Hi - it should be fine to use the two options together.

Cheers

On 6 Nov 2015, at 06:56, chenhf_uestc <[log in to unmask]> wrote:

Thanks, Stephen

You mean that I cannot use -T option directly in the randomise, right? Like that,

randomise -i TwoSamp4D (two group's VBM data) -o TwoSampT -d design.mat -t design.con -m mask -T (carry out Threshold-Free Cluster Enhancement)

You say that I need use the --twopass option (carry out cluster normalisation thresholding), how could I input the command? Just like,

randomise -i TwoSamp4D (two group's VBM data) -o TwoSampT -d design.mat -t design.con -m mask --twopass

or I need use the -T and --twopass at the same time to achieve that use the TFCE method for VBM's multiple comparison correction.
randomise -i TwoSamp4D (two group's VBM data) -o TwoSampT -d design.mat -t design.con -m mask -T --twopass
Which one is right? If I just use the --twopass option, the randomise command could know that I want to  modified (adjusting for local smoothness via a separate resampling procedure) TFCE method?

Thanks,

Feng

发件人：Stephen Smith <[log in to unmask]>

发送时间：2015-11-06 13:15

主题：Re: [FSL] Could I use the TFCE method for VBM's multiple comparison correction?

收件人："FSL"<[log in to unmask]>

抄送：

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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Stop the cultural destruction of Tibet

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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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Stop the cultural destruction of Tibet