The Bonsai.ML project is a collection of packages built to target the Bonsai-Rx ecosystem, providing reactive infrastructure for machine learning operations.
In the Bonsai.ML - Examples repo, we provide example workflows, datasets, and demos for how to get started using the suite of Bonsai.ML packages that are currently available. We provide documentation for each example to illustrate how Bonsai.ML can be incorporated into Bonsai workflows.
For each Bonsai.ML package, check out the Getting Started page to learn more about how to run the example workflows yourself.
All of the datasets used in these examples can be found by going to: https://doi.org/10.5281/zenodo.10629221.
ZebrafishExampleVid.avi - provided by Nicholas Guilbeault in the Thiele lab at the University of Toronto. If you would like to refer to this data, please cite Guilbeault, N.C., Guerguiev, J., Martin, M. et al. (2021). BonZeb: open-source, modular software tools for high-resolution zebrafish tracking and analysis. Scientific Reports 11, 8148, https://doi.org/10.1038/s41598-021-85896-x.
ForagingMouseExampleVid.avi - provided by the Sainsbury Wellcome Centre Foraging Behaviour Working Group. (2023). Aeon: An open-source platform to study the neural basis of ethological behaviours over naturalistic timescales, https://doi.org/10.5281/zenodo.8413142
ReceptiveFieldSimpleCell.zip - provided by the authors of "Touryan, J., Felsen, G., & Dan, Y. (2005). Spatial structure of complex cell receptive fields measured with natural images. Neuron, 45(5), 781-791." https://doi.org/10.1016/j.neuron.2005.01.029
Development of this package was supported by funding from the Biotechnology and Biological Sciences Research Council [grant number BB/W019132/1].