⚠️ 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.
Seed-based resting state functional connectivity with Nilearn.
This project is subject to change as Nilearn GLM features are still under development.
The required dependencies to use the software are:
- Python >= 3.7
- Nilearn >= 0.7.0
- Matplotlib >= 3.4.0
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
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.