Dear YAN Chao-Gan,
I saw you posted a script ( y_Smoothest) which calculates the inherent smoothness of a data set. Thanks for publishing that script, but I have a couple of question related to that:
I wonder if one should rather use the residuals of the GLM, i.e. the file ResMS.img or if it is better to use the con image (e.g. con_0004.img) or even the spmT (e.g. spmT_0004.img) images to determine the inherent smoothness? What would you propose?
I calculated the values with your program and then read that SPM itself does calculate FWHM during the results process as well. The values are given on the results sheet of SPM in the Graphics window on the bottom. However these values and the ones I got with your method (irrespective of the image I used, see above) differ in a way. Do you know what you do differently than SPM? I think SPM takes the residuals as described by Kiebel et al., 1999, NeuroImage (http://www.fil.ion.ucl.ac.uk/spm/doc/papers/sjk_robust.pdf), but even if I take the residuals (ResMS.img), I get different values. SPM unfortunately doesn’t show the values for individual masks, but only for the whole brain.
Moreover, I wonder what you would take as input for FWHM as input for alphasim, the mean of FWHMx, FWHMy, FWHMz?
Thanks a lot for your help in advance and sorry for double posting!
University of Leipzig
Department for Psychosomatic Medicine