SimBA (Simple Behavioral Analysis)
SimBA (Simple Behavioral Analysis) is a platform for analyzing behaviors of experimental animals within video recordings.
More Information
See below for raison d'être, detailed API, tutorials, data, documentation, support, and walkthroughs:
- GitHub: https://github.com/sgoldenlab/simba
- Documentation readthedocs: https://simba-uw-tf-dev.readthedocs.io/en/latest/
- API: https://simba-uw-tf-dev.readthedocs.io/en/latest/api.html
- Gitter chat support: https://app.gitter.im/#/room/#SimBA-Resource_community:gitter.im
- bioRxiv preprint: https://www.biorxiv.org/content/10.1101/2020.04.19.049452v2
- Nature Neuroscience paper: https://www.nature.com/articles/s41593-024-01649-9
- Open Science Framework (OSF) data buckets: https://osf.io/tmu6y/
- Video examples: http://youtube.com/playlist?list=PLi5Vwf0hhy1R6NDQJ3U28MOUJPfl2YWYl
- Slide examples: https://simba-uw-tf-dev.readthedocs.io/en/latest/docs/workflow.html
Installation
To install SimBA, use the following command:
pip install simba-uw-tf-dev
Citation
If you use SimBA in your research, please cite:
Goodwin, N. L., Choong, J. J., Hwang, S., Pitts, K., Bloom, L., Islam, A., Zhang, Y. Y., Szelenyi, E. R., Tong, X., Newman, E. L., Miczek, K., Wright, H. R., McLaughlin, R. J., Norville, Z. C., Eshel, N., Heshmati, M., Nilsson, S. R. O., & Golden, S. A. (2024). Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience. Nature Neuroscience, 27(7), 1411–1424. https://doi.org/10.1038/s41593-024-01649-9
@article{Goodwin_2024,
title = {Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience},
author = {Goodwin, Nastacia L. and Choong, Jia J. and Hwang, Sophia and Pitts, Kayla and Bloom, Liana and Islam, Aasiya and Zhang, Yizhe Y. and Szelenyi, Eric R. and Tong, Xiaoyu and Newman, Emily L. and Miczek, Klaus and Wright, Hayden R. and McLaughlin, Ryan J. and Norville, Zane C. and Eshel, Neir and Heshmati, Mitra and Nilsson, Simon R. O. and Golden, Sam A.},
journal = {Nature Neuroscience},
volume = {27},
number = {7},
pages = {1411--1424},
year = {2024},
doi = {10.1038/s41593-024-01649-9},
url = {https://doi.org/10.1038/s41593-024-01649-9},
publisher = {Springer Science and Business Media LLC}
}
Other formats (APA, MLA, Chicago, Harvard, Vancouver, RIS) and one-click .bib/.ris downloads: How to cite SimBA.
Licence
SimBA is licensed under a modified BSD 3-Clause License, permitting use for academic and research purposes only. For commercial licensing inquiries, contact sronilsson@gmail.com.
Contributors
Contributors on GitHub https://github.com/sgoldenlab/simba#contributors
Contact
1 maintainer
Metadata
1 maintainer
Release files for simba-uw-tf-dev 5.6.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
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| simba_uw_tf_dev-5.6.1.tar.gz | 10.9 MB | Details |
Built distribution (wheel)
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|---|---|---|---|---|
| simba_uw_tf_dev-5.6.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 23.9 MB
Release files / simba_uw_tf_dev-5.6.1.tar.gz
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Release files / simba_uw_tf_dev-5.6.1-py3-none-any.whl
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