Sharing brain mapping statistical results with the neuroimaging data model

Camille Maumet, Tibor Auer, Alexander Bowring, Gang Chen, Samir Das, Guillaume Flandin, Satrajit Ghosh, Tristan Glatard, Krzysztof J. Gorgolewski, Karl G. Helmer, Mark Jenkinson, David B. Keator, B. Nolan Nichols, Jean Baptiste Poline, Richard Reynolds, Vanessa Sochat, Jessica Turner, Thomas E. Nichols

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

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 format specification 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 standardized representation allows authors to relay methods and results in a platform-independent regularized 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.

Original languageEnglish
Article number160102
JournalScientific Data
Volume3
DOIs
Publication statusPublished - 6 Dec 2016

ASJC Scopus subject areas

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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