Dear AFNI experts,
I understand that the assumption of Gaussian shape for spatial autocorrelation function (ACF) of the noise is essentially wrong.
Anyway, I was wondering how spatial restrictions affect the estimation of acf/fwhm values. To give an example, the usage of a mask with separate brain regions (say PCC, dlPFC and mPFC) in a GLM (and in the consequent 3dClustSim) will lead to less discrepancy between the results obtained with acf/fwhm? Why?
Thanks.
Simone
the usage of a mask with separate brain regions (say PCC, dlPFC and mPFC) in a GLM (and in the
consequent 3dClustSim) will lead to less discrepancy between the results obtained with acf/fwhm? Why?
It’s not clear to me how you’re masking the data. One mask per region or one mask for all those regions combined? My guess is that, with restricted regions in the brain, the less discrepancy between ACF and FWHM is likely due to lower spatial variability than the situation with the whole brain.
Dear Gang,
I was actually referring to a mask which combines all of the regions of interests.
Simone
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