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
|