Mapping the developing infant connectome

绘制发育中的婴儿连接组图

• 批准号: 10197927
• 负责人: Longchuan Li
• 金额: $ 50.32万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10197927
• 关键词: Address; Adult; Age-Months; Anatomy; Area; Benchmarking; Birth; Brain; Brain imaging; Characteristics; Code; Communities; Complex; Cross-Sectional Studies; Data; Data Set; Development; Developmental Process; Diffusion; Diffusion Magnetic Resonance Imaging; Disadvantaged; Functional Magnetic Resonance Imaging; Goals; Graph; Growth; Image; Individual; Infant; Infant Development; Lead; Life; Light; Longitudinal Studies; Magnetic Resonance Imaging; Maps; Mathematics; Measures; Methodology; Methods; Modeling; Neurodevelopmental Disorder; Neurosciences; Nodal; Principal Component Analysis; Property; Research; Research Project Grants; Rest; Sample Size; Sampling; Scanning; Scientific Inquiry; Shapes; Specific qualifier value; Statistical Data Interpretation; Structure; System; Techniques; Testing; Time; Variant; age group; analytical tool; base; brain research; cognitive development; cognitive function; connectome; course development; curve fitting; design; disability; frontier; graph theory; improved; individual variation; infancy; innovation; insight; longitudinal analysis; longitudinal design; method development; neural growth; neuroimaging; neuropsychiatry; novel; postnatal; postnatal development; prospective; rate of change; tool

PROJECT SUMMARY/ABSTRACT The overarching goal of this proposal is to develop new and innovative analytic tools for longitudinal infant brain research and to leverage these tools to chart the development of infant brain networks during the first 6 months of life, a period of unparalleled postnatal growth and change. Describing the developmental trajectory of brain systems during this formative period has the potential to provide groundbreaking insights into major areas of scientific inquiry, including the identification of brain systems that underlie the development of cognitive functions, the discovery of how structural and functional network specializations arise, and the identification of brain networks that contribute to neuropsychiatric illness. However, despite this potential, longitudinal studies of infant brain development are still nascent, and prevailing analytic tools—largely designed for cross-sectional analyses of adult data—are ill-suited for fully capturing fast-pace developmental processes during infancy. This proposal aims to 1) develop innovative analytic tools that are specifically designed to address challenges inherent to longitudinal infant brain research; 2) leverage these tools to examine graph theoretic measures of brain network development in typical infancy; and 3) disseminate these tools and approaches to the broader research community. Methods development will focus on two key areas: registration (the approach for transforming individual brain images to a common space) and statistical analysis of longitudinal data (the approach for constructing and analyzing growth curves of brain development). Methods development and analyses will be conducted on anatomical, diffusion tensor imaging and resting- state functional MRI data collected from infants at three longitudinal time points between birth and 6 months of age. Aim 1 of this proposal is to develop and validate a novel hierarchical, tensor-based registration approach, designed to handle the challenges associated with registering highly heterogeneous images, a characteristic of longitudinal infant data. Aim 2 will improve an already state-of-the-art approach for the analysis of longitudinal data and pioneer its application to the case of longitudinal neuroimaging data. Finally, Aim 3 will leverage these methods to produce a temporally-precise mapping of typical growth curves of brain network development in the first postnatal months, providing a benchmark against which to interpret and understand how alternate trajectories of brain development can lead to disability. These aims will help advance the frontier of studies of brain development into early infancy, a formative, and yet relatively uncharted, period of development.

项目摘要/摘要 该提案的总体目标是为纵向婴儿开发新的创新分析工具 大脑研究并利用这些工具来绘制前6个婴儿脑网络的发展 生命几个月，这是无与伦比的产后生长和变化的时期。描述发展轨迹 在这个形成期间的大脑系统的潜力有可能为主要的洞察力提供开创性的见解 科学探究领域，包括识别大脑系统的发展 认知功能，结构和功能网络专业的发现以及 识别导致神经精神疾病的大脑网络。但是，这是这种潜力， 婴儿脑发育的纵向研究仍然是偏生的，并且是普遍的分析工具 - 非常 专为成人数据的横截面分析而设计 - 不适合完全捕获快速发展的发展 婴儿期间的过程。该建议的目的是1）开发专门的创新分析工具 旨在应对纵向婴儿脑研究的挑战； 2）利用这些工具 检查典型婴儿脑网络发展的理论措施； 3）传播这些 更广泛的研究社区的工具和方法。方法开发将集中在两个关键领域： 注册（将单个大脑图像转换为公共空间的方法）和统计分析 纵向数据（构建和分析大脑发育生长曲线的方法）。 方法开发和分析将在解剖学，扩散张量成像和静止 在出生到6个月之间的三个纵向时间点，从婴儿收集的状态功能性MRI数据 年龄。该提案的目的1是开发和验证一种新型的基于张量的注册方法， 旨在应对与注册高度异构图像相关的挑战，这是 纵向婴儿数据。 AIM 2将改善已经最新的方法来分析纵向 数据并开拓其应用于纵向神经影像数据的情况。最后，AIM 3将利用这些 生产大脑网络发展典型生长曲线暂时映射的方法 第一个产后几个月，提供了一个基准，可以解释和理解如何选择 大脑发育的轨迹会导致残疾。这些目标将有助于发展 大脑发育成为早期的早期，是一个形成性的，但相对未知的发展时期。