Hello, 

I’m planning to deconvolve our data before running gPPI and second-level analyses in CONN, based on the method described in the paper “Comparison of whole-brain task-modulated functional connectivity methods for fMRI task connectomics” doi: https://doi.org/10.1038/s42003-024-07088-3 (https://static-content.springer.com/esm/...), and I wanted to check if this approach makes sense and if it is feasible to do it in Conn.

Here's what I was thinking:

1. My data is preprocessed using fMRIPrep.
   
2. Do spatial smoothing and denoising in CONN, after setting "acquisition type" to “sparse” in the Setup.Basic tab as suggested https://www.nitrc.org/forum/message.php?... Click or tap if you trust this link." href="https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nitrc.org%2Fforum%2Fmessage.php%3Fmsg_id%3D15733&data=05%7C02%7Ckapiln%40wustl.edu%7C56e4eb390fb140ffe50808dd89771793%7C4ccca3b571cd4e6d974b4d9beb96c6d6%7C0%7C0%7C638817866767566745%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=b6WpXfSRzZ8ZWOPM%2B3lTF1RluRvoY0mARW6bmfmip6s%3D&reserved=0" target="_blank" rel="noopener noreferrer" data-auth="NotApplicable" data-linkindex="0">here, so the design matrix isn’t convolved with the hrf.
   

• Run a gPPI analysis in CONN to create the appropriate files & structure, but we will later overwrite its results

3. Use the denoised timeseries from conn*/results/preprocessing/ROI_Subject*_Condition*.mat.
   
4. Deconvolve those timeseries using spm_peb_ppi.m function.
   
5. Then reconvolve the interaction term or PPI regregressors using CONN. 
   

Now the question is how/whether we can have CONN do the gPPI calculations before we reconvolve with the canonical hrf meaning which files we need to replace to allow CONN to use that data.