Open-source tools and platforms to investigate analytical variability in neuroimaging

作者: Jacob Sanz-Robinson , Michelle Wang , Brent McPherson , Tristan Glatard , Jean-Baptiste Poline

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摘要: Analytical variability often undermines the reproducibility of neuroimaging studies. Researchers have access to a multitude of analysis tools, many of which carry out the same tasks but yield different results when applied to the same data. The array of tools to investigate and address analytical variability is decentralized and scattered. Consequently, researchers often lack the necessary information and protocols to buttress the reliability of their findings across analysis tools. This review catalogs and describes software tools that can be used to address result variability arising from computational pipelines and environments, and explores the use of web computing platforms and data provenance in tackling this issue. The aim is to aid researchers in investigating analytical flexibility by identifying relevant tools and providing guidance on their utilization to enhance accessibility and comprehension. In this article, we use the term “tools” for software or computational libraries.

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