🚨🧠 Our paper is out! We introduce a simple computational model that generates macroscopic, long-timescale dynamics as seen in large-scale neural recordings. #neuroscience #dynamics @marius10p.bsky.social @zhong-lin.bsky.social @hhmijanelia.bsky.social Link: go.nature.com/4tRNjIu

Nature@nature.com · 3mo ago

Nature research paper: A critical initialization for biological neural networks go.nature.com/4tRNjIu

Here's what I think everyone is missing about this issue: Prediction is how we identify understanding! If we had a model that could do OOD prediction, then we would rightly say it understands. Of course, that doesn't mean understanding *necessarily* emerges from training to predict. #NeuroAI

The Transmitter @thetransmitter.bsky.social · 3mo ago

Prediction without understanding sustained astronomy through a thousand years of epicycles, writes @tonyzador.bsky.social. AI is now offering neuroscience the same deal. #neuroskyence www.thetransmitter.org/machine-lear...

New preprint out 🎉 What happens to the hippocampal “place code” when an animal is actively engaged in a task? The answer surprised us (and might surprise you too!). Let's dive in ⬇️ Link: "Hippocampal trace coding dominates and disrupts place coding" www.biorxiv.org/content/10.6...

🧪🧠 New preprint: helping resolve a decades-long debate in synaptic plasticity NMDA receptors are central to Hebbian learning. Yet for >30 years, the existence and function of presynaptic NMDA receptors have remained controversial. 📄 doi.org/10.64898/202... 1/6

New paper out at PNAS: www.pnas.org/doi/10.1073/... Revisiting the high-dimensional geometry of population responses in the visual cortex with @jpillowtime.bsky.social. The review took forever because a reviewer was doubtful our new estimator can infer eigenvalues beyond the rank of the data! (1/6)

Are you thinking about doing neuroscience outreach but want to make it more exciting or hands on? Check out RetINaBox! (A collab led by the Trenholm lab) We tried to bring the experience of experimental neuroscience to a classroom setting: www.eneuro.org/content/13/1... #neuroscience 🧪

RetINaBox: A Hands-On Learning Tool for Experimental Neuroscience

An exciting aspect of neuroscience is developing and testing hypotheses via experimentation. However, due to logistical and financial hurdles, the experiment and discovery component of neuroscience is...

eneuro.org

Whoaaa!! This is a fantastic effort, and an amazing resource. Huge congratulations to the authors! 🎉

Apurva Ratan Murty@apurvaratan.bsky.social · 8mo ago

Need more fMRI data (beyond the amazing NSD)? Introducing MOSAIC! Incredible effort led expertly by Ben Lahner, with help from grad student Mayukh Deb. Work in collaboration with the amazing Aude Oliva! @neurosky.bsky.social. More below..

Last day of poster sessions and presentations at @neuripsconf.bsky.social. Full schedule featuring Mila-affiliated researchers presenting their work at #NeurIPS2025 here mila.quebec/en/news/foll...

In San Diego attending #NeurIPS2025? Come to our poster to talk more about representation geometry in LLMs. 😃 🗓️ Friday 4:30-7:30 pm session 📍 Exhibit Hall C, D, E 🏁 Poster # 2502

Arna Ghosh@arnaghosh.bsky.social · 9mo ago

LLMs are trained to compress data by mapping sequences to high-dim representations! How does the complexity of this mapping change across LLM training? How does it relate to the model’s capabilities? 🤔 Announcing our #NeurIPS2025 📄 that dives into this. 🧵below #AIResearch #MachineLearning #LLM

(1/n) We are excited to share our new paper in Nature Communications, by Hagar Lavian (@hlavian.bsky.social) and team, revealing how the zebrafish brain integrates visual navigation signals! www.nature.com/articles/s41...

