I don't understand how you are computing the mean.  The mean across the entire 
4D dataset inside the brain mask will be 10000.

Peace,

Matt.

From: 
<[email protected]<mailto:[email protected]>>
 on behalf of Chao Zhang <[email protected]<mailto:[email protected]>>
Date: Monday, July 11, 2016 at 4:42 PM
To: "[email protected]<mailto:[email protected]>" 
<[email protected]<mailto:[email protected]>>
Subject: [HCP-Users] fMRI time series intensity normalization

Hi,

I am using the FIX fMRI dataset. However I have a question about the time 
series preprocessing:

Step 6 in fMRIVolume pipeline said that '6. Intensity normalization to mean of 
10000 (like in FEAT) and bias field removal. Brain mask based on FreeSurfer 
segmentation.'. But the mean values are not 10000, e.g. I checked one subject 
for which the mean ranges from -115 to 27000.

So this becomes an issue when deriving the ROI/regional time series, what I did 
was first convert to z-score for each time series and then calculate the 
average across time series within the ROI.

I came to recognize that this may not be correct. Another idea is to keep all 
original data and do the average within the ROIs. However, if one ROI is very 
big, then the large difference of the baselines (the mean values) of different 
voxels may make this choice not valid.

I wonder why the the mean value is not actually 10000 and what is the correct 
way to derive the ROI time series. Thanks very much,

Best,
Chao

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