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# Eigenangles: evaluating the statistical similarity of neural network activity and connectivity via eigenvector angles
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-Code and data repository accompanying the publication Gutzen et al. (2022) https://doi.org/...
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+Code and data repository accompanying the publication Gutzen et al. 2022 https://doi.org/...
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<RRID> [![DOI](https://zenodo.org/badge/DOI/XXXX/zenodo.XXXX.svg)](https://doi.org/XXXX/zenodo.XXXX)
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/git/https%3A%2F%2Fgin.g-node.org%2FINM-6%2Feigenangles/HEAD?labpath=eigenangle_basics.ipynb)
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+## Keywords
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+Statistical Testing | Random Matrix Theory | Neural Network Models | Connectivity-Activity Relation
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## Content
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-The different applications and testing scenarios of the eigenangle test are separated into the folders [`balanced_network`](./balanced_network), [`stochastic_activity`](./stochastic_activity), and [`polychony_network`](./polychony_network) containing their corresponding workflows (see the respective `README.md` for details). The top-level folder `scripts` contains a general code basis used by each of the workflows.
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-The folder `paper_figures` contains the figures from the publications as generated by either notebooks or scripts in the respective application folders. Figure 1 and 2 are produced by the respective notebook with this folder.
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-The interactive jupyter notebook `eigenangle_basics.ipynb` presents a step-wise construction and explanation of the eigenangle test and can be executed via the above mybinder badge.
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+The different applications and testing scenarios of the eigenangle test are separated into the folders [`balanced_network`](./balanced_network), [`stochastic_activity`](./stochastic_activity), and [`polychony_network`](./polychony_network) containing their corresponding workflows (see the respective `README.md` for details). The top-level folder [`scripts`](./scripts) contains a general code basis used by each of the workflows.
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+The folder [`paper_figures`](./paper_figures) contains the figures from the publications as generated by either notebooks or scripts in the respective application folders. Figure 1 and 2 are produced by the respective notebook with this folder.
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+The interactive jupyter notebook [`eigenangle_basics.ipynb`](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/git/https%3A%2F%2Fgin.g-node.org%2FINM-6%2Feigenangles/HEAD?labpath=eigenangle_basics.ipynb) presents a step-wise construction and explanation of the eigenangle test and can be executed via the above mybinder badge.
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## Abstract
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Neural systems are often represented by networks, and the strategic comparisons between multiple, similar networks is a prevalent task in many research scenarios.
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