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Hi Matthew, anyone else interested, I just stumbled across this comment -- "although the RFT maths gives us a Bonferroni-like correction, it is not the same as a Bonferroni correction. It is easy to show that the RFT correction is better than a Bonferroni correction, by simulation. Using the code in the http://imaging.mrc-cbu.cam.ac.uk/scripts/randomtalk.m, you can repeat the creation of smoothed random images many times, and show that the RFT threshold of 4.06 does indeed give you about 5 images in 100 with a significant Z score peak." -- from Matthew Brett's Wiki http://tinyurl.com/2etkhz (http://imaging.mrc-cbu.cam.ac.uk/imaging/PrinciplesRandomFields#head-504893e8afe62f1e3e8aaf3cb368a1d389261ef5) But I remembered seeing in the code for SPM (v2 or 5), that the *minimum* critical threshold of RF and Bonferroni is used: spm_uc.m And that the minimum p-value is reported: spm_P.m Which seems to conflict with the above comment, since if RF is more accurate, taking Bonferroni where it is less strict will inflate the type I error rate above the nominal value. No? Does anyone have any more info on this? E.g. a ref justifying the SPM minimum approach? I should admit here that I haven't read all the Worsley papers like I should have done, so may be missing something obvious... If I am missing something though, perhaps a note added to the Wiki and/or the SPM code referring to it would help others? Best, Ged.