https://github.com/eulerlab/hybrid-model

Efficient coding of natural scenes for neural system identification
https://github.com/eulerlab/hybrid-model

Last synced: 12 months ago
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Efficient coding of natural scenes for neural system identification

• Host: GitHub
• URL: https://github.com/eulerlab/hybrid-model
• Owner: eulerlab
• License: mit
• Created: 2023-02-24T13:19:52.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2023-04-25T13:33:56.000Z (about 3 years ago)
• Last Synced: 2025-03-21T17:55:00.966Z (over 1 year ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 12.2 MB
• Stars: 1
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# hybrid-model

Efficient coding of natural scenes for neural system identification.

This repository contains scripts, notebooks and data [links](https://doi.org/10.5281/zenodo.7656868) related to our manuscript:

Yongrong Qiu, David A. Klindt, Klaudia P. Szatko, Dominic Gonschorek, Larissa Hoefling, Timm Schubert, Laura Busse, Matthias Bethge, Thomas Euler (2023). Efficient coding of natural scenes improves neural system identification. PLoS Comput Biol 19(4): e1011037. [https://doi.org/10.1371/journal.pcbi.1011037](https://doi.org/10.1371/journal.pcbi.1011037).