使用磁共振成像(MRI)进行神经成像数据分析与共享的最佳实践。

Best practices in data analysis and sharing in neuroimaging using MRI.

作者信息

Nichols Thomas E, Das Samir, Eickhoff Simon B, Evans Alan C, Glatard Tristan, Hanke Michael, Kriegeskorte Nikolaus, Milham Michael P, Poldrack Russell A, Poline Jean-Baptiste, Proal Erika, Thirion Bertrand, Van Essen David C, White Tonya, Yeo B T Thomas

机构信息

University of Warwick, Coventry, UK.

McGill University, Montreal, Canada.

出版信息

Nat Neurosci. 2017 Feb 23;20(3):299-303. doi: 10.1038/nn.4500.

Abstract

Given concerns about the reproducibility of scientific findings, neuroimaging must define best practices for data analysis, results reporting, and algorithm and data sharing to promote transparency, reliability and collaboration. We describe insights from developing a set of recommendations on behalf of the Organization for Human Brain Mapping and identify barriers that impede these practices, including how the discipline must change to fully exploit the potential of the world's neuroimaging data.

摘要

鉴于对科学发现可重复性的担忧,神经影像学必须定义数据分析、结果报告以及算法和数据共享的最佳实践,以促进透明度、可靠性和协作。我们阐述了代表人类脑图谱组织制定一套建议过程中的见解,并识别出阻碍这些实践的障碍,包括该学科必须如何变革才能充分挖掘全球神经影像学数据的潜力。

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