Very nice paper that came out of a new collaboration between @jsenk.bsky.social and @neworderofjamie.bsky.social we started a while ago. Structural plasticity helps strike the balance between using sparse connectivity (*not* full matrices with loads of zeros) and being able to change it on the go.

This paper shows alignment between LLMs and brain data is outperformed by a null model. More evidence for the argument I've been making in talks lately that we shouldn't believe any computational paper that puts less effort into null than main model. www.biorxiv.org/content/10.1...

We're organising a "Neuromorphic hardware and algorithms" workshop at Sussex on 11th-12th of June 2026. Expect keynotes by Chiara Bartolozzi and André van Schaik as well as awesome ECR speakers. (Free) registration now open at genn-team.github.io/workshop2026/. Accepting abstracts until March 31st!

state of the LLMs: Measuring the impact of Qwen, DeepSeek, Llama, GPT-OSS, Nemotron, and all of the new entrants to the ecosystem Impressive tipping point that happened during 2025 www.interconnects.ai/p/8-plots-th...

Some things we learned: 1. CA1 pyramidal neuron dendritic voltage dynamics during behavior are low-dimensional, well described by just two or three compartments (basal, soma, apical). This rules out models in which dendritic branches act as distinct computational compartments.

We're ending 2025 with a bang! I'm really proud to be part of the amazing team that produced this comprehensive perspective on "How #heterogeneity shapes dynamics and computation in the #brain" (and in #neuromorphic systems, I add 😇): authors.elsevier.com/sd/article/S...

I’m very grateful to the FMI, the tenure committee, inspiring colleagues, and all the hidden supporters who made this possible. Huge thanks to past and present group members for their curiosity and creativity. Excited for the next chapter.

Always such a vibrant NeuroAI community in Montreal !

Yet another commentary (and rant) on why following the original #neuromorphic approach, using *also* #analog circuits to emulate the physics of cortical circuits, can be fascinating: www.pnas.org/doi/10.1073/...

In our latest D-ITET professor series interview, Prof. Laura Bégon-Lours shares insights into neuromorphic computing and ferroelectric oxides – and she explains why these technologies could transform remote devices, wearables, and smart implants. Read the full interview: ee.ethz.ch/news-and-eve...

Excellent research on Time Modulated Arrays: Prof. Hua Wang’s Integrated Devices, Electronics, and Systems (IDEAS) Group has received the Top-10 Key Achievement Award from the Smart Networks and Services Joint Undertaking in 2025. Congratulations! Read more: ee.ethz.ch/news-and-eve...

"Spiking Networks Hate It! Find Out the One Plasticity Trick They Don’t Want You to Know! Never stabilise models by hand again." - I woke up thinking we missed an opportunity with the title of this one. :/ www.science.org/doi/10.1126/... Also: It snowed in Vienna, 10cm white fluffies! Happy Sunday!

With my great advisors and colleagues, @achterbrain.bsky.social @zhe @danakarca.bsky.social @neural-reckoning.org, we show that if heterogeneous axonal delays (imprecise) can capture the essential temporal structure of a task, spiking networks do not need precise synaptic weights to perform well.

Honored (and scared) of being invited to give the keynote lecture on #neuromorphic for NER at IEEE EMBS 12th Annual International Conference on #NeuralEngineering (neuro.embs.org/2025/) Slides available here: bit.ly/3Jspfek

Oct 30, 4:30 "How does the Geometry of Brain Activity Shape Behavior?" Valeria Fascianelli; moderator Stefano Fusi, Zuckerman Institute, Columbia. Open seminars series; register here: tinyurl.com/379uda2z @valeriafascianelli.bsky.social , @columbiauniversity.bsky.social, @stefanofusi.bsky.social

Inspiring perspective paper by Prof. Giacomo Indiveri in Neuron. In this interview, he talks about the term “neuromorphic”, the uniqueness of the Institute of Neuroinformatics and comparisons with artificial intelligence. Read more: ee.ethz.ch/news-and-eve... @giacomoi.bsky.social

#Spiking #neural #networks ( #SNN ) running on continuous-time, noisy, and highly variable computing substrates can learn reliably with #ReinforcementLearning ... Not only in real brains, but also in mixed-signal #neuromorphic hardware! 😇

#Spiking #neural #networks (#SNN) running on continuous-time, noisy, and highly variable computing substrates can learn reliably with #ReinforcementLearning ... Not only in real brains, but also in mixed-signal #neuromorphic hardware! 😇 Neuromorphic dreaming […] [Original post on fediscience.org]

#Spiking neural networks running on continuous-time, noisy, and high;y variable computing substrates can learn reliably... Not only in real brains. Also in mixed-signal #neuromorphic hardware 😇 Neuromorphic dreaming as a pathway to efficient learning in artificial agents www.doi.org/10.1088/2634...

A thought-provoking perspective from the visionary @giacomoi.bsky.social, calling for neuromorphic computing to return to its root: fundamental neuroscience; an inspiring vision for the future of NeuroAI 🤩

What is this "neuromorphic" hype all about? Here's my (neuro)view on it: https://authors.elsevier.com/a/1ltRg3BtfHC-Jf

Curious about the meaning of "neuromorphic"? Here's my latest NeuroView on this topic: www.cell.com/neuron/fullt...

Exciting news! Prof. Dr. Melika Payvand is joining D-ITET as Tenure Track Assistant Professor of Autonomous Intelligent Agents. Congratulations!

