Right, that approach to get the data separately for each condition is perfectly fine as well for longitudinal resting-state conditions each spanning an entire functional run.

Best

Alfonso

Originally posted by kiana orangi:

I have a problem using CONN, which I could not figure out by reading the Forums. I would appreciate it if anyone could help me.

In our study, each participant underwent two resting-state fMRIs: once when sleep-deprived and once with full sleep. We wanted to extract the denoised time series from CONN to perform DCM in SPM.
I specified two conditions (sleep dep/full sleep) based on this blog (for pre/post design here (https://andysbrainbook.readthedocs.io/en...)). (https://andysbrainbook.readthedocs.io/en...) But the "data" time series in results/preprocessing/ROI_Subject*_Condition001 and ROI_Subject*_Condition002 are the same!
I read in forums, that we can have condition-specific time series with running 
"w = max(0,conditionweights{1});
idx = find( w>0 );
data_reduced = cellfun(@(x)x(idx,:), data, 'uni',0);
w_reduced = w(idx);"

But I am not sure this is okay in my case since I have resting state data. Could you please share your thoughts with me?

Best wishes and thank you for your time,