NBS: NBS

In FCtools: Functional Connectivity Tools

NBS

Description

Network-based statistics analysis

Usage

NBS(model, contrast, FC_data, nperm = 100, nthread = 1, p = 0.001)

Arguments

model	A data.frame or matrix containing all the predictors in the model
contrast	The predictor of interest. The edge- and network-wise statistics will only be estimated for this predictor
FC_data	An N x E matrix containing the vectorized edges; where N = number of subjects, E=number of edges
nperm	The number of permutations to generate the null distribution of network strengths. Set to 100 by default
nthread	The number of CPU threads to use. Set to 1 by default
p	the edge-wise threshold. Set to 0.001 by default

Details

This function implements the NBS analysis described in Zalesky et al. (2010) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.neuroimage.2010.06.041")}

Value

A list object containing

• results Edge- and network-wise results in a data.frame object

• t.orig Edge-wise t-stats

• tcrit The critical t-value

• max.netstr A vector containing the null distribution of the permuted network strengths

Examples

demomat=get('demomat')[,1:7021] 
contrast=c(1,1,2,2)
random=c('sub1','sub2','sub3','sub4')
model1=NBS(model=contrast, 
           contrast=contrast, 
           FC_data=demomat, 
           nperm=2, 
           nthread=2, 
           p=0.001)

FCtools documentation built on Sept. 15, 2026, 5:09 p.m.