All-GCL: A large-scale dataset of functional mouse ganglion cell layer responses

This repository accompanies the manuscript "All-GCL: A large-scale dataset of functional mouse ganglion cell layer responses" and provides code for reproducing the main figures, loading the dataset, and exploring the data through tutorials. All-GCL contains functional recordings from more than 80,000 mouse ganglion cell layer neurons, together with standardized metadata, pretrained classifiers, tutorials, and analysis code for reproducible neuroscience.

Preprint: bioRxiv

Contents

• Usage
• Data and Related Resources
• Authors and Acknowledgements
• Citation
• License

Usage

1. Download the data from Hugging Face.

2. Clone this repository:

   git clone https://github.com/eulerlab/all-GCL-manuscript.git
   cd all-GCL-manuscript

3. Install the package using uv:

   uv sync

4. Configure the dataset path by updating dataset_dir in config.yaml to point to the folder containing the downloaded data.

5. Tutorial: Open the tutorial notebook tutorial notebook or figures notebooks like Fig2_dataset_overview in jupyter for example via uv:

   uv run --with jupyter jupyter lab

Data and Related Resources

• Dataset (NWB format):
  Publicly available at Hugging Face:
  https://huggingface.co/datasets/eulerlab/all-gcl

• Stimulus documentation:
  Detailed descriptions and implementation of visual stimuli (QDSpy):
  https://github.com/eulerlab/QDSpy-stimuli-Documentation

• GCL classifier:
  Code and pretrained models for functional cell-type classification:
  https://github.com/eulerlab/gcl_classifier

• djimaging:
  DataJoint schema and tables used to generate this dataset originally (see djimaging/README.md for details):
  https://github.com/eulerlab/djimaging/releases/tag/all-gcl-v0.1.0

Authors and Acknowledgements

Dominic Gonschorek^#,1,2, Jonathan Oesterle^#,1-3, Thomas Zenkel^#,1,2, Federico D'Agostino^#,2,4, Katrin Franke^1,5-7, Ryan Arlinghaus^1,2, Chenchen Cai^1,2, Florentyna Deja^1,2, Nadine Dyszkant^1,2, Tom Schwerd-Kleine^1,2, Klaudia Szatko^1,2, Timm Schubert^1,2, Philipp Berens^1-4, Thomas Euler^1,2,+

^#These authors contributed equally

¹Institute for Ophthalmic Research, University of Tübingen, Tübingen, Germany

²Werner Reichardt Centre for Integrative Neuroscience, University of Tübingen, Tübingen, Germany

³Hertie Institute for Artificial Intelligence in Brain Health, University of Tübingen, Tübingen, Germany

⁴Tübingen AI Center, University of Tübingen, Germany

⁵Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, USA

⁶Stanford Bio-X and Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA

⁷Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA

Correspondence: thomas.euler@cin.uni-tuebingen.de

Citation

If you use this dataset, please cite:

Gonschorek et al. (2025) "A large-scale dataset of functional mouse ganglion cell layer responses" bioRxiv
https://www.biorxiv.org/content/10.64898/2025.12.04.691221v1

If you use data originating from one or more published studies included in this dataset, please also cite the corresponding original publications:

• Szatko, Klaudia P., et al. "Neural circuits in the mouse retina support color vision in the upper visual field." Nature communications 11.1 (2020): 3481.

• Höfling, Larissa, et al. "A chromatic feature detector in the retina signals visual context changes." Elife 13 (2024): e86860.

• Gonschorek, Dominic, et al. "Nitric oxide modulates contrast suppression in a subset of mouse retinal ganglion cells." Elife 13 (2025): RP98742.

• Dyszkant, Nadine, et al. "Photoreceptor degeneration has heterogeneous effects on functional retinal ganglion cell types." The Journal of Physiology 603.21 (2025): 6599-6621.

License

This repository is licensed under the MIT License. The dataset is distributed under CC-BY-NC-ND 4.0 International license.