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Provides a set of python scripts for deriving a whole brain parcellation of functional magnetic resonance imaging (fMRI) data. The resulting regions are suitable for use as regions of interest (ROIs) in fMRI data analysis. The pyClusterROI method employs a spatially-constrained normalized-cut spectral clustering algorithm to generate individual-level and group-level parcellations. The spatial constraint is imposed to ensure that the resulting ROIs are spatially coherent, i.e. the voxels in the resulting ROIs are connected. Using this package, clustering can be performed based on either the temporal correlation between voxel time courses, the spatial correlation between whole brain functional connectivity maps generated from each voxel time course, or a by spatial distance.

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pyClusterROI classification

pyClusterROI specifications

Software type:
Restrictions to use:
Programming languages:
Computer skills:
NiBabel, NumPy, SciPy
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
GNU General Public License version 3.0

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pyClusterROI support



  • Cameron Craddock <>


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Funding source(s)

This work was supported by P50 MH077083 (HSM), R01 MH073719 (HSM), NIH R01 EB002009 (XPH), K23 MH077869 (PEH), and a NARSAD Young Investigator Award (PEH).

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