Hi,

I read in a previous post an explanation why the FC between ROI 1 (seed) and ROI 2 (target) is different from ROI 2 (seed) and ROI 1 (target). However, in my matrix the correlation between the upper and lower triangle is .2, that seems very low, is that possible or is it more likely that I did something wrong?

What I did:
1) first level GLM for every subject
2) extract time series for all ROIs using VOI extract in SPM for every subject. Adjust for F-contrast and contrast of interest is the same F-contrast, no threshold
3) run the PPPI script for all ROIs for every subject
4) use the con image of the contrast of interest and get a mean value for all target ROIs for every subject using this function:
function ROI_data = Extract_ROI_Data_ppi2(ROI, Contrast)
Y = spm_read_vols(spm_vol(ROI),1);
indx = find(Y>0);
[x,y,z] = ind2sub(size(Y),indx);
XYZ = [x y z]';
ROI_data = nanmean(spm_get_data(Contrast, XYZ),2)
end

write that output in a 3d matrix (seed,target,subject)

5) get the mean values over subjects to make a connectivity plot
6) calculate the correlation with this code:

fc_l = [];fc_u = []; %lower and upper half of the diagonal of the matrix
for i=1:99 %100 ROIs
fc_l_i = FC_mean((i+1):100,i);
fc_l = [fc_l;fc_l_i]; %columns stacked, left lower half of the matrix
fc_u_i = FC_mean(i,(i+1):100);
fc_u = [fc_u,fc_u_i]; %rows next to each other, right upper half of the matrix
end
fc_u = fc_u.';
scatter(fc_u,fc_l)
[rho,pval]=corr(fc_u,fc_l)

Any thoughts on this are highly appreciated!
Selma