NeuroScout: A cloud-based platform for flexible re-analysis of naturalistic fMRI datasets

项目摘要 在过去的二十年里，功能性磁共振成像（fMRI）的广泛引入 它彻底改变了健康和临床人群中人类大脑和认知功能的研究。然而 功能磁共振成像的潜在应用仍然受到其资源密集性的限制。因为即使很小， 探索性研究的成本很高，生物医学研究人员只能集体测试一小部分， 这是一小部分研究假设，原则上是服从功能磁共振成像研究。有一个 迫切需要新的方法学途径，能够快速和有效地测试新的 通过重新使用现有的fMRI数据集，而不是获取新的理论假设。以帮助实现 为了实现这一目标，我们提出了一个名为NeuroScout的新平台，该平台将支持快速灵活的基于云的 分析现有的功能性fMRI数据集。我们的方法与以前的基础设施有很大不同 项目中，而不是开发一个领域通用的神经成像平台，我们专注于提取 从有限的一组功能磁共振成像实验中获得最大的效用--也就是说， 三维刺激，如电影和音频叙事。建议的工作包括三个具体方面： 目标。目标1的重点是通过自动化大部分功能， 分析过程，并允许研究人员在云中轻松执行分析。目标2增加 通过开发高度可扩展的多模态刺激注释工具，实现分析灵活性。目标3 专注于通过将NeuroScout输出与现有数据共享整合来激励平台使用， 可视化和解释平台，如NeuroVault和Neurosynth。当完全部署时， NeuroScout平台将提供一个交钥匙解决方案，用于非常快速的分析和可视化， 现有的功能磁共振成像数据的边际成本非常接近于零。研究人员将能够反复测试和 完善从视觉文字识别到社会认知等领域的假设，并以交互方式 可视化并与更广泛的研究社区分享他们的结果。

Project Summary The widespread introduction of functional magnetic resonance imaging (fMRI) over the past two decades has revolutionized the study of human brain and cognitive function in healthy and clinical populations. Yet the potential utility of fMRI remains constrained by its resource-intensive nature. Because even small, exploratory studies are expensive to conduct, biomedical researchers can collectively test only a small fraction of the research hypotheses that are in principle amenable to fMRI investigation. There is an urgent need for novel methodological approaches that enable rapid and efficient testing of novel theoretical hypotheses by reusing existing fMRI datasets rather than acquiring new ones. To help achieve this goal, we propose a new platform called NeuroScout that will support rapid and flexible cloud-based analysis of existing functional fMRI datasets. Our approach differs importantly from previous infrastructure projects in that, rather than developing a domain-general neuroimaging platform, we focus on extracting maximum utility from a limited set of fMRI experiments--namely, those that use intrinsically high dimensional stimuli such as movies and audio narratives. The proposed work encompasses three Specific Aims. Aim 1 focuses on reducing the burden of re-analyzing existing fMRI by automating much of the analysis process and allowing researchers to easily execute their analyses in the cloud. Aim 2 increases analytical flexibility by developing highly extensible tools for multimodal stimulus annotation. Aim 3 focuses on incentivizing platform use by integrating NeuroScout outputs with existing data sharing, visualization and interpretation platforms such as NeuroVault and Neurosynth. When fully deployed, the NeuroScout platform will provide a turnkey solution for extremely rapid analysis and visualization of existing fMRI data at a marginal cost very close to zero. Researchers will be able to iteratively test and refine hypotheses in domains ranging from visual word recognition to social cognition, and interactively visualize and share their results with the broader research community at the push of a button.