Dear Stephen,

Thanks a lot for sharing the scripts.

I'm a bit puzzles though about how to interpret the outcomes. If I understood correctly the scripts compare the BETA maps per source, between two different conditions (here pre and post treatment). If outputs the pvalues maps, the FDR pvalue corrected maps and thresholds the BETA difference maps based on the FDR corr pvalue (and even splits these into positive and negative difference maps).

Let me update you on my situation here.

I'm investigating a single case study by exploring a patient's functional connectivity patterns before and after treatment (i have two pre and two post treatment resting state scans).

I ran part of the preprocessing outside conn (yet using SPM tools) as I wanted to include denoising using ICA-AROMA, and prewhitening of the data (removing the autocorrelation between the scans). I then denoised the data further using the regression steps (for motion and white/CSF matter) in CONN and then ran the first level analysis (correlation).

Now I implemented your script for comparing (for example) the BETAs of pre 1 and pre 2. Inspection of the pFDR_thresholded_corr_* maps (doesn't matter which source) shows significant differences basically everywhere in the brain (see also Figure 1 attached). Indeed, when inspecting BETA differences maps thresholded based on these pvalues, I see significant differences in BETA patched all over the brain (see also Figure 2). I'm very new to this, but to me this seems very very unlikely, or??

Yet, if these maps are indeed correct, how should I interpret them? It hard to imagine that for each source I find differences between the pre1 and pre2 condition? Can you advice on some strategy to adopt to get from these patched difference maps to something more inclusive?

In case these maps are incorrect, any idea what could have gone wrong???

Thanks a lot in advance!