Graph Theory GLM (GTG) MATLAB Toolbox

This MATLAB toolbox calculates & runs a GLM on graph theory properties derived from brain networks. The GLM accepts continuous & categorical between-participant predictors & categorical within-participant predictors. Significance is determined via non-parametric permutation tests, including correction for multiple comparisons. Both fully connected & thresholded networks are tested.

The toolbox also provides a data processing path for resting state & task fMRI data. Options for partialing nuisance signals include: local & total white matter signal (Jo et al., 2013), PCA of white matter/ventricular signal (Muschelli et al., 2014), Saad et al. (2013)'s GCOR, & Chen et al. (2012)’s GNI. In addition, Power et al. (2014)'s motion scrubbing method & Patel et al. (2014)'s WaveletDespike are available.

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Specifications

Category:Connectivity Analysis
License:GNU General Public License (GPL)
Development Status:4 - Beta
Diagnosis:Brain Injuries
Domain:MR
Intended Audience:End Users
Natural Language:English
Operating System:OS Independent
Programming Language:MATLAB
Supported Data Format:NIfTI-1, Other Format
Other Keywords: graph, graph theoretic, graph theory, network

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RE: preprocessing  posted by Hannah Bohle 23 hours ago

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RE: preprocessing  posted by Jeff Peters on Jan 13

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RE: preprocessing  posted by Jeffrey Spielberg on Jan 11

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RE: preprocessing  posted by Hannah Bohle on Jan 11

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preprocessing  posted by Jeff Peters on Jan 9

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RE: Complete paths copied in some input variables posted by Jeffrey Spielberg on Oct 10, 2016

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RE: Complete paths copied in some input variables posted by Yacila Isabela Deza Araujo on Oct 10, 2016

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RE: Complete paths copied in some input variables posted by Jeffrey Spielberg on Oct 8, 2016

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RE: GTG for event-related design posted by Jeffrey Spielberg on Oct 6, 2016

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GTG for event-related design posted by Alex Rainer on Oct 6, 2016