovative analysis techniques to characterize microstructural features of white matter in children. Our research team at UNC has generated the only longitudinal dataset available, with neuroimaging and cognitive measures, collected from birth through 6 years of age, from large cohorts of children who are typically developing and at genetic high-risk for schizophrenia. This existing data will serve as the basis for the proposed research and career development training. The importance of identifying early indicators or biomarkers of risk is critical for determining who is at-risk and how to design targeted preventive interventions. The proposed research will help identify white matter connections that are important for the development of working memory and will determine whether they are altered in children at risk for schizophrenia. In addition, the feasibility study f working memory training in typical children will provide valuable information about the capacity to measure experience-dependent structural changes in white matter tracts. Strengthening neural networks associated with early foundational cognitive processes may help to ameliorate later impairments in other cognitive, social and developmental capacities that depend on working memory.

Public Health Relevance

The proposed research will help to identify white matter tracts in the brain that are important for the development of working memory in typically developing children and this information will be used to determine whether these white matter tracts are altered in children at risk for schizophrenia. Evidence is often seen at the neural level before it becomes apparent at the behavioral level and working memory deficits are common in children who later develop schizophrenia. Thus, identifying early indicators or biomarkers of risk that predict the later onset of schizophrenia are important for 1) identifying who is at risk and 2) how to design targeted pre-emptive intervention strategies.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Scientist Development Award - Research & Training (K01)
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Study Section
Developmental Brain Disorders Study Section (DBD)
Program Officer
Sarampote, Christopher S
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University of North Carolina Chapel Hill
Schools of Medicine
Chapel Hill
United States
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Stephens, Rebecca L; Langworthy, Benjamin; Short, Sarah J et al. (2018) Verbal and nonverbal predictors of executive function in early childhood. J Cogn Dev 19:182-200
Lee, Seung Jae; Steiner, Rachel J; Yu, Yang et al. (2017) Common and heritable components of white matter microstructure predict cognitive function at 1 and 2 y. Proc Natl Acad Sci U S A 114:148-153
Short, Sarah J; Stalder, Tobias; Marceau, Kristine et al. (2016) Correspondence between hair cortisol concentrations and 30-day integrated daily salivary and weekly urinary cortisol measures. Psychoneuroendocrinology 71:12-8
Short, Sarah J; Lubach, Gabriele R; Shirtcliff, Elizabeth A et al. (2014) Population variation in neuroendocrine activity is associated with behavioral inhibition and hemispheric brain structure in young rhesus monkeys. Psychoneuroendocrinology 47:56-67
Alcauter, Sarael; Lin, Weili; Smith, J Keith et al. (2014) Development of thalamocortical connectivity during infancy and its cognitive correlations. J Neurosci 34:9067-75
Shi, Yundi; Short, Sarah J; Knickmeyer, Rebecca C et al. (2013) Diffusion tensor imaging-based characterization of brain neurodevelopment in primates. Cereb Cortex 23:36-48
Short, Sarah J; Elison, Jed T; Goldman, Barbara Davis et al. (2013) Associations between white matter microstructure and infants' working memory. Neuroimage 64:156-66
Gilmore, John H; Shi, Feng; Woolson, Sandra L et al. (2012) Longitudinal development of cortical and subcortical gray matter from birth to 2 years. Cereb Cortex 22:2478-85