Federico D’Agostino
@fededagos.bsky.social
360 followers 380 following 11 posts
PhD student @ Uni Tübingen | @bethgelab.bsky.social | Computational Neuroscience & ML
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fededagos.bsky.social
Thanks for sharing this!
I was not aware of it but looks really relevant. No problem if your lab is no longer working on this much, we will try to incorporate it in the future and reach out if we have any trouble 😉
This is exactly the kind of engagement we hoped to get!
fededagos.bsky.social
Try it out and help us improve the accessibility of retinal datasets and models together.

A team effort with:
@thomaszen.bsky.social
@dgonschorek.bsky.social
@lhoefling.bsky.social
@teuler.bsky.social
@bethgelab.bsky.social

#openscience #computationalneuroscience (9/9)
fededagos.bsky.social
This is just the beginning.
We see openretina as more than a Python package—it aims to be the start of an initiative to foster open collaboration in computational retina research.
We’d love your feedback! (8/9)
fededagos.bsky.social
Researchers can use openretina to:
✅ Explore pre-trained models in minutes
✅ Train their own models
✅ Contribute datasets & models to the community (7/9)
fededagos.bsky.social
The currently supported models follow a Core + Readout architecture:
🔸 Core: Extracts shared retinal features across data recording sessions
🔸 Readout: Maps shared features to individual neuron responses
🔹 Includes pre-trained models & easy dataset loading (6/9)
fededagos.bsky.social
Why does it matter?
Current retina models are often dataset-specific, limiting generalization.
With OpenRetina, we integrate:
🐭 🦎 🐒 Data from multiple species
🎥 Different stimuli & recording modalities
🧠 Deep learning models that can be trained across datasets (5/9)
fededagos.bsky.social
What is openretina?
It’s a Python package built on PyTorch, designed for:
🔹 Training deep learning models on retinal data
🔹 Sharing and using pre-trained retinal models
🔹 Cross-dataset, cross-species comparisons
🔹 In-silico hypothesis testing & experiment guidance (4/9)
fededagos.bsky.social
Understanding the retina is crucial for decoding how visual information is processed. However, decades of data and models remain scattered across labs and approaches. We introduce openretina to unify retinal system identification. (2/9)
fededagos.bsky.social
🚨 New paper alert! 🚨
We’ve just launched openretina, an open-source framework for collaborative retina modeling across datasets and species.
A 🧵👇 (1/9)
fededagos.bsky.social
Incredibly honoured to have been a part of this!
maxime-beau.bsky.social
I am very proud to announce that my PhD paper finally came out in Cell! In this *very* collaborative study, we develop and release a deep-learning approach to predict neuron type identity from their electrical signature. doi.org/10.1016/j.ce... 1/16 🧵