Hi - yes, this is the --twopass mode in randomise.
Cheers
> On 6 Nov 2015, at 02:42, chenhf_uestc <[log in to unmask]> wrote:
>
> Dear FSLers,
>
> The results of VBM are actually nonstationary images, and thus we cannot directly use cluster-based inference. We need correct the inference for such nonstationary. Previously, I used nonstationary cluster extent correction based on RFT for multiple comparison correction for VBM results. Recently, I read the paper, titled "Adjusting the effect of nonstationarity in cluster-based and TFCE inference". In this study, Dr. Salimi-Khorshidi and colleagues find that adjusting for local smoothness via a separate resampling procedure is more effective at removing nonstationarity than an adjustment via a random field theory based smoothness estimator.
>
> Where could I use this method? In the FSL software, there is nonparametric randomise TFCE method. However, in the original TFCE paper (Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference, 2009, neuroimage), I do not find the separate resampling procedure in this paper.
>
> What about the current version of FSL software? Has used the separate resampling procedure or not? Has used the method introduced in "Adjusting the effect of nonstationarity in cluster-based and TFCE inference"? If not, could I use the TFCE method for VBM's multiple comparison correction.
>
> Best,
> Feng
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Stephen M. Smith, Professor of Biomedical Engineering
Head of Analysis, Oxford University FMRIB Centre
FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
+44 (0) 1865 222726 (fax 222717)
[log in to unmask] http://www.fmrib.ox.ac.uk/~steve
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