Data Exploration and Analysis Portal for Brain Research through Advanced Imaging Neuroscience

项目摘要 人口神经科学要求在流行病学范围内调查大脑-行为关系 以纵向设计研究的样本，包括大量评估模式和受试者 在许多数据收集点登记，以获得大样本和广泛的人口代表性。的 注：青少年大脑认知发展(ABCD)研究和人类连接组计划 发展项目(HCP-D和HCP-A)总共招收了数以千计的人，其中许多人是儿童 和青少年，预计将在长达十年的时间里遵守这些规定。预见到需要一种可访问的 分析平台为了促进严格的建模，zai zai数据分析和信息学中心(DAIC)拥有 开发和部署基于网络的数据探索和分析门户(DEAP)。尽管它还处于萌芽状态 当前版本的DEAP已经提供了一种灵活的工具，可以满足这两种数据的许多需求 科学家和应用研究人员。在这里，我们建议生成一个更多功能的DEAP扩展，即 通过高级成像神经科学(DEAP)进行脑研究的数据探索和分析门户 大脑)。我们将通过整合以下方法来实施重要的新功能：i)将HCP数据包括到 评估概括性；ii)新开发的多顶点评分作为总结概括性的方法 全脑模式；以及iii)基于因果推理方法的偏差评估。在完成这项工作后 建议，我们将促进可重复和有效的科学发现通过提供研究社区 使用简单易用但复杂的信息学工具。这项建议的具体目标是： 具体目标1：将HCP数据整合到DEAP-Brain中。我们将通过以下方式集成ABCD和HCP数据 使成像处理和可变约定同质化。HCP成人队列和HCP寿命 开发队列将被整合到DEAP中，从而能够对推广能力进行正式评估。 具体目标2：将多边形顶点得分(PVS)作为评估泛化能力的框架 脑电地形图。我们将实施我们新开发的PVS方法，这是一种创新的方法 总结整个大脑中联想模式的重现性。 具体目标3：实施偏见评估模块。我们将实现偏差评估模块 对于基于因果推理原则的DEAP用户，使用倾向评分、主成分方法、 和合成控制系统。

Project Summary Population neuroscience requires investigation of brain-behavioral relationships within epidemiological samples studied in longitudinal designs, including a large number of assessment modalities and with subjects enrolled at many data collection sites to achieve a large sample and broad representation of the population. Of note, the Adolescent Brain Cognitive Development (ABCD) Study and the Human Connectome Project Development (HCP-D and HCP-A), have, in aggregate, enrolled thousands of individuals, many as children and adolescents, and are expected to follow them for up to ten years. Foreseeing the need for an accessible analysis platform to foster rigorous modeling, the ABCD Data Analysis and Informatics Center (DAIC) has developed and deployed the web-based Data Exploration and Analysis Portal (DEAP). Despite its nascent stage, the present version of DEAP already provides a flexible tool that meets many needs of both data scientists and applied investigators. Here, we propose to produce a more versatile extension of DEAP, the Data Exploration and Analysis Portal for Brain Research through Advanced Imaging Neuroscience (DEAP- BRAIN). We will implement important new features by incorporating approaches for: i) including HCP data to assess generalizability; ii) newly developed poly-vertex score as a method to summarize generalizability of whole brain patterns; and iii) bias assessment based on causal inference methods. By the completion of this proposal, we will facilitate reproducible and valid scientific discovery through providing the research community with an easy to use but sophisticated informatics tool. The Specific Aims of the proposal are: Specific Aim 1: Integrating HCP data into DEAP-BRAIN. We will integrate ABCD and HCP data through homogenizing the imaging processing and variable conventions. The HCP adult cohort and HCP lifespan development cohort will be integrated in DEAP, allowing a formal assessment of generalizability. Specific Aim 2: Implementing poly-vertex scores (PVS) as the framework for assessing generalizability of brain mapping. We will implement our newly developed PVS method, an innovative approach to summarize the reproducibility of association patterns across brain. Specific Aim 3: Implementing bias assessment modules. We will implement the bias assessment module for DEAP users based on causal inference principles, using propensity scores, principal component methods, and synthetic controls.