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Everything Matters: The ReproNim Perspective on Reproducible Neuroimaging

Authors :
David N. Kennedy
Sanu A. Abraham
Julianna F. Bates
Albert Crowley
Satrajit Ghosh
Tom Gillespie
Mathias Goncalves
Jeffrey S. Grethe
Yaroslav O. Halchenko
Michael Hanke
Christian Haselgrove
Steven M. Hodge
Dorota Jarecka
Jakub Kaczmarzyk
David B. Keator
Kyle Meyer
Maryann E. Martone
Smruti Padhy
Jean-Baptiste Poline
Nina Preuss
Troy Sincomb
Matt Travers
Source :
Frontiers in Neuroinformatics, Vol 13 (2019)
Publication Year :
2019
Publisher :
Frontiers Media S.A., 2019.

Abstract

There has been a recent major upsurge in the concerns about reproducibility in many areas of science. Within the neuroimaging domain, one approach is to promote reproducibility is to target the re-executability of the publication. The information supporting such re-executability can enable the detailed examination of how an initial finding generalizes across changes in the processing approach, and sampled population, in a controlled scientific fashion. ReproNim: A Center for Reproducible Neuroimaging Computation is a recently funded initiative that seeks to facilitate the “last mile” implementations of core re-executability tools in order to reduce the accessibility barrier and increase adoption of standards and best practices at the neuroimaging research laboratory level. In this report, we summarize the overall approach and tools we have developed in this domain.

Details

Language :
English
ISSN :
16625196
Volume :
13
Database :
Directory of Open Access Journals
Journal :
Frontiers in Neuroinformatics
Publication Type :
Academic Journal
Accession number :
edsdoj.86b8f0329234929a4b516ca8ce35226
Document Type :
article
Full Text :
https://doi.org/10.3389/fninf.2019.00001