@article {Maumet041798, author = {Camille Maumet and Tibor Auer and Alexander Bowring and Gang Chen and Samir Das and Guillaume Flandin and Satrajit Ghosh and Tristan Glatard and Krzysztof J. Gorgolewski and Karl G. Helmer and Mark Jenkinson and David B. Keator and B. Nolan Nichols and Jean-Baptiste Poline and Richard Reynolds and Vanessa Sochat and Jessica Turner and Thomas E. Nichols}, title = {NIDM-Results: a Neuroimaging Data Model to share brain mapping statistical results}, elocation-id = {041798}, year = {2016}, doi = {10.1101/041798}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Only a tiny fraction of the data and metadata produced by an fMRI study is finally conveyed to the community. This lack of transparency not only hinders the reproducibility of neuroimaging results but also impairs future meta-analyses. In this work we introduce NIDM-Results, a standard providing a machine-readable description of neuroimaging statistical results along with key image data summarising the experiment. NIDM-Results provides a unified representation of mass univariate analyses including a level of detail consistent with available best practices. This standard allows authors to relay methods and results in a standard format that is not tied to a particular neuroimaging software package. Tools are available to export NIDM-Result graphs and associated files from the widely used SPM and FSL software packages, and the NeuroVault repository can import NIDM-Results archives. The specification is publically available at: http://nidm.nidash.org/specs/nidm-results.html.}, URL = {https://www.biorxiv.org/content/early/2016/07/18/041798}, eprint = {https://www.biorxiv.org/content/early/2016/07/18/041798.full.pdf}, journal = {bioRxiv} }