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[user@localhost temp]$ first_utils --vertexAnalysis --usebvars -i L_Hipp_all.bvars -d designd des_2sample.mat -o L_Hipp_vertexMNI_2sample --useReconMNI
The various options are specified in the User Guide under Vertex Analysis, Usage. It is important to come up with a naming convention for the output files. I suggest starting with the structure name, adding "_vertex" to indicate this file is the output of the vertex analysis, then add suffixes. Here is a convention:
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The output of this step is a 4D nifti file (*.nii.gz) with the name as indicated in the -o option, and a _mask file with a similar name. Additional files with the same name as the design matrix but with different extenstions extensions are also created: *.con for t-contrast, *.fts for f-contrast.
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Randomize is like "Results" in SPM in that it does a statistical test on a contrast. The inputs (analysis and mask) are the outputs from the previous step.
[user@localhost temp]$ randomise -i L_Hipp_vertexMNI_2sample.nii.gz -m L_Hipp_vertexMNI_2sample_mask.nii.gz -o L_Hipp_vertexMNI_2sample_rand -d designdes_2sample.mat -t designdes_2sample.con -f designdes_2sample.fts --fonly -D (more threshold options required)
more options:
Just as in SPM Results we put in statistical tests (F or t) and thresholds, so we do the same with randomise (see here for initial details). A starting point might be
--fonly -D -F 3
to look at bi-directional effects (--fonly), after de-meaning the data (-D), with an F threshold of 3, with cluster-based correction for multiple comparisons.
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The guide (see Running vertex analysis) suggests always using demean and F-test only).
The "-o" indicates the output file name, so you probably want to label this with the test parameters (e.g., -o L_Hipp_vertexMNI_2sample_rand_D_F3 for the suggested options).
Probably Incorrect Example
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: t-tests
To run a t test
[user@localhost temp]$ randomise -i L_Hipp_vertexMNI.nii.gz -m L_Hipp_vertexMNI_mask.nii.gz -o L_Hipp_vertexMNI_rand -d design.mat -t design.con -T
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