Yes I think that's it.
Cheers.

> On 22 Nov 2016, at 04:20, Harms, Michael <[email protected]> wrote:
> 
> 
> Isn’t it more like (data/4DMean*10000), so that the percentage change 
> relative to the mean is preserved?
> 
> cheers,
> -MH
> 
> -- 
> Michael Harms, Ph.D.
> -----------------------------------------------------------
> Conte Center for the Neuroscience of Mental Disorders
> Washington University School of Medicine
> Department of Psychiatry, Box 8134
> 660 South Euclid Ave.  Tel: 314-747-6173
> St. Louis, MO  63110  Email: [email protected]
> 
> From: <[email protected] 
> <mailto:[email protected]>> on behalf of "Glasser, 
> Matthew" <[email protected] <mailto:[email protected]>>
> Date: Monday, November 21, 2016 at 9:53 PM
> To: mali s <[email protected] <mailto:[email protected]>>, 
> NEUROSCIENCE tim <[email protected] <mailto:[email protected]>>
> Cc: "[email protected] <mailto:[email protected]>" 
> <[email protected] <mailto:[email protected]>>
> Subject: Re: [HCP-Users] 4D Intensity normalization in the fMRIVolume pipeline
> 
> We didn’t do global signal regression or mean stabilization if that is what 
> you are wondering about.  The formula is essentially (data – 4DMean) + 10000.
> 
> Peace,
> 
> Matt.
> 
> From: mali s <[email protected] <mailto:[email protected]>>
> Date: Monday, November 21, 2016 at 9:49 PM
> To: Timothy Coalson <[email protected] <mailto:[email protected]>>
> Cc: Matt Glasser <[email protected] <mailto:[email protected]>>, 
> "[email protected] <mailto:[email protected]>" 
> <[email protected] <mailto:[email protected]>>
> Subject: Re: [HCP-Users] 4D Intensity normalization in the fMRIVolume pipeline
> 
> We are doing connectivity analysis on this data, and it is important for us 
> to understand the exact formula used to convert to the intensity normalized 
> image. It would really help if you can share this or guide me to a link where 
> I can find the details.
> 
> To put it precisely, let's say I have r(x,y,z,t) after all the preprocessing 
> steps, and just before the intensity normalization. What is the formula used 
> to convert this to the intensity normalized image n(x,y,z,t) ?
> 
> Regards,
> Mali
> 
> 
> On Tue, Nov 22, 2016 at 8:44 AM, Timothy Coalson <[email protected] 
> <mailto:[email protected]>> wrote:
>> Yes, because the 3d volume means were already close to each other even 
>> before any normalization.
>> 
>> Tim
>> 
>> 
>> On Mon, Nov 21, 2016 at 8:56 PM, mali s <[email protected] 
>> <mailto:[email protected]>> wrote:
>>> Thank you the replies!
>>> Tim, I think I understand your explanation. In mathematical terms, it means 
>>> 4d mean is close to each of the 3d volume means, right?
>>> I'm guessing "PFA" means "please find attached".
>>> BOLD scans have a lot of structural signal in them, which we haven't 
>>> subtracted out - the activation-related signal is a modest local 
>>> fluctuation compared to this base signal level.  Additionally, since you 
>>> are averaging over the entire brain mask, the activation signals get 
>>> considerably diluted by white matter, and by gray matter that isn't 
>>> similarly active at that timepoint.
>>> Tim
>>> I'm guessing "PFA" means "please find attached".
>>> BOLD scans have a lot of structural signal in them, which we haven't 
>>> subtracted out - the activation-related signal is a modest local 
>>> fluctuation compared to this base signal level.  Additionally, since you 
>>> are averaging over the entire brain mask, the activation signals get 
>>> considerably diluted by white matter, and by gray matter that isn't 
>>> similarly active at that timepoint.
>>> Tim
>>> I'm guessing "PFA" means "please find attached".
>>> 
>>> BOLD scans have a lot of structural signal in them, which we haven't 
>>> subtracted out - the activation-related signal is a modest local 
>>> fluctuation compared to this base signal level.  Additionally, since you 
>>> are averaging over the entire brain mask, the activation signals get 
>>> considerably diluted by white matter, and by gray matter that isn't 
>>> similarly active at that timepoint.
>>> 
>>> Tim
>>> 
>>> 
>>> On Mon, Nov 21, 2016 at 8:14 PM, Glasser, Matthew <[email protected] 
>>> <mailto:[email protected]>> wrote:
>>>> I don’t know what PFA is and am otherwise having some trouble following 
>>>> your question.  There is grand mean intensity normalization to 10000, 
>>>> meaning that the entire 4D image inside the brain mask has a mean of 10000.
>>>> 
>>>> Peace,
>>>> 
>>>> Matt.
>>>> 
>>>> From: <[email protected] 
>>>> <mailto:[email protected]>> on behalf of mali s 
>>>> <[email protected] <mailto:[email protected]>>
>>>> Date: Monday, November 21, 2016 at 8:08 PM
>>>> To: "[email protected] <mailto:[email protected]>" 
>>>> <[email protected] <mailto:[email protected]>>
>>>> Subject: [HCP-Users] 4D Intensity normalization in the fMRIVolume pipeline
>>>> 
>>>> Dear HCP team,
>>>> 
>>>> We are using minimally preprocessed volume files from HCP database 
>>>> (100206/MNINonLinear/Results/tfMRI_MOTOR_LR/tfMRI_MOTOR_LR.nii). The 
>>>> release notes for this subject say these files were processed using v3+ of 
>>>> the pipeline. I believe 4d intensity normalization to mean of 10^4 is 
>>>> being done here. 
>>>> 
>>>> However, PFA the mean brain activation (after applying mask) during the 
>>>> course of the scan . They are all close to 10^4,  more like a global 
>>>> signal normalization for every 3d volume.
>>>> 
>>>> I am having trouble reconciling both. Thanks in advance for the help.
>>>> 
>>>> Regards,
>>>> Mali
>>>> 
>>>> 
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> 
> 
> 
> -- 
> Mali Sundaresan
> 
>  
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