New #paper alert! Here, we show that #auditory #stimulation can be used to selectively #suppress slow wave #sleep by 30% without affecting total sleep time. onlinelibrary.wiley.com/doi/10.1111/js…

#PeerReview from eLife - the journal of 👉🏿 Uncertainty-modulated prediction errors in cortical microcircuits biorxiv.org/content/10.110… #biorxiv #reviewedpreprint

François Chollet a cool recent paper on cortical circuit function is this one, Bengio was actually a co-author on it has cool ties with predictive coding, biologically plausible/backprop free learning biorxiv.org/content/10.110…

Increased perceptual reliability reduces membrane potential variability in cortical neurons biorxiv.org/cgi/content/sh… #biorxiv_neursci

Prospective and retrospective coding in cortical neurons. arxiv.org/abs/2405.14810

What’s the point of strong spike frequency adaptation in serotonin neurons? This new work offers a clue: adaptation lets neurons broadcast a prediction of their future output, preventing slow downstream regions from lagging behind. 💡 doi.org/10.48550/arXiv…

Prospective and retrospective coding in cortical neurons. arxiv.org/abs/2405.14810

Hierarchy of prediction errors shapes the learning of context-dependent sensory representations biorxiv.org/cgi/content/sh… #biorxiv_neursci

coolest conference souvenir: electronic neuron circuit lu.i on this board: an implementation of a leaky integrate and fire neuron, with the membrane voltage visualized with LEDs (or connect an oscilloscope to see the traces).

🏷️:Unsigned temporal difference errors in cortical L5 dendrites during learning 🔗:doi.org/10.1101/2021.1…

Jérôme Lecoq You’ll need to add this one to the graph! Beautiful work from Walter Senn and colleagues: biorxiv.org/content/10.110…

Happy to have participated and presented our work at the last Bernstein Network Computational Neuroscience!

And two posters: "DelGrad: Exact gradients in spiking networks for learning transmission delays and weights" (P. Lake) "Emergence of Synfire Chains in Functional Multi-Layer Spiking Neural Networks" (J. Göltz) Universität Bern EBRAINS #BernsteinConference

🧠 Forschende der #unibern haben ein Modell entwickelt, das zeigt, wie KI-Systeme Bewusstsein erlangen könnten. Sie schlagen den „Human-AI Deal“ vor, um den Umgang zwischen Mensch und Maschine zu regeln: sohub.io/9xl6. Faculty of Medicine, University of Bern

Pleased to present our latest paper with Cyriel Pennartz in AI & Ethics, thanks to our fruitful collaboration made possible by Human Brain Project "The conductor model of consciousness, our neuromorphic twins, and the human-AI deal" rdcu.be/dXhWz &👇Universität Bern Press Release

Happy to present today and tomorrow three of our projects at #SNUFA24 Go Team!

📣 Elections for the new OCNS Directors are now open. All current OCNS members are eligible to vote. Candidates info page: lnkd.in/dyjqmiTa Voting page: lnkd.in/dgtni5jT Election procedures: lnkd.in/dVnyfc6 Hurry up. The deadline is tomorrow 📅

Happy to see that our open source palm-sized analogue neuromorphic hardware Lu.i are used to explain key neuromorphic engineering concepts! carsales.com.au/editorial/deta…

For more details see our repo github.com/giant-axon/lu.… and the preprint our researchers from Universität Bern and Electronic Vision(s) - in memoriam Karlheinz Meier published arxiv.org/abs/2404.16664

DreamOn: a data augmentation strategy to narrow the robustness gap between expert radiologists and deep learning classifiers frontiersin.org/journals/radio…