I am using the FSL interface in Nipype for fMRI analysis and having a hard time creating a feat-specific file for preprocessing. Specifically, what I would like to do is:
- Create a
fsf_fileusing custom parameters for each participant
- Loop across all participants and run preprocessing for each using
fsf_filefrom step 1
In a previous workflow I have created an fsf for a level one analysis using
fsl.Level1Design(). However, I can’t find any guidance for how to perform the same function as
fsl.Level1Design() but running only pre-stats.
Looking closely into the nipype directory, I can see in
/nipype/interfaces/fsl/model_templates that there is a model template,
feat_header.tcl, which would allow me to change which stages are run by FEAT by accessing
# Which stages to run # 0 : No first-level analysis (registration and/or group stats only) # 7 : Full first-level analysis # 1 : Pre-Stats # 3 : Pre-Stats + Stats # 2 : Stats # 6 : Stats + Post-stats # 4 : Post-stats set fmri(analysis) $analysis_stages
However, there is no script in the fsl interface that can be used to access this template. Am I missing something crucial here? How can I create an fsf file for preprocessing and run this in FEAT without running preprocessing node-by-node in a workflow? Thanks, I appreciate any advice.