🔬 Published Studies & Validations
Peer-reviewed studies and preprints that have used SimBA, plotted by country and summarized across species, journals, and the behaviors, brain regions, and methods they report. Compiled from the public use-case spreadsheet and the full text of the collected papers. To search and filter the individual studies, see browse all studies below.
Data pulled October 24, 2026
Studies per year
Publications by calendar year; the current year is to-date.
By continent
Studies grouped by the continent of each contributing country.
Studies by species
Animal model studied (top 10 by study count).
Top countries
Most studies by country (top 20).
All institutions
Every contributing institution by study count (number of studies shown at left); each counted once per study it contributed to.
Behaviours automated
INDICATIVE, NOT EXHAUSTIVE. What SimBA was used to score, read from the methods text of the collected papers: a behaviour counts once per study when it is named near a SimBA mention and near a classifier/scoring cue. Most studies score several. Keyword-based, so uncommon behaviours may be undercounted.
Brain regions
INDICATIVE, NOT EXHAUSTIVE. Papers naming each region anywhere in their full text.
Methods & tools
INDICATIVE, NOT EXHAUSTIVE. What the studies pair SimBA with — recording methods, molecular assays, and the other behaviour tools they cite.
Disease & behavioural models
INDICATIVE, NOT EXHAUSTIVE. Models, conditions and paradigms the papers study.
What SimBA has been used for
Concepts appearing across the full text of 185 downloaded studies — methods, behaviours, brain regions, models and compounds. Larger = mentioned in more papers. Brain-region terms sit in their own region; other colors only show where a word landed. Showing 132 of 165 concepts. Keyword-based overview (indicative, not exhaustive). Updated October 20, 2026.
Full list of studies (spreadsheet) → · one entry per study · multi-country studies counted in each country
📚 Browse all studies
Search across titles, authors, institutions and use-case descriptions, filter by species, year or publication type, and click a row to see what SimBA was used for.
Data pulled October 24, 2026 · 165 studies (98 peer-reviewed, 67 preprints)
| Year | Study | Species | Countries |
|---|
Click a row to see how SimBA was used · Source spreadsheet →
📑 How to cite SimBA
Using SimBA in your research? Please cite the SimBA paper:
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
Goodwin, Nastacia L., et al. “Simple Behavioral Analysis (SimBA) as a Platform for Explainable Machine Learning in Behavioral Neuroscience.” Nature Neuroscience, vol. 27, no. 7, 2024, pp. 1411–24, https://doi.org/10.1038/s41593-024-01649-9.
Goodwin, Nastacia L., Jia J. Choong, Sophia Hwang, Kayla Pitts, Liana Bloom, Aasiya Islam, Yizhe Y. Zhang, et al. “Simple Behavioral Analysis (SimBA) as a Platform for Explainable Machine Learning in Behavioral Neuroscience.” Nature Neuroscience 27, no. 7 (2024): 1411–24. https://doi.org/10.1038/s41593-024-01649-9.
Goodwin, N.L. et al. (2024) ‘Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience’, Nature Neuroscience, 27(7), pp. 1411–1424. Available at: https://doi.org/10.1038/s41593-024-01649-9.
Goodwin NL, Choong JJ, Hwang S, Pitts K, Bloom L, Islam A, et al. Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience. Nat Neurosci. 2024;27(7):1411–24. doi: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}
}
TY - JOUR AU - Goodwin, Nastacia L. AU - Choong, Jia J. AU - Hwang, Sophia AU - Pitts, Kayla AU - Bloom, Liana AU - Islam, Aasiya AU - Zhang, Yizhe Y. AU - Szelenyi, Eric R. AU - Tong, Xiaoyu AU - Newman, Emily L. AU - Miczek, Klaus AU - Wright, Hayden R. AU - McLaughlin, Ryan J. AU - Norville, Zane C. AU - Eshel, Neir AU - Heshmati, Mitra AU - Nilsson, Simon R. O. AU - Golden, Sam A. TI - Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience JO - Nature Neuroscience VL - 27 IS - 7 SP - 1411 EP - 1424 PY - 2024 DO - 10.1038/s41593-024-01649-9 UR - https://doi.org/10.1038/s41593-024-01649-9 ER -
The .ris file imports into Mendeley, EndNote, Zotero and most other reference managers. You can also paste the DOI (10.1038/s41593-024-01649-9) into your manager's “add by identifier” option.
SimBA works alongside other open-source tools. Please also cite the pose-estimation software and any other packages your analysis used.