That is correct.

I would apply ICA+FIX and this is something we hope to do with the HCP data as 
time allows.  We have a modified ICA+FIX pipeline that enables correcting 
multiple runs at the same time (ICA+FIX doesn’t work as well on the very short 
task fMRI runs).  ICA+FIX removes a linear trend.  If you will be parcellating 
before fitting the GLM there is no reason to smooth the data.  Also temporal 
filtering above and beyond ICA+FIX is not clearly beneficial.

Peace,

Matt.

From: 
<hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>>
 on behalf of "Poppe, Andrew" 
<andrew.po...@hhchealth.org<mailto:andrew.po...@hhchealth.org>>
Date: Wednesday, November 15, 2017 at 2:32 PM
To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" 
<hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>>
Subject: [HCP-Users] Questions about Connectome in a Box

Hello,

I just wanted to check some assumptions I had about what has been done to the 
data in the connectome in a box 1200 subject release. I apologize if this 
information is readily available someplace.

Specifically, for files in the preproc directory (e.g., 
320826/preproc/320826/MNINonLinear/Results/tfMRI_EMOTION_LR/tfMRI_EMOTION_LR_Atlas_MSMAll.dtseries.nii),
 is the following accurate?


-          No ICA+FIX has been applied

-          No spatial smoothing applied

-          No temporal filtering applied

If all of that is true, and if my intention is to parcellate those data, would 
you recommend applying any of those steps? And if so, should temporal filtering 
be applied prior to parcellation (I assume smoothing is unnecessary if 
parcellating).

Thanks for any help you can offer!

-Andrew

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