GIFTwrap: a containerized and FAIR cloud-based implementation of the widely used GIFT toolbox: Request for supplemental funds for NIH 2R01EB006841 “Multivariate methods for identifying multi-task/mult

GIFTwrap：广泛使用的 GIFT 工具箱的容器化和基于 FAIR 云的实现：请求 NIH 2R01EB006841 补充资金 – 用于识别多任务/多任务的多变量方法

• 批准号: 10406750
• 负责人: VINCE D CALHOUN
• 金额: $ 23.34万
• 依托单位: GEORGIA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-04-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10406750
• 关键词: Adopted; Algorithms; Architecture; Automation; Award; Big Data Methods; Brain imaging; Classification; Communities; Community Developments; Computer software; Data; Documentation; Entropy; Environment; FAIR principles; Functional Magnetic Resonance Imaging; Funding; Goals; Individual; Label; Methods; Modeling; Modernization; Morphologic artifacts; Movement; Noise; Parents; Phase; Publications; Pythons; Running; Signal Transduction; Software Tools; Training; United States National Institutes of Health; Update; Validation; Visualization; Visualization software; Work; algorithm development; base; cloud based; connectome; data fusion; data structure; falls; flexibility; imaging biomarker; multitask; response; software development; tool; vector; web based interface

Abstract The GIFT software was the first software tool to implement ICA of fMRI data and group ICA which has since been widely adopted by the brain imaging community. This tool has continuously expanded over the years, now providing access to a large suite of tools including data-driven functional connectivity, over a dozen different ICA approaches, independent vector analysis, dynamic functional connectivity, spatial dynamics, connectome visu- alization, and much more that are not offered in any other single tool. It also offers fully automated ICA ap- proaches for use in individual subject prediction and classification. Though we have begun to evolve the model, GIFT is primarily still based on a standalone software development and analysis model. Modern tools have moved towards centralized analysis, comparability, analytic interaction and community development. In this sup- plement we will focus on three main goals: 1) Building of architecture improvements to facilitate FAIR principles and modernize the tools, 2) to release the GIFT tools as a brain imaging data structure app (BIDSapp) for easy use and integration into modern analysis frameworks, and to deploy GIFT in several widely used analytic plat- forms, and 3) to provide a web-based interface for individuals to run fully automated ICA analysis which requires a simple upload of data to the tools. The result will have significant impact as it will offer a large expansion of utility for a tool which already has a large user base, will open up its use to many more in the community including those focused on big data tools and deployment within a modern containerized environment, and will facilitate automation, replication, cross-study comparisons, and robustness to processing pipelines and noise via spatially constrained ICA and automated labelling of intrinsic networks (beyond just artifact versus signal).

摘要 GIFT软件是第一个实现fMRI数据ICA和伊卡分组的软件工具， 被脑成像界广泛采用。多年来，该工具一直在不断扩展， 提供对一套大型工具的访问，包括数据驱动的功能连接，十几种不同的伊卡 方法，独立向量分析，动态功能连接，空间动力学，连接体可视化， 化，以及其他任何单一工具都无法提供的更多功能。它还提供完全自动化的伊卡AP- 用于个体主题预测和分类的方法。虽然我们已经开始改进模型， GIFT仍然主要基于独立的软件开发和分析模型。现代工具有 转向集中分析、可比性、分析互动和社区发展。在这个超级- 作为补充，我们将专注于三个主要目标：1）建立架构改进，以促进公平原则 并使工具现代化，2）将GIFT工具作为大脑成像数据结构应用程序（BIDSapp）发布， 使用并集成到现代分析框架中，并在几个广泛使用的分析平台中部署GIFT， 表格，以及3）为个人提供基于Web的界面，以运行完全自动化的伊卡分析， 一个简单的数据上传到工具。其结果将产生重大影响，因为它将提供一个大的扩展， 一个已经拥有庞大用户群的工具的实用程序，将向社区中的更多用户开放，包括 那些专注于大数据工具和现代容器化环境中的部署， 自动化，复制，交叉研究比较，以及通过空间处理管道和噪声的鲁棒性 约束伊卡和自动标记内在网络（不仅仅是伪影与信号）。