Brain Surrogate Maps with Autocorrelated Spatial Heterogeneity.
Project description
BrainSMASH
BrainSMASH (Brain Surrogate Maps with Autocorrelated Spatial Heterogeneity) is a Python-based computational platform for statistical testing of spatially autocorrelated brain maps. At the heart of BrainSMASH is the ability to simulate surrogate brain maps with spatial autocorrelation that is matched to spatial autocorrelation in a target brain map. Additional utilities are provided for users using Connectome Workbench style surface-based neuroimaging files.
Exhaustive documentation can be found here.
Dependencies
Installing BrainSMASH requires:
- Python 3+
- numpy
- scipy
- pandas
- nibabel
- matplotlib
- scikit-learn
If you wish to use the additional utilities provided for Connectome Workbench users, you must have
Connectome Workbench installed with the wb_command
executable locatable in your
system PATH environment variable.
Installation
BrainSMASH is most easily installed using pip:
pip install brainsmash
You may also clone and install the source files manually:
git clone https://github.com/murraylab/brainsmash.git
cd brainsmash
python setup.py install
License
The BrainSMASH source code is available under the GNU General Public License v3.0.
Preprint
Please cite the following preprint if you use BrainSMASH in your research: TODO
Core development team
- Joshua B Burt, Murray Lab - Yale University
- John D Murray, Murray Lab - Yale University
Change Log
- 0.0.1 Initial beta release.
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