Hi Andrew, 

I ran some graph theory analyses prior to using NBS and the results showed case-control differences in quite a few brain regions (mostly cases having lower values, such as lower nodal efficiency, than controls) after controlling for nuisance covariates like age, sex and site. I then tried using NBS to identify subnetworks, with the expectation that I will find significant subnetworks involving the same regions identified in the graph theory analyses. I used a two-sample t-test with the contrast [-1 1 0 0 0] - the first column for cases, second column for controls, third column for age and fourth column for site. However, there were no significant subnetworks over a range of primary thresholds (p<0.001 to p<0.05) for both extent and intensity. I also tried using the FDR option with 50,000 permutations but likewise, no significant differences were found. Significant subnetworks were identified if I do not control for the nuisance covariates but I do think it is necessary to add them in.

I am a bit puzzled by the results because there were differences at the nodal level and it would make sense to see differences at the connection level. What do you think? I know this is not directly related to NBS methodology, but it would be really great if I can get your opinion on this. 

Thank you very much!

Best Regards
GT