If you are after area-wise activation in individual subjects, would you be willing to do a parcellated (i.e. area-wise) analysis where you could use something simple like FDR or Bonferroni (and get substantial SNR/power benefits)? If what you are actually after is to define regions of activation (instead of assessing the statistical significance of the activation in every grayordinate), I wouldn't use statistical thresholding but instead would use gradients in the effect size map to identify most probably boundaries.
In most cases for multiple comparison correction we are recommending people to use FSL's PALM, but it is permutation-based. Peace, Matt. From: <hcp-users-boun...@humanconnectome.org<mailto:hcp-users-boun...@humanconnectome.org>> on behalf of Julien Dubois <jcrdub...@gmail.com<mailto:jcrdub...@gmail.com>> Date: Friday, October 9, 2015 at 4:53 PM To: "hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>" <hcp-users@humanconnectome.org<mailto:hcp-users@humanconnectome.org>> Subject: [HCP-Users] Cluster-extent thresholding of CIFTI data Dear HCP developers, I'm wondering if you have come up with a good cluster-extent thresholding procedure and implemented it as part of the workbench yet. I have seen a couple of threads here<https://www.mail-archive.com/hcp-users%40humanconnectome.org/msg00893.html> and here<https://www.mail-archive.com/hcp-users%40humanconnectome.org/msg00993.html> re: this issue. One strategy would be to go the Monte Carlo way, considering the two surfaces and the volume separately (cf. Hagler et al 2006<http://www.sciencedirect.com/science/article/pii/S1053811906007919> for the surface, which seems to be implemented in Freesurfer as mri_mcsim<https://surfer.nmr.mgh.harvard.edu/fswiki/BuildYourOwnMonteCarlo> and mri_glmfit-sim for the surface; and of course the very popular AlphaSim<http://afni.nimh.nih.gov/pub/dist/doc/program_help/AlphaSim.html>, superseded by 3dClustSim<http://afni.nimh.nih.gov/pub/dist/doc/program_help/3dClustSim.html>, in AFNI for the volume). Another way would be to go the Random Field Theory route. It's done in the volume in SPM with spm_uc_clusterFDR.m; I'm sure it has been adapted to surface data in some software suites (looks like the matlab code<http://www.math.mcgill.ca/keith/fmristat/toolbox/stat_threshold.m> in this old thread<https://mail.nmr.mgh.harvard.edu/pipermail/freesurfer/2007-August/005881.html> could work). Finally, FSL's randomize is another option that would play well with both surface & volume at the same time, and it seems to be the route you've taken. However (*correct me if I'm wrong*), this is not applicable to single-subject data with one run only, which is one of my interests. Please advise on the current status of development, and whether I need to "hack" my own cluster extent threshold correction based on MC or RFT for CIFTI data (if anyone knows any other good code resources to perform these analyses on surface/volume data, please share!). Thanks, - Julien -- Julien Dubois Postdoctoral Scholar California Institute of Technology, Pasadena, CA http://emotion.caltech.edu/~jdubois _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> http://lists.humanconnectome.org/mailman/listinfo/hcp-users _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
