NIDM-Results: Standardized reporting of mass univariate neuroimaging results in SPM, FSL and AFNI

Camille Maumet 1, * B. Nolan Nichols 2 Guillaume Flandin 3 Karl Helmer 4 Tibor Auer 5 Alexander Bowring 1 Vanessa Sochat 6 Samir Das 7 Tristan Glatard 7, 8, 9 Richard Reynolds 10 Robert Cox 10 Gang Chen 10 Mark Jenkinson 11 Matthew Webster 11 Jason Steffener 12 Krzysztof Gorgolewski 6 Jessica Turner 13 Thomas Nichols 14, 1 Satrajit Ghosh 15 Jean-Baptiste Poline 16 David Keator 17
* Corresponding author
1 WMG - Warwick Manufacturing Group [Coventry]
2 SRI - SRI International [Menlo Park]
3 Wellcome Trust Centre for Neuroimaging
4 Massachusetts General Hospital [Boston]
5 MRC CBU - Cognition and Brain Sciences Unit
6 Stanford University [Stanford]
7 Montreal Neurological Institute and Hospital
8 CREATIS - Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé
9 Images et Modèles
CREATIS - Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé
10 NIH - National Institutes of Health [Bethesda]
11 University of Oxford [Oxford]
12 Columbia University [New York]
13 Georgia State University
14 Department of Statistics [Warwick]
15 MIT - Massachusetts Institute of Technology
16 Henry H. Wheeler Jr. Brain Imaging Center, University of California at Berkeley
17 UCI - University of California [Irvine]
Abstract : Results of a neuroimaging study are usually shared through the publication of a scientific paper describing the experiment and analysis outcome. While hundreds of gigabytes of data are usually generated as part of an fMRI experiment, in the literature the authors typically report their results as a list of significant local maxima, i.e. locations in the brain defined in a standard space (e.g. MNI) that pass rigorous statistical testing. This practice is unsatisfactory in terms of data re-use as it does not allow for the automatic extraction of acquisition or processing information and it provides only sparse information about the location of the brain activity. While databases have been built to provide manually curated (such as BrainMap ​ [1]​) or automatically-extracted (e.g. NeuroSynth ​ [2]​) meta-data associated with published papers, ideally, these meta-data should be made available by the authors themselves at the time of the publication.
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https://www.hal.inserm.fr/inserm-01570626
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Camille Maumet, B. Nolan Nichols, Guillaume Flandin, Karl Helmer, Tibor Auer, et al.. NIDM-Results: Standardized reporting of mass univariate neuroimaging results in SPM, FSL and AFNI. 22nd Annual Meeting of the Organization for Human Brain Mapping (OHBM 2016), Jun 2016, Geneva, Switzerland. ⟨inserm-01570626⟩

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