Hi all,

I am exploring the functions of CONN toolbox using a dataset and trying to undertstand the interpretation of the cluster-level and roi-level inferences results.

Just as an example, consider the following study:
gPPI (regression)
3 groups
4 within-subjects conditions
36 ROIs manually organized in 4 groups (a-priori)


I am trying to check group differences:
Between subjects contrast: any difference
Within subjects contrast: average


I am just testing the results explorer and trying to understand how to interpret the results, so I am using very liberal thresholds.
Connection threshold: 0.05 (uncorrected)
Cluster Theshold: 0.05 (uncorrected, SPC mass intensity)


The results give me 3 clusters, each cluster made of several connections.
Plot https://i.imgur.com/Gd8EtKi.png
Table https://i.imgur.com/cyqivxG.png

How do I interpret this results?

There are three different clusters of ROI-to-ROI connections on which the gPPI differs between groups?
Why are three different clusters ? The difference between groups is different between those clusters? Different profiles ?
Do I need to do post-hoc to know more about that?






Regarding the ROI-level inference the question is: does the multiple comparisons correction considers the direction of the connection ?
How can we interprete the results ? With the direction information or just describing the ROIs involved without any reference about directionality ?

Plot https://i.imgur.com/SHJCpUW.png
Table https://i.imgur.com/LbzpUmN.png



Thank you.
Ricardo