By non-stationarity, I assume you are talking about variable smoothness across the cortical surface? We don't correct for it right now, which means that p-values for clusters in low-smoothness regions will be a little conservative and those in high-smoothness regions will be a little liberal. The theory exists to correct for this, but I have not implemented it yet. PALM my have a solution. See https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/PALM/UserGuide and our interface https://surfer.nmr.mgh.harvard.edu/fswiki/FsPalm. CC'ing Anderson in case he wants to weigh in. best doug

On 07/11/2018 10:00 AM, Antonin Skoch wrote:

Dear experts,

following on this old thread, do you have any new knowledge on the possible severity of non-stationarity in cortical-thickness maps and its effect on permutation-based cluster-extent inference? Given current status of development, is here a possibility to estimate it/correct for it?

Regards,

Antonin Skoch

Hi Hugo, they are assumed to be stationary. I've never tried to figure out how much of a problem this is. doug

On 7/25/12 6:03 PM, Hugo Baggio wrote:

Dear all,

I have been performing cortical thickness analyses and as far as I
understand the thickness maps are non-stationary (please correct
me if I'm wrong). I have two questions: 1. How susceptible is
Monte Carlo clusterwise correction to this(should I expect
clusters at smoother areas to be bigger?)? 2. Does FS perform some
sort of correction to this non-stationarity or are images assumed
to be stationary at statistical analyses?

Thanks a lot for your help!

Hugo

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