In case it helps anyone: I just put 6+ million conductance-based neuron simulations (STG & DA models) on Zenodo. Took a few days of cluster time to generate. Spike trains with various sampling strategies and noise levels, ready to use.
Code and information : shorturl.at/BAALO
🦋 We’re now on Bluesky!
The Neuroengineering Lab at University of Liège studies intelligence from neurons to hardware.
Follow our journey 👇
🌍 www.neuroengineering.uliege.be
🐦 X: x.com/NeuroEngULiege
🟦 LinkedIn: www.linkedin.com/company/neur...
#Neuroengineering #Neuromorphic #BrainInspired #AI
Great to welcome a local TV crew into our lab! 🎥🧠
We had the pleasure of hosting the LABO4 team for a behind-the-scenes look at our daily research on the mysteries of the human brain.
Catch the segment tonight at 19:30 on QU4TRE!
👉 www.news.uliege.be/cms/c_206393...
Once you get past the first 5 minutes of me bumbling around clearly in need of media training, we settle into a nice groove talking about fitting mechanistic models, ML/AI for neuroscience, underconstrainedness vs. degeneracy, and its potential benefits for biology (plus some good chuckles).
We’ve heard a lot about deep nudes and sexual deepfakes made without consent. Yet for weeks now, social media platforms from Meta have been running ads for deepfake apps, available directly on the App Store. I’ve reported at least 5 of them in the past 2 weeks. How did this become normalized?
"Une partie des dizaines de milliers de livres, documents et revues qu’accueillait l’établissement sera jetée à la poubelle"
www.huffingtonpost.fr/internationa...
Those abuses are real, but they’re not the same story as AI used for discovery, modeling, or understanding nature.
We probably need to be much clearer (and push the media to do the same...) about which "AI" we’re talking about, and not let the worst uses define the whole field.
At the same time, there are obvious bad uses that are sensational, harmful, and media-friendly (non-consensual sexual image manipulation, scams, etc.).
I think part of the problem is that "AI" has collapsed into a single word covering wildly different things. AI for science has already delivered real, measurable progress and will clearly continue to do so.
The review process for COSYNE 2026 is now complete. We are pleased to inform you that your submission #11: "Neuronal population inference reveals how neuromodulation reshapes conductance space" has been accepted to COSYNE 2026 for a POSTER presentation. Congratulations!
Excited to be at #COSYNE2026! 🧠
We’ll present a poster in #computational #neuroscience on population inference and #neuromodulation plausible targets investigation, extending our NeurIPS workshop work.
The COSYNE 2026 abstract is available here: hdl.handle.net/2268/339005
Super interesting talk! Perceptions and actions shouldn’t be viewed as opposite or orthogonal concepts, but rather as two sides of the same coin under the Bayesian brain hypothesis.
Thanks for this talk @cpehlevan.bsky.social ! The call for a science of "AI for Science" and for caution when interpreting learned mechanisms in a purely data-driven context was particularly insightful.
Why can neurons with completely different ion channels fire identically? 🧠
Neuronal degeneracy isn't a bug - it's a feature. Come see how we reconstruct entire degenerate populations from spike times within an interpretable feedback framework.
Poster @dataonbrainmind.bsky.social
#NeurIPS2025 #DBM
Curious? You can find our extended abstract on ORBi: hdl.handle.net/2268/336182
And check out our recent preprint on the same topic here:
- arXiv: arxiv.org/abs/2509.12783
- ORBi: hdl.handle.net/2268/335923
Damien Ernst, Guillaume Drion and Arthur Fyon
Thrilled to announce that our work on reconstructing degenerated neuronal populations has been accepted at the NeurIPS 2025 Workshop on Data on the Brain & Mind 🎉
I will be in San Diego in early December to present a poster, and I’m really looking forward to it!
A schematics of the computational approach we used.
🧠✨ Thrilled to announce my FIRST preprint is now live! ✨🧠
Sharing my first research paper on arXiv, tackling a challenge in computational neuroscience.
📄 arXiv preprint: arxiv.org/abs/2509.12783
📚 ORBi (with supplementary materials): hdl.handle.net/2268/335923
