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Thank you! What we ended up doing is using the non-stationarity toolbox implemented in SPM (Hayasaka, http://fmri.wfubmc.edu/cms/NS-General). As it turns out, it's not hard to use a looped 3dcalc (AFNI, Cox) command to split the FSL-generated 4D VBM results into separate 3D datasets (one for each subject), then submit these as the dependant variable in a SPM model estimation, save the "SPM.mat", and use that model to submit to the "ns" toolbox. It spits out the NS-corrected clusters quite nicely. If anyone needs (more specific) steps on how to do this, you can email me at schwartd (at) ohsu.edu. Anyway, thank you! -Daniel -----Original Message----- From: FSL - FMRIB's Software Library on behalf of Reza Salimi Sent: Sun 6/7/2009 4:16 AM To: [log in to unmask] Subject: Re: [FSL] Non-stationary thresholding of VBM results Hi Daniel, currently we are adding this option to *randomise* for both TFCE and cluster-based inferences, but unfortunately, it is not yet publicly available ... We will present the algorithm and the results in HBM 2009 in SF in case you are going to be there ... but in general, If you want to adjust the inference for the nonstationarity, it is necessary to use adjusted cluster-sizes (in RFT-based RPV units) in all of you * randomise* permutations (see Hayasak et al. 2004). It means, you need to modify the current randomise code in order to do that ... and cannot combine other tools with *randomise *in order to do that ... However, if you want to parametrically do this, you can use the T-stat image from* randomise* plus the standardized residual error of the first permutation's GLM fit. This residual is used in order to estimate the geometry of the random Z-stat (or gaussianized T-stat) and hence its null distribution under the null hypothesis, and results in a voxel-wise roughness estimate (RPV, or roughness per voxel). Currently, this residual is not written as an ouput volume; you need to add a line to the randomise.cc file, which writes this 4D residual volume in the output (note! just the first permutation) ... I haven't used that matlab toolbox, but in the RFT-based adjustment for nonstationarity (according to Wrosely's works, and later Hayasaka's works), these are the only two volumes you need. hope it helps ... Best, Reza On Wed, May 27, 2009 at 4:16 PM, Daniel Schwartz <[log in to unmask]> wrote: > > Hi everyone! > > I'm not sure if NS cluster based inference is available in FSL (I assume it > isn't) so I've been trying to use Worsley's FMRISTAT MATLAB-based toolbox. > However, I'm having some trouble implementing the correction. Does anybody > either a) have a different program to suggest or b) have instructions on how > to do this in FMRISTAT? Thank you in advance for your help! > > -Daniel > -- G. Salimi-Khorshidi, D.Phil. Student, Dept. of Clinical Neurology, University of Oxford. [log in to unmask] http://www.fmrib.ox.ac.uk/~reza FMRIB Centre, John Radcliffe Hospital, Headington, Oxford, OX3 9DU Tel: +44 (0) 1865 222466 Fax: +44 (0)1865 222717