For generating surrogate brain maps with spatial autocorrelation using geometric eigenmodes.
Project description
The eigenstrapping toolbox is designed to help researchers generate statistically-rigorous models for null hypothesis testing between brain maps using non-local spectral shape descriptors - or geometric eigenmodes. Documentation can be found here.
Features
A growing library of eigenmodes of standard surfaces and surface densities (fsaverage, fsLR)
Cortical and subcortical null models for assessing statistical correspondence between brain maps
Generation of geometric eigenmodes on user-derived surfaces
Installation Guide
Eigenstrapping is available in Python 3.7+. MATLAB version coming soon!
Dependencies
To install eigenstrapping, the following Python packages are required:
nibabel and nilearn are required for surfaces and volumes. matplotlib is only required for fitting plots in fit.py and some of the surface plotting functions. Future improvements will reduce the number of dependencies needed.
Additional dependencies
Installation
eigenstrapping can be installed using pip:
pip install eigenstrapping
Alternatively, you can install the package from the Github repository:
git clone https://github.com/SNG-newy/eigenstrapping.git cd eigenstrapping python setup.py install
Citing
When using eigenstrapping, please cite the following manuscript:
null
And please also cite the papers for the method that we use to calculate eigenmodes on the surface:
Laplace-Beltrami spectra as ‘Shape-DNA’ of surfaces and solids. Reuter M, Wolter F-E, Peinecke N. Computer-Aided Design. 2006;38(4):342-366. http://dx.doi.org/10.1016/j.cad.2005.10.011
BrainPrint: a discriminative characterization of brain morphology. Wachinger C, Golland P, Kremen W, Fischl B, Reuter M. Neuroimage. 2015;109:232-48. http://dx.doi.org/10.1016/j.neuroimage.2015.01.032 http://www.ncbi.nlm.nih.gov/pubmed/25613439
License information
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License cc-by-nc-sa. The full license can be found in the LICENSE file in the eigenstrapping distribution.
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