Sorry for the flurry of posts, but I solved one of the issues listed below. For the percent
signal change calculations, I placed the re-scaled copes/varcopes in the first level
directory subjectN.feat/reg_standard/pctsig/ for each subject and used the copefiles there
as inputs. However, I noticed from the log file that when flame12 runs, it grabs the
lower level copes from subjectN.feat/reg_standard/stats/ which explains the identical
results. Kind of a tough bug to catch since I listed the files explicitly as coming from my
"pctsig" directory.
On Wed, 13 May 2009 18:12:12 +0100, Patrick Purdon
<[log in to unmask]> wrote:
>Hi David,
>
>Thanks for sending along that link, I think I understand all that, I'm trying to answer
>slightly different questions that aren't addressed by the standard 4D global
normalization.
>In particular, 1) I'd like to compare activity changes between drug levels in terms of
>percent signal changes (where the percentage is computed relative to the local voxel
>mean for each run), and 2) I would also like to use flame12 to detect any region-
specific
>changes in mean BOLD signal.
>
>I tried a work around for (1) where I scaled the first level copes by 100/(mean_func)
and
>varcopes by (100/mean_func)^2, but for some reason that gave identical results to the
>unscaled case (is there some scaling/normalization that happens when copes are passed
>up to 2nd level?), and for (2) I'm wondering if there's an easy way to get a mean BOLD
>image and its variance from the standard FSL output (I know how I'd do this from
scratch,
>but am hoping there's a way to get it for free from what FSL already computes).
>
>Any ideas FSL experts? Thanks for your help!
>
>--P
>
>PS-- In case it isn't clear, when I scaled the first level copes to "convert" them to
percent
>signal change units, what I did was:
>
>scaled_cope(x,y,z) = 100*cope(x,y,z)/mean_func(x,y,z);
>
>(the reason I did this is so that the resulting 2nd level pe's and copes would be in terms
>of percentage signal changes)
>
>
>On Tue, 12 May 2009 21:22:50 -0400, David V. Smith <[log in to unmask]>
>wrote:
>
>>Hi Patrick,
>>
>>Somebody will probably have to correct me on this, but I don't think you
>>really need to do any normalization here for two reasons. In fact, depending
>>on how you do it, normalizing may create spurious deactivations in your data
>>(see Laurienti, 2004, JoCN).
>>
>>1) I think only relative changes matter, so the mean intensity shouldn't
>>affect your stats
>>
>>2) All of the data are scaled to a preset mean. You can see some of the FSL
>>course slides for more info on this.
>>http://www.fmrib.ox.ac.uk/fslcourse/lectures/feat1_part1.pdf
>>
>>Hopefully I'm not steering you in the wrong direction. I defer to the
>>experts on this one...
>>
>>Cheers,
>>David
>>
>>
>>-----Original Message-----
>>From: FSL - FMRIB's Software Library [mailto:[log in to unmask]] On Behalf
>>Of Patrick Purdon
>>Sent: Tuesday, May 12, 2009 5:52 PM
>>To: [log in to unmask]
>>Subject: [FSL] Adjusting Global Intensity Normalization? Group Analysis on
>>Mean BOLD signal?
>>
>>Hi FSL'ers,
>>
>>I'm analyzing data from a drug study, where the drug is likely to change the
>>mean BOLD signal in a region-specific manner, in addition to altering
>>functional responses to stimulation. To account for any possible
>>region-specific mean BOLD signal changes as a function of drug level, I
>>would like to:
>>
>>1. Normalize each data set (or cope image) by its temporal mean (like
>>"mean_func.nii.gz"), essentially creating a "percent signal change image."
>>This would allow me to compare drug-level effects in my group analysis in
>>terms of percent signal changes.
>> --I tried doing this on some simulated data by scaling the first-level
>>"cope1" by 100/mean_func and varcope1 by (100/mean_func)^2, but the flame12
>>2nd-level pe's and copes ended up being identical to the unscaled case
>>(????). What could be happening here? Is there a straightforward way to
>>accomplish this?
>>
>>2. Run a flame12 analysis on the mean BOLD signal as a function of drug
>>level.
>> --Is there an easy way to get an unscaled temporal mean and variance
>>from the first-level analysis that can be passed up to flame12?
>>
>>Any suggestions on how to do this? Thanks a lot for your help!
>>
>>--Patrick
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