Hi all,
I’d like to open this discussion back up, if I could. It sounds like the suggestion was:
[I]If you want to spatially smooth a source image, you should smooth at the individual anatomy level BEFORE projecting to a template brain.[/I]
However, this seems to be the [U]opposite[/U] of what is recommended for fMRI. The principles of fMRI are clearly different from MEG on many levels, but the recommendation for fMRI is to smooth AFTER normalization to a template brain when averaging subjects together. This link explains things well for fMRI (http://mindhive.mit.edu/node/112).
One reason I can think to do smoothing AFTER projection is so that the filter properties are consistent across subjects. For example, if a subject’s head is smaller than the template the warping will be expanding the original brain and will functionally expand any smoothing kernels that are applied before projection. Similarly, if a subject’s head is bigger than the template, the warping will shrink the brain and therefore shrink the smoothing kernel. This would mean the smoothness is brain-size dependent (e.g. smaller brain means smoother sources). I admit I have no idea how much this will really matter and I’m not even considering the nonlinearity of warping.
For fMRI, spatial smoothing increase SNR by attenuating voxel-independent noise AND by helping account for anatomy differences in a group. I’m not sure this first reason is valid for MEG where each source is not independent (i.e. recording noise will affect multiple sources at the same time due to the inverse kernel). It seems the second reason (i.e. group-anatomy) is the reason to do smoothing in MEG. To me, this means having the smoothing kernel be the same across all subjects in a group would make the most sense (e.g. [Project -> Smooth]). In fact, I’m not sure if smoothing MEG for individual subjects is valid (please correct me…I’d love to smooth my data).
I’d love to hear what other people think about this and please point out where I’m wrong.
-Stephen Foldes