XCP-D : A Robust Postprocessing Pipeline of fMRI data

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Authors: Taylor Salo, Kahini P. Mehta, Azeez Adebimpe, Maxwell A. Bertolero, Kristin A. Murtha, Matthew Cieslak, Steven L. Meisler, Thomas J. Madison, Valerie J. Sydnor, Sydney C. Covitz, Roey Schurr, Damien A. Fair
+1 more Theodore Daniel Satterthwaite
Cited by: 0

Abstract

XCP-D paves the final section of the reproducible and scalable route from the MRI scanner to functional connectivity data in the hands of neuroscientists. We developed XCP-D to extend the BIDS and NiPrep apparatus to the point where data is most commonly consumed and analyzed by neuroscientists studying functional connectivity. Thus, with the development of XCP-D, data can be automatically preprocessed and analyzed in BIDS format, using NiPrep-style containerized code, all the way from the from the scanner to functional connectivity matrices.

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
6 January 2026