1 University of Warwick, Coventry, UK.
2 McGill University, Montreal, Canada.
3 Montreal Neurological Institute, Montreal, Canada.
4 Institute of Neuroscience and Medicine (INM-1), Jülich Research Center, Jülich, Germany.
5 Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany.
6 Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada.
7 Otto-von-Guericke-University, Magdeburg, Germany.
8 Center for Behavioral Brain Sciences, Magdeburg, Germany.
9 MRC Cognition and Brain Sciences Unit, Cambridge, UK.
10 Child Mind Institute, New York, New York, USA.
11 Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York, USA.
12 Stanford University, Stanford, California, USA.
13 University of California, Berkeley, California, USA.
14 NEUROingenia Clinical and Research Center, Mexico City, Mexico.
15 Inria, Paris-Saclay University, Paris, France.
16 Washington University in St. Louis, St. Louis, Missouri, USA.
17 Erasmus University Medical Center, Rotterdam, The Netherlands.
18 National University of Singapore, Singapore.

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

Nat Neurosci. 2017 Feb 23;20(3):299-303

Authors: Nichols TE, Das S, Eickhoff SB, Evans AC, Glatard T, Hanke M, Kriegeskorte N, Milham MP, Poldrack RA, Poline JB, Proal E, Thirion B, Van Essen DC, White T, Yeo BT

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.

PMID: 28230846 [PubMed - indexed for MEDLINE]