Hello,
I've been trying some group resting-state analyses using tc_ica in melodic, then dual_regression. I have a few possibly silly questions so far:
1) In the dual regression dr_stage2_ic???? maps, there is often a large contribution of ventricles. Looking back at the melodic output, there is indeed some voxels from ventricles, even in components that should be relatively clean (auditory) maps. Are there ways to reduce this noise? Using a thresholded map as input to dual_regression, or running fsl_regfilt to denoise individual subjects? We let melodic estimate the number of components, would fixing a larger number reduce this problem? This last solution seems somewhat arbitrary.
2) In our first test of the whole procedure, many voxels in the randomise output appear to be voxels at the very edge of the brain, or at the edge of the somewhat limited FOV of the scan. We ran BET as part of the melodic gui, but is it necessary to apply a less lenient bet, or to mask at some point (other than the mask dual_regression calculates)? Registration seemed okay, although with the blank spaces from our FOV.
3) Is there any difference, other than computational load, between running dual_regression with the full melodic_IC and running dual_regression with individual components (of interest, excluding the noise components) split from the melodic_IC file? And, in the later case, it is preferable to re-merge the components of interest for a multiple regression?
Thanks in advance for any help,
-Michael
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