Hi Graham,

Burying your head in David's PALS paper is indeed the best way to get your head around this stuff. It took me three careful reads before I really digested it. (And you can't whip through in a short plane ride.)

To get a more hands-on feel for Caret/SureFit surfaces, consider
downloading and playing with these datasets in Caret:

PALS_VE05_FIG-11_FMRI_MFMapping.73730.spec
From PALS paper, figure 11
http://sumsdb.wustl.edu/sums/archivelist.do?archive_id=6334372

Human.PALS.VE-et-al_JN06_WILLIAMS_Suppl_Fig-1_Volumes_Fiducials.spec
From WS paper (http://www.jneurosci.org/cgi/content/full/26/20/5470),
supplementary figure 1
http://sumsdb.wustl.edu/sums/archivelist.do?archive_id=6473226

Also, notice in David's email replies:  You have taught him to say
"voxel-wise statistics" rather than "volume-averaged fMRI results" --
well done!

When mapping to the PALS_B12 surfaces, there's plenty of uncertainty to
go around.  Increasingly, there's consensus that reconstructing
individual surfaces and doing one's analysis in "surface-land" is an excellent complement to voxelwise-statistics for most cortical studies. But for the majority of researchers not yet prepared to do so, this atlas is a useful visualization substrate for their group results.

Questions about which mapping method to use are valid, and reasonable
people can disagree about such things, but as you say, it's relatively
in the noise compared to what I would call "doing it right."

Another source of variability stems from the degree to which the
PALS_B12 average fiducial surface represents your sample's average
anatomy well.  In a joint study with Dr. Csernansky and Deanna Barch's
lab, the PALS_B12 average fiducial represents the CONTROLS' anatomy well, but schizophrenics' anatomy less well. Anatomical differences across groups almost certainly contribute (even where they may not quite reach statistical significance by our conservative method). In the attached captures, the structural underlay is a mean SCZ volume for SCZ13anat_SFSdiff.jpg, mean CONTROL volume for CON19anat_SFSdiff.jpg. In both captures, the blue contour is the average CON fiducial (sample subjects -- not PALS_B12); the red contour is the average SCZ fiducial. Not shown, the CON average fiducial overlaps the PALS_B12 fiducial much better than does the SCZ average fiducial. Of course, you don't know how good a proxy PALS_B12 is for your sample unless you reconstruct all your subjects. (Thanks to Dr. Lei Wang and Dr. Deanna Barch for allowing use of their prepublication data.)

On 10/27/2006 12:39 AM, Graham Wideman wrote:
David:

Further, my superficial understanding of MFM worries me that a weak
activation caught by all surfaces might produce the same appearance
as strong activation caught by only a small proportion of the MF
surfaces.

That is indeed possible.  However, this isn't necessarily a bad
thing.  Moreover, the same thing can occur during volume-based
statistical analyses - a voxel that shows weak but consistent
activation may show the same z-statistic as a voxel that has a strong
activation in a small proportion of individuals.

Not sure if it's important, but these seem somewhat different cases. In the voxel-based situation the "confounding" obscures the difference between "a few strong activations" vs "many weak activations".

In the MFM situation, the confounding is at a subsequent stage: this is not about muddling strong and weak activations, but rather it's about the sampling strategy (fMRI->surface mapping) being more or less sensitive in different regions, depending on the variability of the MF surfaces in that region (ie: how many of the MF surfaces intersect an activation).

But all this may be relatively in the noise, I guess, compared to using surfaces derived from each individual subject.

(Again, time to read the paper in detail, and see in what ways you've been able to characterize the sensitivity of generic MFM vs using subjects' own surfaces.).

All very interesting.

Graham
--

Donna L. Dierker
(Formerly Donna Hanlon; no change in marital status -- see http://home.att.net/~donna.hanlon for details.)


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