Hello all! 

I am doing some research related to task-based connectivity. We are using CONN's implementation of gPPI, and then performing GLM analysis to compare connectivity across participants between tasks. I've noticed that no matter what region I use as a seed and search for any effects (F-test, contrast 1,0;0,1;) between tasks, there is a huge cluster that is called significant by the GLM analysis that includes that region. It also often includes the other regions in the network containing the selected seed. 

For instance, in the attached file, we use the ACC within the salience network as a seed, and the results include a large cluster that combines the ACC with the rest of the salience network. 

I have a few questions about this that partially relate to my general unfamiliarity with the mathematics behind GLMs:

• Should we expect this to happen every time? (If not, am I using the model incorrectly?)


• Why does this happen / what does it mean for the connectivity of a seed region to vary with itself between tasks?

Please let me know if you need any more information to help—any information would be appreciated, as I've been thinking about this issue for multiple weeks.