Brain Surrogate Maps with Autocorrelated Spatial Heterogeneity.
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.
Installing BrainSMASH requires:
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.
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
The BrainSMASH source code is available under the GNU General Public License v3.0.
Please cite the following preprint if you use BrainSMASH in your research:
Burt, J.B., Helmer, M., Shinn, M.W., Anticevic, A., Murray, J.D. (2020). Generative modeling of brain maps with spatial autocorrelation. bioRxiv doi: 10.1101/2020.02.18.955054v1
Core development team
- Joshua B Burt, Murray Lab - Yale University
- John D Murray, Murray Lab - Yale University
- 0.1.1 Fixed bug in NaN handling.
- 0.1.0 Added goodness-of-fit metrics to stats module.
- 0.0.9 Fixed bug in Sampled.sampled.permute_map().
- 0.0.8 Relaxed nibabel version dependency.
- 0.0.7 Removed console print statements.
- 0.0.6 Fixed masked dense array handling.
- 0.0.1 Initial beta release.
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