Everything Matters: The ReproNim Perspective on Reproducible Neuroimaging
- Kennedy, David N;
- Abraham, Sanu A;
- Bates, Julianna F;
- Crowley, Albert;
- Ghosh, Satrajit;
- Gillespie, Tom;
- Goncalves, Mathias;
- Grethe, Jeffrey S;
- Halchenko, Yaroslav O;
- Hanke, Michael;
- Haselgrove, Christian;
- Hodge, Steven M;
- Jarecka, Dorota;
- Kaczmarzyk, Jakub;
- Keator, David B;
- Meyer, Kyle;
- Martone, Maryann E;
- Padhy, Smruti;
- Poline, Jean-Baptiste;
- Preuss, Nina;
- Sincomb, Troy;
- Travers, Matt
- et al.
Published Web Location
https://www.frontiersin.org/articles/10.3389/fninf.2019.00001/fullAbstract
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.
Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.