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⚠️ This project is not actively maintained anymore as the author doesn't do Seed-based resting state functional connectivity analysis on a regular basis anymore. ⚠️

Please feel free to take over, give it a better name, and take the idea to adapt in your own analysis.

SBFC

Seed-based resting state functional connectivity with Nilearn.

This project is subject to change as Nilearn GLM features are still under development.

Test and coverage codecov

Dependencies

The required dependencies to use the software are:

  • Python >= 3.7
  • Nilearn >= 0.7.0
  • Matplotlib >= 3.4.0

Install

First make sure you have installed all the dependencies listed above. Then you can install by running the following command in a command prompt:

pip install git+http://github.com/htwangtw/sbfc.git

Prepare your data

This library work on minimally processed data only. If you need to preprocess your imaging data, please consider fMRIprep.

You can find an example in example and files that you should prepare to run the pipeline.