Variational (VEM) analysis

Variational (VEM) analysis

Variational (VEM) analysis – To run a JDE-VEM analysis you need:

  • paradigm csv file corresponding to your experimental design
  • the preprocessed (spatially UNsmoothed) BOLD data associated with a single run [4D-Nifti file]
  • the TR (in s) used at acquisition time
  • a parcellation mask (if you normalize your data into MNI space, you can use the one provided with pyhrf)
Variational (VEM) analysis

If you want to use provided parcellation mask, check the path of the file by running:

$ pyhrf_list_datafiles

and check for the stanford_willard_parcellation_3x3x3mm.nii.gz file.

Then you can run:

$ pyhrf_jde_vem_analysis 2.5 stanford_willard_parcellation_3x3x3mm.nii.gz paradigm.csv bold_data_session1.nii
Variational (VEM) analysis

If you want to tune the parameters, check command line options (see commands). This is adviced to set the dt parameter (the temporal resolution of the HRF) and the output folder.


check out the path of the files subj0_bold_session0.nii.gzsubj0_parcellation.nii.gz and paradigm_loc.csv using:

$ pyhrf_list_datafiles

then run:

$ pyhrf_jde_vem_analysis 2.4 subj0_parcellation.nii.gz paradigm_loc.csv subj0_bold_session0.nii.gz

replacing the files by their full path. This will create output files in the current folder. Check Visualization tools to check the outputs file.

  • The multirun extension is currently under development and testing