Imaging genomics bases of pediatric executive functioning

儿科执行功能的影像基因组学基础

基本信息

批准号：
8830050
负责人：
Brian Avants
金额：
$ 15.96万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-29 至 2019-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8830050
关键词：
Academic Training Acceleration Address Adolescence Adolescent Affect Age Algorithms Area Attention deficit hyperactivity disorder Big Data Biological Biological Markers Brain Child Childhood Cognition Cognitive Confidence Intervals Data Data Set Development Disease Environment Environmental Risk Factor Equilibrium Genetic Genomics Genotype Healthcare Image Intervention Knowledge Lead Linear Algebra Magnetic Resonance Imaging Maps Mathematics Measurement Mental Health Mentors Methods Metric Modality Modeling Neurocognition Neurosciences Outcome Performance Philadelphia Population Predictive Value Prevention strategy Principal Investigator Psyche structure Psychometrics Randomized Relative (related person)Research Risk Sampling Science Scientist Single Nucleotide Polymorphism Site Socioeconomic Status Software Validation Statistical Methods System Testing Thinking Time Training Validation Work base career cohort executive function experience functional/structural genomics imaging modality improved innovation insight neurodevelopment neuroimaging neuropsychiatry novel public health relevance relating to nervous system success trait white matter

项目摘要

DESCRIPTION (provided by applicant): We propose to establish new integrative and data-driven methods for building systems neuroscience models of executive functioning during childhood. We will develop these methods by employing public datasets that contain complementary quantitative biological metrics of genomics, structural and functional neuroimaging and cognitive performance. By studying the multi-dimensional predictors of executive functioning during childhood, the Principal Investigator will gain invaluable protected time that will enhance his career as a big data scientist. The candidate will also gain experience in the new science of integrating imaging with genomics and in the statistical methods necessary to optimally construct sparse and interpretable low-dimensional models from high-dimensional data. We will determine validity by comparing models between training and independent testing datasets. Ultimately, this research will identify a fusion of genomics and imaging predictors that predict executive functioning in normal subjects and how these relationships are modified by environment.

描述（由申请人提供）：我们建议建立新的综合和数据驱动方法来构建儿童时期执行功能的系统神经科学模型。我们将通过使用包含基因组学、结构和功能神经影像以及认知表现的互补定量生物指标的公共数据集来开发这些方法。通过研究童年时期执行功能的多维预测因素，首席研究员将获得宝贵的受保护时间，这将增强他作为大数据科学家的职业生涯。候选人还将获得将成像与基因组学相结合的新科学以及从高维数据优化构建稀疏且可解释的低维模型所需的统计方法方面的经验。我们将通过比较训练数据集和独立测试数据集之间的模型来确定有效性。最终，这项研究将确定基因组学和成像预测因子的融合，预测正常受试者的执行功能以及这些关系如何被环境改变。