Network-Based Statistic (NBS)

Matlab toolbox for testing hypotheses about the human connectome. NBS has been widely used to identify connections and networks comprising the connectome that are associated with an experimental effect or a between-group difference. User provides a series of connectivity matrices from different cohorts, or from the same subject during different experimental conditions. Connectivity matrices are inferred from neuroimaging data using other packages that, for example, count the number of tractography streamlines that interconnect each pair of regions (diffusion-MRI), or measure the extent of inter-regional correlation in BOLD response (fMRI). User specifies hypothesis to be tested at every connection with the general linear model. Features include: graphical user interface; NBSview, a basic network viewer modeled on SPMresults; exchange blocks for repeated measures; options to measure network size with intensity or extent; false discovery rate (FDR) option. Developed by Zalesky, Fornito, Cocchi and Bullmore.
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RE: F test for a two-tailed t test posted by Alejandro Cosa on Feb 16

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RE: F test for a two-tailed t test posted by Andrew Zalesky on Feb 15

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F test for a two-tailed t test posted by Alejandro Cosa on Feb 15

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RE: List of connectivity strengths posted by Andrew Zalesky on Feb 13

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RE: List of connectivity strengths posted by gmcphilemy on Feb 13

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RE: Diagnosis covariate and interaction  posted by Andrew Zalesky on Jan 24

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Diagnosis covariate and interaction  posted by gmcphilemy on Jan 24

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RE: Design matrix posted by Andrew Zalesky on Dec 19, 2017

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RE: Design matrix posted by Alexia Bourgeois on Dec 19, 2017

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RE: ANCOVA rank deficient posted by Juan Pablo Princich on Dec 18, 2017