MIT/X Consortium License Yes Child Mind Institute, Nathan Kline Institute, NYU Langone Medical Center NITRC C-PAC MacOS, POSIX/UNIX-like Yes Python Michael Milham The Configurable Pipeline for the Analysis of Connectomes (C-PAC) is a configurable, open-source, Nipype-based, automated processing pipeline for resting state functional MRI (R-fMRI) data, for use by both novice and expert users. C-PAC was designed to bring the power, flexibility and elegance of the Nipype platform to users in a plug and play fashion—without requiring the ability to program. Using an easy to read, text-editable configuration file, C-PAC can rapidly orchestrate automated R-fMRI processing procedures, including: - quality assurance measurements - image preprocessing based upon user specified preferences - generation of functional connectivity maps (e.g., correlation analyses) - customizable extraction of time-series data - generation of local R-fMRI metrics (e.g., regional homogeneity, voxel-matched homotopic connectivity, fALFF/ALFF) C-PAC makes it possible to use a single configuration file to launch a factorial number of pipelines differing with respect to specific processing steps. 2015-4-03 3 - Alpha v0.3.9 2013-9-04 3 - Alpha Benchmark C-PAC Connectivity Analysis, Workflow, 3 - Alpha, Child Development Disorders, Pervasive, MR, Computational Neuroscience, BRAIN Initiative, Developers, End Users, MIT/X Consortium License, English, MacOS, POSIX/UNIX-like, NiPyPe, Python, NIfTI-1 http://www.nitrc.org/projects/cpac/, http://http://fcp-indi.github.io noreply+milham01-at-med.nyu.edu@nitrc.org