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
