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

项目摘要 群体神经科学需要在流行病学范围内调查脑-行为关系 纵向设计中研究的样本，包括大量评估模式和受试者 在许多数据收集点登记，以实现大样本和广泛的人口代表性。的 注，青少年大脑认知发展（ABCD）研究和人类连接组项目 HCP-D和HCP-A，总共招募了数千人，其中许多是儿童 和青少年，并预计将跟踪他们长达十年。预见到需要一个无障碍的 ABCD数据分析和信息学中心（DAIC）是一个分析平台，旨在促进严格的建模， 开发并部署了基于Web的数据探索和分析门户（DEAP）。尽管它的新生 目前的DEAP版本已经提供了一个灵活的工具，可以满足两种数据的许多需求 科学家和应用研究者。在这里，我们建议产生一个更通用的DEAP扩展， 通过高级成像神经科学进行脑研究的数据探索和分析门户网站（DEAP- 大脑）。我们将通过整合以下方法来实现重要的新功能：i）包括HCP数据， 评估可推广性; ii）新开发的多顶点评分作为总结可推广性的方法 全脑模式;和iii）基于因果推理方法的偏差评估。在完成这项工作后， 建议，我们将通过提供研究社区，促进可重复和有效的科学发现 使用一个易于使用但复杂的信息学工具。该提案的具体目标是： 具体目标1：将HCP数据集成到DEAP-BRAIN中。我们将通过以下方式整合ABCD和HCP数据： 图像处理和变量约定。HCP成人队列和HCP寿命 发展队列将被纳入DEAP，允许对普遍性进行正式评估。 具体目标2：实施多顶点评分（PVS）作为评估可推广性的框架 大脑地图我们将实施我们新开发的PVS方法，这是一种创新的方法， 总结了大脑中关联模式的可重复性。 具体目标3：实施偏倚评估模块。我们将实施偏见评估模块 对于DEAP用户，基于因果推理原则，使用倾向分数，主成分方法， 和合成对照。

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.