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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:

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:

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

Change Log


  • 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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