Fragmented early-life experiences, aberrant circuit maturation, emotional vulnerabilities

拟成立的康特中心的项目包括人体研究和实验动物研究

The projects of the proposed Conte Center integrate human and experimental animal studies to investigate the overarching hypothesis that fragmentation and unpredictability of early life maternal and environmental signals (FRAG) contribute to adolescent vulnerabilities and subsequent mental illness via mechanisms involving aberrant development and maturation of emotional brain circuits. The Biostatistics, Computation and Data Management (BCDM) Core works closely with Projects 1-4 and the Imaging Core to plan and support their statistical analyses and to provide data management support. Through these efforts the Core plays a central role in ensuring the rigor and reproducibility of Center research. The BCDM Core also plays an integral role in the innovation of the Center through the development of statistical and computational models that use a range of cognitive, emotional and imaging variables to predict developmental vulnerabilities and risk for mental illness and through the development and testing of measures that assess fragmented and unpredictable early life signals. The BCDM Core is pivotal to the coordination and integration of results across projects and cores. Guided by constructive suggestions of the Reviewers of the original renewal submission, the core will:: 1) Provide computational and biostatistical support for studies of the relationship of FRAG with age- and sex- specific vulnerabilities and mental illness. Address the contributions of FRAG in the context of other risk factors and optimize approaches to the analysis of complex datasets including cognitive, emotional, and imaging data. 2). Use data from multiple human cohorts to test measures that easily, reliably, and accurately assess fragmented and unpredictable maternal and environmental signals. The Core will also capitalize on new data sources, (e.g., smartphone-based ecological mood assessments) to evelop new, reliable measures that enhance the Center's impact. 3). Develop statistical / computational models that integrate measures of early-life experiences with cognitive, emotional and imaging data to predict anhedonia and risk for mental illness. 4). Develop a Center information resource, provide data management support to all projects and cores, and facilitate integration across projects. This includes accommodating human demographic, cognitive, emotional, and imaging data and experimental animal data.