[SM54] Pipeline reproduction (nistats - deriv)

[bclenet]

Softwares

• We use Nistats 0.0.1b for statistical modeling of fMRI data (whole-brain correction analysis).
• We use Nilearn 0.5.0 for signals extraction on the pre-hypothesized regions for ROI-based analysis. Then, we use Nistats0.0.1b for the statistical modeling on these signals.

Input data

derivatives (fMRIprep)

Additional context

• spatial_smoothing : Smoothing: 5mm, Nistats 0.0.1b, 5mm, Fixed kernel, Native volume

List of tasks

Please tick the boxes below once the corresponding task is finished. 👍

• 👌 A maintainer of the project approved the issue, by assigning a 🏁status: ready for dev label to it.
• 🌳 Create a branch on your fork to start the reproduction.
• 🌅 Create a file team_{team_id}.py inside the narps_open/pipelines/ directory. You can use a file inside narps_open/pipelines/templates as a template if needed.
• 📥 Create a pull request as soon as you completed the previous task.
• 🧠 Write the code for the pipeline, using Nipype and the file architecture described in docs/pipelines.md.
• 📘 Make sure your code is documented enough.
• 🐍 Make sure your code is explicit and conforms with PEP8.
• 🔬 Create tests for your pipeline. You can use files in tests/pipelines/test_team_* as examples.
• 🔬 Make sure your code passes all the tests you created (see docs/testing.md).