Yeah robots are definitely not taking over the world. Not the red one, at least. 🤣

Publishing in Neuromorphic Computing and Engineering means more visibility and higher impact: 📊 Impact Factor: 6.1 📶 Citescore: 9.2 🥇 Q1 JCR subject ranking ⏱️ 7-day median to first decision Join the leaders shaping neuromorphic innovation! iopscience.iop.org/journal/2634... #MaterialsScience

Is it possible to go from spikes to rates without averaging? We show how to exactly map recurrent spiking networks into recurrent rate networks, with the same number of neurons. No temporal or spatial averaging needed! Presented at Gatsby Neural Dynamics Workshop, London.

Introducing our new favorite stimulus. A few minutes are enough to map the visual preferences of thousands of neurons. Mapping the visual cortex with Zebra noise and wavelets www.biorxiv.org/content/10.1... By Sophie Skriabine and Max Shinn, with Samuel Picard and @kenneth-harris.bsky.social

Trying to train RNNs in a biol plausible (local) way? Well, try our new method using predictive alignment. Paper just out in Nat. Com. Toshitake Asabuki deserves all the credit! www.nature.com/articles/s41...

Looking forward to speaking at the first Biohybrid Robotics Conference tomorrow! biohybrid-robotics.com

Thanks to Maryada (@giacomoi.bsky.social lab)! Due to component variability it is hard to set the weights across neuromorphic devices. Using our crosshomeostatic learning rule, that governs all four weight classes, we drove neuromorphic RNNs into balanced E/I regimes. www.nature.com/articles/s41...

I'm extremely proud of the work of Maryada, Saray Soldado-Magraner and colleagues, in collaboration with Dean Buonomano, which shows how their cross-homeostatic #plasticity model enables analog #neuromorphic #circuits to produce stable recurrent dynamics on our DYNAP-SE

I'm extremely proud of the work of Maryada, Saray Soldado-Magraner and colleagues, in collaboration with @deanbuono.bsky.social which shows how their #cross-homeostatic #plasticity model enables analog #neuromorphic #circuits to produce stable recurrent dynamics on our chips!!! rdcu.be/euiv2

This is the smartest damn thing I’ve heard all year. If nothing else, it might serve to erode employers‘ trust in ChatGPT.

Fusing multisensory signals across channels and time. Now published at PLOS Comp Biol! 🎉 With @swathianil.bsky.social and @marcusghosh.bsky.social. journals.plos.org/ploscompbiol... TLDR, when multisensory signals vary over time, neural architecture becomes important. Biggest not always best.

The firing of neural populations is high-dim even if their subthreshold activity is low-dim! This work by @bio-emergent.bsky.social and @haydari.bsky.social shows how, with a solvable model, a data analysis technique, and data from mouse visual cortex: www.biorxiv.org/content/10.1...

Hot off the press! We take advantage of the intrinsic variability of #analog #neuromorphic circuits to create unique paintings with a #robotic artist. www.nature.com/articles/s41...

🧠 Neuromorphic Computing: Two Approaches, One Debate. Join leading researchers as they explore the future of brain-inspired computing. 📅 June 18 | 2 p.m. GMT / 9 a.m. EST Hosted by Neuromorphic Computing and Engineering Register now! 👉 ow.ly/Tbpr50VXETS #NeuromorphicComputing #Webinar

I'm about to char a special session on "#Neuromorphic Technology for Intelligent Edge Computing" at #ISCAS25 in London and present my view on using "Principles of #Neural Design for Implementing Efficient #Mixed-Signal #Neuromorphic Processors" 🙂 drive.switch.ch/index.php/s/...

1/6 Why does the brain maintain such precise excitatory-inhibitory balance? Our new preprint explores a provocative idea: Small, targeted deviations from this balance may serve a purpose: to encode local error signals for learning. www.biorxiv.org/content/10.1... led by @jrbch.bsky.social

Our team is hiring in Zurich! www.google.com/about/career...

One more step toward EEG based epileptic seizure detection using #neuromorphic #spiking neural network chips! rdcu.be/ek2SC Jim Bartels, Olympia Gallou, Hiroyuki Ito, Matthew Cook, Johannes Sarnthein, Giacomo Indiveri & Saptarshi Ghosh

Take our short 5-min anonymous survey on the Neuromorphic field’s current state & future: 📋 tinyurl.com/3jkszrnr 🗓️ Open until May 12, 2025 Results will be shared openly and submitted for publication. Your input will help us understand how interdisciplinary trends are shaping the field.

Here is how I have been comparing the two big hype phenomena in AI and robotics, in my recent talks. Spoiler alert: the hype is unfounded.

Yet another demonstration of how noisy analog #neuromorphic circuits can achieve impressive results in emulating real neural processing systems, implement always-on on-chip #learning, and solving practical #edge-computing applications! @giacomoi.bsky.social

I'm extremely proud of this work, which shows how using the physics of analog electronic circuits helps us understand learning and computational principles of cortical neural networks and build efficient neural processing systems that can complement and outperform AI accelerators in edge computing!

A canonical cortical electronic circuit for neuromorphic intelligence https://www.biorxiv.org/content/10.1101/2025.03.28.646019v1

I am really proud to announce that our latest effort on showing the advantages of our analog/digital #neuromorphic spiking neural network chips in solving complex biomedical applications has just been published here: https://rdcu.be/ef5N0 The demonstrates that *small* *highly variable* and *low […]