Methods C-PAC has been implemented in Python using the Nipype pipelining library.
Nipype provides C-PAC with mechanisms to automatically detect and exploit parallelism
present in a pipeline, iterate over several parameter settings, and to restart a pipeline
without having to recompute previously completed processing steps. C-PAC extends Nipype
functionality by providing workflows specific to connectivity analyses, functional connectivity
derivatives and analyses not present in other neuroimaging packages, and a simplified …

Once a distant goal, discovery science for the human connectome is now a reality.
Researchers who previously struggled to obtain neuroimaging data from 20-30 participants
are now exploring the functional connectome using data acquired from thousands of
participants, made publicly available through the 1000 Functional Connectomes Project and
its International Neuroimaging Data-sharing Initiative (INDI). Beyond access to data,
scientists need access to appropriate tools to facilitate data exploration-particularly those …