CONN (functional connectivity toolbox)

For other uses, see conn (disambiguation).
CONN

CONN (functional connectivity toolbox)
Developer(s) The Gabrieli Lab. McGovern Institute for Brain Research. MIT
Stable release
2015a
Operating system Microsoft Windows Linux Mac OS X
Type Neuroimaging data analysis
License MIT License
Website CONN

CONN is a Matlab-based cross-platform imaging software for the computation, display, and analysis of functional connectivity in fMRI (functional Magnetic Resonance Imaging) in the resting state and during task.

CONN is available as a SPM toolbox and it is freely available for non-commercial use.

Usage

CONN offers a user-friendly GUI to manage all aspects of functional connectivity analyses,[1] including preprocessing of functional and anatomical volumes, elimination of subject-movement and physiological noise,[2] outlier scrubbing,[3] estimation of multiple connectivity and network measures, and population-level hypothesis testing. In addition the processing pipeline can also be automated using batch scripts

History

CONN is written by members of the Gabrieli Lab at MIT. The first release of CONN was in 2011 and there has been approximately one major new release each year to date.

Impact

Since its release CONN has been downloaded over 20,000 times to date,[4] and it is included in the NIH funded Neuroimaging Informatics Tools and Resources Clearinghouse list of top-10 tools and resources in neuroimaging[5]

Download

CONN can be downloaded from its home page at the NITRC site, and user support is provided at the CONN support forum

See also

References

  1. ↑ Whitfield-Gabrieli, S., and Nieto-Castanon, A. (2012). Conn: A functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connectivity. doi:10.1089/brain.2012.0073
  2. ↑ Behzadi, Y., Restom, K., Liau, J. and Liu, T.T. (2007) A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. NeuroImage, 37: 90-101.
  3. ↑ Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage, 59(3), 2142–2154
  4. ↑ CONN toolbox download stats
  5. ↑ NITRC top viewed tools and resources
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