The Functional_Fusion Framework is designed to bring contrast maps and preprocessed time series from different fMRI experiments into a common analysis space - flexibly and efficiently. The framework is especially designed to share and analyze datasets with many different task for individual subjects. Aggregating these fMRI datasets is a powerful way to build better and bigger models of brain function.
It is written and maintained by the Diedrichsen Lab, Western University. We welcome contributions of datasets and code from the community.
Contact: Joern Diedrichsen ([email protected])
This project depends on several third party libraries, including:
numpy (version>=1.22.2)
nilearn (version>=0.9.0), ...
pip install numpy nibabel nilearn neuroimagingtools
Or you can install the package manually from the original binary source as above links.
Once you clone the functional fusion repository, you may want to it to your PYTHONPATH, so you can import the functionality. Add these lines to your .bash_profile, .bash_rc .zsh_profile file...
export PYTHONPATH=<abspath_of_repo_maindir>:$PYTHONPATH
For detailed documentation see: https://functional-fusion.readthedocs.io/en/latest/.
Source files for the online documentation can be found in the docs folder.