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A connectome-constrained deep mechanistic network (DMN) model of the fruit fly visual system in PyTorch.

  • Explore connectome-constrained models of the fruit fly visual system.
  • Generate and test hypotheses about neural computations.
  • Try pretrained models on your data.
  • Develop custom models using our framework.

Flyvis is our official implementation of Lappalainen et al., "Connectome-constrained networks predict neural activity across the fly visual system." Nature (2024).

Documentation

For detailed documentation, installation instructions, tutorials, and API reference, visit our documentation website.

Tutorials

Explore our tutorials to get started with flyvis. You can read the prerun tutorials in the docs or try them yourself for a quick start in Google Colab:

  1. Explore the Connectome

  2. Train the Network on the Optic Flow Task

  3. Flash Responses

  4. Moving Edge Responses

  5. Ensemble Clustering

  6. Maximally Excitatory Stimuli

  7. Custom Stimuli

Main Results

Find the notebooks for the main results in the documentation.

Citation

@article{lappalainen2024connectome,
	title = {Connectome-constrained networks predict neural activity across the fly visual system},
	issn = {1476-4687},
	url = {https://doi.org/10.1038/s41586-024-07939-3},
	doi = {10.1038/s41586-024-07939-3},
	journal = {Nature},
	author = {Lappalainen, Janne K. and Tschopp, Fabian D. and Prakhya, Sridhama and McGill, Mason and Nern, Aljoscha and Shinomiya, Kazunori and Takemura, Shin-ya and Gruntman, Eyal and Macke, Jakob H. and Turaga, Srinivas C.},
	month = sep,
	year = {2024},
}

Links

Correspondence

For questions or inquiries, please contact us.

Project links

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License

MIT License

Requires

Python <3.13, >=3.9

Provides Extra

dev docs examples pretrained

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