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Many of the recent emails regarding the limitations of the stationariness assumption for SVC in VBM made specific reference to SPM99. Does SPM2 use a local estimate of resels per voxel estimate when calculating small volume correction? I.e. is the SVC procedure in SPM2 "safe" for VBM? Thanks HOWIE ROSEN UCSF Department of Neurology Memory and Aging Center -----Original Message----- From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]]On Behalf Of Satoru Hayasaka Sent: Tuesday, February 22, 2005 11:48 AM To: [log in to unmask] Subject: Re: [SPM] SVC procedure in VBM At 10:39 AM 2/22/2005 -0800, Matthew Brett wrote: >Thanks very much for this - it's very helpful. Do you have a view on >the extent of the problem if you simply assume that the image is >stationary, at 8mm, 12mm smoothing? I happened to have a VBM data set, smoothed with 12mm. I took a look at the RPV image, and I can tell that my data set is not stationary. The smoothest spot has FWHM about 30mm and the least smooth spot has FWHM about 12mm. So I don't think a heavy smoothing induces stationarity, and simply assuming stationarity could lead to biased results in a cluster size test. The p-values are underestimated for clusters in smooth areas, and are overestimated for clusters in rough areas. You are more likely to detect clusters in smooth areas than the ones in rough areas. A voxel-height test, on the other hand, seems to be robust to non-stationarity. But if it is to be used in an SVC context, I suggest re-calculating the average smoothness in an ROI, just in case that the ROI happens to be in a smooth / rough spot. -Satoru Satoru Hayasaka ============================================== Post-Doctoral Fellow, MR Unit, UCSF / VA Medical Center Email: shayasak_at_itsa_dot_ucsf_dot_edu Phone:(415) 221-4810 x4237 Homepage: http://www.sph.umich.edu/~hayasaka ==============================================================