LISA onesample test (vlisa_onesample) --------------------------------------- The program **vlisa_onesample** performs a one-sample t-test on a group of images including a correction for multiple comparisons using the LISA algorithm [2018_Lohmann]_. The input is a list of 3D images resulting from a 1st level computation. For ease of use, the input images may be specified using wildcards as shown below. The output is a map thresholded such that FDR < alpha for every voxel. The default is alpha=0.05. The resulting image shows (1-FDR) so that larger values indicate higher significance. Note that a region-of-interest mask is required. The mask should exclude non-brain voxels, and it may cover the entire brain. In the example below, the mask is in the file "braimmask.nii". :: vlisa_onesample -in images_*.v -mask brainmask.nii -out result.v Note that this program also accepts input images in Nifti format ("images_*.nii" or "images_*.nii.gz"), but the output is always in vista format. To convert the output to the Nifti format, use the following command: :: vnifti -in result.v -out result.nii Parameters of 'vlisa_onesample': ``````````````````````````````````` -help Prints usage information. -in Input files. -out Output file. -alpha FDR significance level. Default: 0.05 -perm Number of permutations. Default: 5000 -mask Region of interest mask. -seed Seed for random number generation. Default: 99402622 -radius Bilateral parameter (radius in voxels). Default: 2 -rvar Bilateral parameter (radiometric). Default: 2.0 -svar Bilateral parameter (spatial). Default: 2 -filteriterations Bilateral parameter (number of iterations). Default: 2 -cleanup Whether to remove isolated voxels. Default: true -j Number of processors to use, '0' to use all. Default: 0 .. index:: lisa_onesample References ^^^^^^^^^^^^^^^^^^^^^^^ .. [2018_Lohmann] Lohmann G., Stelzer J., Lacosse E., Kumar V.J., Mueller K., Kuehn E., Grodd W., Scheffler K. (2018). LISA improves statistical analysis for fMRI. Nature Communications 9:4014. `(link) `_