Lessons learned: A neuroimaging research center's transition to open and reproducible science.

Lessons learned: A neuroimaging research center's transition to open and reproducible science.
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DOI:
10.3389/fdata.2022.988084
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发表时间:
2022
影响因子:
3.1
通讯作者:
Kilts, Clinton D.
Kilts, Clinton D.
中科院分区:
其他
文献类型:
--
作者:
Bush, Keith A.;Calvert, Maegan L.;Kilts, Clinton D.

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近年来,由于技术复杂性的增加和功能性神经影像学发现通常不可重现的新证据,人类功能性神经影像学发生了巨大的变化。为了应对这些趋势,神经影像科学家开发了原则,实践和工具来管理这种复杂性,并提高神经影像科学的严谨性和可重复性。我们将这些最佳实践分为四类:实验预注册,公平数据原则,可重复的神经成像分析和开放科学。虽然人们日益认识到有必要实施这些最佳做法,但在如何实现这一目标方面几乎没有实际指导。在这项工作中,我们描述了在阿肯色州大学医学科学脑成像研究中心4年(2018年7月至2022年5月)内采用这些最佳实践的经验教训。我们简要总结了四类最佳实践。然后,我们描述了我们中心的科学工作流程(从假设制定到结果报告),并详细说明了这个工作流程的每个元素如何映射到这四个类别。我们还提供了支持此映射过程的实践或工具的具体示例。最后,我们提供了逐步采用这些实践的路线图,提供了为什么和做什么的建议,以及每个过渡步骤的成本效益权衡总结。
Human functional neuroimaging has evolved dramatically in recent years, driven by increased technical complexity and emerging evidence that functional neuroimaging findings are not generally reproducible. In response to these trends, neuroimaging scientists have developed principles, practices, and tools to both manage this complexity as well as to enhance the rigor and reproducibility of neuroimaging science. We group these best practices under four categories: experiment pre-registration, FAIR data principles, reproducible neuroimaging analyses, and open science. While there is growing recognition of the need to implement these best practices there exists little practical guidance of how to accomplish this goal. In this work, we describe lessons learned from efforts to adopt these best practices within the Brain Imaging Research Center at the University of Arkansas for Medical Sciences over 4 years (July 2018–May 2022). We provide a brief summary of the four categories of best practices. We then describe our center's scientific workflow (from hypothesis formulation to result reporting) and detail how each element of this workflow maps onto these four categories. We also provide specific examples of practices or tools that support this mapping process. Finally, we offer a roadmap for the stepwise adoption of these practices, providing recommendations of why and what to do as well as a summary of cost-benefit tradeoffs for each step of the transition.
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