CONN (functional connectivity toolbox)
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 (functional connectivity toolbox) | |
Developer(s) | The Gabrieli Lab. McGovern Institute for Brain Research. MIT |
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Stable release | 2018
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Operating system | Microsoft Windows Linux Mac OS X |
Type | Neuroimaging data analysis |
License | MIT License |
Website | www www |
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,[2] elimination of subject-movement and physiological noise,[3] outlier scrubbing,[4] 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 Alfonso Nieto-Castanon. It has been supported by the Gabrieli Lab at MIT, Guenther Lab at Boston University, and PEN Lab at Northeastern University. 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 50,000 times to date,[5] it has been used in over 1,000 publications,[6] and it is included in the NIH funded Neuroimaging Informatics Tools and Resources Clearinghouse list of top-10 tools and resources in neuroimaging[7]
Download
CONN can be downloaded from its home page at the NITRC site, and user resources and support are provided at the CONN site and the CONN support forum
See also
References
- Whitfield-Gabrieli, S; Nieto-Castanon, A (2012). "Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks". Brain Connect. 2: 125–41. doi:10.1089/brain.2012.0073. PMID 22642651.
- Nieto-Castanon,A. (2020). Handbook of fcMRI methods in CONN. Boston, MA: Hilbert Press. ISBN 978-0-578-64400-4.
- Behzadi, Y; Restom, K; Liau, J; Liu, TT. "A component based noise correction method (CompCor) for BOLD and perfusion based fMRI". NeuroImage. 37: 90–101. doi:10.1016/j.neuroimage.2007.04.042. PMC 2214855. PMID 17560126.
- Power, JD; Barnes, KA; Snyder, AZ; Schlaggar, BL; Petersen, SE. "Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion". NeuroImage. 59: 2142–54. doi:10.1016/j.neuroimage.2011.10.018. PMC 3254728. PMID 22019881.
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