The field of functional neuroimaging has substantially advanced as a big data science in the past decade, thanks to international collaborative projects and community efforts. Here we conducted a literature review on functional neuroimaging, with focus on three general challenges in big data tasks: data collection and sharing, data infrastructure construction, and data analysis methods. The review covers a wide range of literature types including perspectives, database descriptions, methodology developments, and technical details. We show how each of the challenges was proposed and addressed, and how these solutions formed the three core foundations for the functional neuroimaging as a big data science and helped to build the current data-rich and data-driven community. Furthermore, based on our review of recent literature on the upcoming challenges and opportunities toward future scientific discoveries, we envisioned that the functional neuroimaging community needs to advance from the current foundations to better data integration infrastructure, methodology development toward improved learning capability, and multi-discipline translational research framework for this new era of big data.
在本篇综述中，我们回顾了近十余年来数据科学在神经影像学，特别是功能神经影像的分析中愈发广泛的应用与发展，并在总结了过往文献中涉及的神经影像大数据研究的三个重点任务：数据收集，数据分析与数据信息学。基于这三个重点任务，本文对当前公开的功能神经影像数据库，计算机分析算法以及影像学常用数据库平台进行了汇总。本文进一步提出了未来功能神经影像学作为一门数据科学的发展方向，即功能神经影像学与转化医学的深度结合，功能神经影像学数据整合和体系化建设，以及对应的知识发掘策略和学习系统的发展。





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