CONN (functional connectivity toolbox)

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For other uses, see conn (disambiguation).
CONN
CONN (functional connectivity toolbox) examples.tif
CONN (functional connectivity toolbox)
Developer(s)The Gabrieli Lab. McGovern Institute for Brain Research. MIT
Stable release
2018
Operating systemMicrosoft Windows Linux Mac OS X
TypeNeuroimaging data analysis
LicenseMIT License
Websitewww.nitrc.org/projects/conn - NITRC
www.conn-toolbox.org - 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,[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[]

  1. ^ Whitfield-Gabrieli, S; Nieto-Castanon, A (2012). "Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks". Brain Connect. 2 (3): 125–41. doi:10.1089/brain.2012.0073. PMID 22642651.
  2. ^ Nieto-Castanon,A. (2020). Handbook of fcMRI methods in CONN. Boston, MA: Hilbert Press. ISBN 978-0-578-64400-4.
  3. ^ Behzadi, Y; Restom, K; Liau, J; Liu, TT (2007). "A component based noise correction method (CompCor) for BOLD and perfusion based fMRI". NeuroImage. 37 (1): 90–101. doi:10.1016/j.neuroimage.2007.04.042. PMC 2214855. PMID 17560126.
  4. ^ Power, JD; Barnes, KA; Snyder, AZ; Schlaggar, BL; Petersen, SE (2012). "Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion". NeuroImage. 59 (3): 2142–54. doi:10.1016/j.neuroimage.2011.10.018. PMC 3254728. PMID 22019881.
  5. ^ [1] CONN toolbox download stats
  6. ^ [2] google scholar
  7. ^ [3] NITRC top viewed tools and resources
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