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The short answer is, no, in fMRI we care most about partitioning temporal variance rather than mean image signal intensity, e.g. for establishing significance.
The longer answer is that we could be doing better with the bias field correction (e.g. if someone wants to make accurate effect size maps of % BOLD). In other cases, it is better to normalize the data so that unstructured noise variance is equal across
the image (e.g. when doing any kind of analysis that would be sensitive to different weights of the variance across the matrix, like ICA). It is important to note that one cannot do both of these things at the same time, but one can do one of them and then
the other (e.g. run ICA on variance normalized data and then convert output maps to effect size).
Peace,
Matt.
From: Tianwen Chen <[email protected]>
Date: Monday, April 13, 2015 at 1:15 PM To: "[email protected]" <[email protected]> Subject: [HCP-Users] inhomogeneous signal intensity Hi HCP users,
When we looked at the resting state fMRI data (minimally preprocessed), we found that there are pretty obvious signal intensity difference between brain areas. For example, the frontal areas have significantly higher signal intensity than other brain areas
(see the attached figure). We are wondering whether this is considered as artifacts that need special treatment?
Thanks,
Tianwen
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- [HCP-Users] inhomogeneous signal intensity Tianwen Chen
- Re: [HCP-Users] inhomogeneous signal intensity Glasser, Matthew
