Lipsia is a collection of tools for the analysis of fMRI data. Its main focus is on new algorithms such as statistical inference (LISA), Eigenvector centrality mapping (ECM) and network detection in task-fMRI (TED). Below, a brief description follows. For further details see documentation.

Lipsia currently supports Linux and all other operating systems via Docker. Follow the instructions here: install.

Find the full lipsia documentation here: documentation.

Onesample test at the 2nd level (vlisa_onesample). Example: the input is a set of contrast maps called "data_*.nii.gz":

vlisa_onesample -in data_*.nii.gz -mask mask.nii -out result.v
vnifti -in result.v -out result.nii

Twosample test at the 2nd level (vlisa_twosample). Example: input are two sets of contrast maps called "data1_*.nii.gz" and "data2_*.nii.gz":

vlisa_twosample -in1 data1_*.nii.gz -in2 data2_*.nii.gz -mask mask.nii -out result.v
vnifti -in result.v -out result.nii

Single subject test (1st level) (vlisa_prewhitening). Example: input are two runs acquired in the same session called "run1.nii.gz" and "run2.nii.gz". Preprocessing should include a correction for baseline drifts!:

vlisa_prewhitening -in run1.nii.gz run2.nii.gz -design des1.txt des2.txt -mask mask.nii -out result.v
vnifti -in result.v -out result.nii

Example: input is an fMRI data set called "data.nii.gz" and a brain mask called "mask.nii.gz".:

vecm -in data.nii.gz -mask mask.nii.gz -j 0 -out ecm.v
vnifti -in ecm.v -out ecm.nii

Lipsia uses its own data format, which is called vista (extension .v). Many lipsia programs also accept gzipped files or nifti-files as input (.v.gz or .nii.gz). The output is always in unzipped vista-format. You can easily convert your nifti data from and to lipsia with the program *vnifti:

vnifti -in data.nii -out data.v
vnifti -in data.nii.gz -out data.v
vnifti -in result.v -out result.nii

Alternatively, you can import a folder with DICOM files into the vista format:

vdicom -in dir_dicom

The current release contains only a rudimentary set of preprocessing tools. Preprocessing should therefore be performed beforehand using other software packages. Note that some lipsia algorithms require that the preprocessing pipeline contains a removal of baseline drifts. This step can be done using the lipsia program "vpreprocess" if it was omitted in the initial preprocessing.