Best Practices in Data Analysis and Sharing in Neuroimaging using MRI

Abstract : Neuroimaging enables rich noninvasive measurements of human brain activity, but translating such data into neuroscientific insights and clinical applications requires complex analyses and collaboration among a diverse array of researchers. The open science movement is reshaping scientific culture and addressing the challenges of transparency and reproducibility of research. To advance open science in neuroimaging the Organization for Human Brain Mapping created the Committee on Best Practice in Data Analysis and Sharing (COBIDAS), charged with creating a report that collects best practice recommendations from experts and the entire brain imaging community. The purpose of this work is to elaborate the principles of open and reproducible research for neuroimaging using Magnetic Resonance Imaging (MRI), and then distill these principles to specific research practices. Many elements of a study are so varied that practice cannot be prescribed, but for these areas we detail the information that must be reported to fully understand and potentially replicate a study. For other elements of a study, like statistical modelling where specific poor practices can be identified, and the emerging areas of data sharing and reproducibility, we detail both good practice and reporting standards. For each of seven areas of a study we provide tabular listing of over 100 items to help plan, execute, report and share research in the most transparent fashion. Whether for individual scientists, or for editors and reviewers, we hope these guidelines serve as a benchmark, to raise the standards of practice and reporting in neuroimaging using MRI.
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Submitted on : Friday, August 25, 2017 - 2:17:59 PM
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Thomas Nichols​, Samir Das​, Simon B. Eickhoff​ 3​, Alan Evans​, Tristan Glatard​, et al.. Best Practices in Data Analysis and Sharing in Neuroimaging using MRI. Nature Neuroscience, Nature Publishing Group, 2017, 20, pp.299-303. ⟨10.1038/nn.4500⟩. ⟨hal-01577319⟩

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