This repository implements the hierarchical Bayesian framework for learning brain parcellations across task-based and resting-state fMRI datasets. The technical details are described in the following paper, and we have applied the framework to generate a new probabilistic atlas of the human cerebellum.
The code for this framework is openly available. You can use this repository to:
- Learn new probabilistic brain parcellations across multiple fMRI datasets using other datasets for different brain structures.
- Use existing probabilistic atlases to obtain individualized brain parcellations for new subjects through the optimal integration of individual localizer data and the group atlas.
Diedrichsen Lab, Western University
.. toctree:: :maxdepth: 2 :caption: Contents: install.rst overview.rst atlas_training_example indiv_parcel.rst math.rst gpu_acceleration.rst reference.rst literature.rst
GitHub repository link: https://github.com/DiedrichsenLab/HierarchBayesParcel
Please find out our development license (MIT) in LICENSE file.
For any problems and questions, please use the issues page on this repository. https://github.com/DiedrichsenLab/HierarchBayesParcel/issues. We will endeavour to answer quickly.