On Wed, Jun 13, 2012 at 11:28 AM, Chaleece Sandberg
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Hello!
I am wondering how SPM performs this function and what the data are that I'm looking at. The process is to choose a peak voxel for a particular contrast and then extract the eigenvariate for the area around that voxel. When using a sphere, it makes sense that the peak voxel is at the center of the sphere. Is it correct to assume that the eigenvariate is computed using all voxels in that sphere? If so, then what happens when using a mask? Is the eigenvariate computed using all voxels in that mask, or just those in the mask that belong to the peak's cluster? Does it even matter which peak I choose if I'm using a mask?
It chooses all voxels that are above the threshold, in the mask, and inside the sphere. If a voxel doesn't meet all three criteria then its not included. Depending on the radius of the sphere, the peak voxel that you select may or may not make a difference.
When it lists the number of voxels in the graphics window under the graph of the eigenvariate, are those the voxels that are active at the chosen threshold within the chosen mask? In other words, if there are just a handful of voxels, the computation is from those voxels and not the whole mask? So, for example, if there are 6 voxels in the RH mask, but 60 in the LH mask (in areas that are roughly the same size bilaterally), is there a built-in correction for the fact that one is much more "active" than the other?
The eigenvalues are computed for the active voxels. There is no correction for the number of voxels.
I hope these questions make sense. I haven't found any other source for answering them, so any insight would be greatly appreciated!
Thanks!
