[1KB2] Pipeline reproduction (FSL - raw)

[elodiegermani]

Softwares

FSL

Input data

raw data

Additional context

Use of feat process and analysis: run-level + subject-level + group-level.

List of tasks

Please tick the boxes below once the corresponding task is finished. :+1:

• [x] :ok_hand: A maintainer of the project approved the issue, by assigning a :checkered_flag:status: ready for dev label to it.
• [x] :deciduous_tree: Create a branch on your fork to start the reproduction.
• [x] :sunrise: Create a file team_{team_id}.py inside the narps_open/pipelines/ directory. You can use a file inside narps_open/pipelines/templates file as a template if needed.
• [x] :brain: Write the code for the pipeline, using Nipype and the file architecture described in docs/pipelines.md.
• [ ] :blue_book: Make sure your code is documented enough.
• [x] :snake: Make sure your code is explicit and conforms with PEP8.
• [ ] :microscope: Create tests for your pipeline. You can use files in tests/pipelines/test_team_* as examples.
• [ ] :microscope: Make sure your code passes all the tests you created (see docs/testing.md).
• [ ] :inbox_tray: create a pull request from your code.

[bclenet]

For further work on this pipeline :

According to the description,

Gain, loss, and response predictor were orthogonalized to the unmodulated predictor.

This seems to be feasible with the orthogonalization parameter of nipype's Level1Design FSL interface.