In March of 2000 (http://www.mailbase.ac.uk/lists/spm/2000-03/0205.html), Karl offered the following relative to smoothing.
"The smoothness should be 2-3 times the voxel size of the data that
enters the estimation procedure (i.e. after spatial normalization).
One can therefor subsample the data to smaller voxels and then smooth
with a kernel that approximates the original voxel size. It is
important to note that the smoothness is the post hoc smoothness of the
residual fields (given in the SPM table footnotes). This smoothness
may be much greater than the size of the smoothing kernel."
I recently analyzed fMRI data that has native voxel dimensions of 3.75x3.75x5mm.
After realign & coregister, voxel dimensions were still 3.75x3.75x5mm.
Without applying any smoothing via spm_smooth.m, SPM reports the smoothness as (given in the SPM table footnotes) as:
FWHM 8.6x8.6x10mm = 2.3x2.3x2 voxels
Thus it seems that without applying any smoothing via spm_smooth.m, my data meet the smoothness criteria.
Is this to be expected?
My usual approach is to apply a smoothing kernel of twice the native voxel size (e.g.7.5x7.5x10) regardless of the smoothness reported by SPM , but if I understand Karls criteria, no smoothing need be applied to this data to accomplish the desired smoothness. Actually, if I apply a filter kernel of 7.5x7.5x10mm to the data via spm_smooth.m, SPM reports the smoothness as:
FWHM 48.9x52.8x60.2mm=13x14.1x12 voxels!!!!!!!
So, is it best to process the data initially without applying any smoothing, and then based upon the smoothness reported by SPM decide whether and how much smoothing to apply via spm_smooth.m?
Jerry Allison, Ph.D.
Medical College of Georgia
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