Visual motion and landmark position align with heading direction in the zebrafish interpeduncular nucleus - Nature Communications

How are various visual signals integrated in the vertebrate brain for navigation? Here authors show that different spatial signals are topographically organized and align to one another in the zebrafi...

nature.com

1/ Why does RL struggle with social dilemmas? How can we ensure that AI learns to cooperate rather than compete? Introducing our new framework: MUPI (Embedded Universal Predictive Intelligence) which provides a theoretical basis for new cooperative solutions in RL. Preprint🧵👇 (Paper link below.)

Population coding 🙌

The Transmitter @thetransmitter.bsky.social · 8mo ago

“I will die on the hill that population coding is the relevant level of encoding information in the brain.” In the latest “This paper changed my life,” Nancy Padilla-Coreano discusses a paper on mixed selectivity neurons. #neuroskyence www.thetransmitter.org/this-paper-c...

How I contributed to rejecting one of my favorite papers of all times, Yes, I teach it to students daily, and refer to it in lots of papers. Sorry. open.substack.com/pub/kording/...

How I contributed to rejecting one of my favorite papers of all time

I believe we should talk about the mistakes we make.

open.substack.com

This is an excellent blueprint on a very fascinating use of AI scientist! And the results and super cool and interesting! 🤩 I have been asked this when talking about our work on using powerlaws to study representation quality in deep neural networks, glad to have a more concrete answer now! 😃

Kenneth Harris@kenneth-harris.bsky.social · 9mo ago

1. New preprint resolving a conundrum in systems neuroscience with an AI scientist, and humans Reilly Tilbury, Dabin Kwon, @haydari.bsky.social, @jacobmratliff.bsky.social, @bio-emergent.bsky.social, @carandinilab.net, @kevinjmiller.bsky.social, @neurokim.bsky.social www.biorxiv.org/content/10.1...

Conrad Hal Waddington was born OTD in 1905. His “epigenetic landscape” is a diagrammatic representation of the constraints influencing embryonic development. On his 50th birthday, his colleagues gave him a pinball machine on the model of the epigenetic landscape. 🧪 🦫🦋 🌱🐋 #HistSTM #philsci #evobio

I’m looking for interns to join our lab for a project on foundation models in neuroscience. Funded by @ivado.bsky.social and in collaboration with the IVADO regroupement 1 (AI and Neuroscience: ivado.ca/en/regroupem...). Interested? See the details in the comments. (1/3) 🧠🤖

AI and Neuroscience | IVADO

ivado.ca

A tad late (announcements coming) but very happy to share the latest developments in my previous preprint! Previously, we show that neural representations for control of movement are largely distinct following supervised or reinforcement learning. The latter most closely matches NHP recordings.

Olivier Codol@oliviercodol.bsky.social · 2y ago

Here’s our latest work at @glajoie.bsky.social and @mattperich.bsky.social ‘s labs! Excited to see this out. We used a combination of neural recordings & modelling to show that RL yields neural dynamics closer to biology, with useful continual learning properties. www.biorxiv.org/content/10.1...

LLMs are trained to compress data by mapping sequences to high-dim representations! How does the complexity of this mapping change across LLM training? How does it relate to the model’s capabilities? 🤔 Announcing our #NeurIPS2025 📄 that dives into this. 🧵below #AIResearch #MachineLearning #LLM

Very cool study, with interesting insights about theta sequences and learning!

Abhilasha Joshi, PhD@rhythmicspikes.bsky.social · 11mo ago

1/ 🚨 New preprint! 🚨 Excited and proud (& a little nervous 😅) to share our latest work on the importance of #theta-timescale spiking during #locomotion in #learning. If you care about how organisms learn, buckle up. 🧵👇 📄 www.biorxiv.org/content/10.1... 💻 code + data 🔗 below 🤩 #neuroskyence

Together with @repromancer.bsky.social, I have been musing for a while that the exponentiated gradient algorithm we've advocated for comp neuro would work well with low-precision ANNs. This group got it working! arxiv.org/abs/2506.17768 May be a great way to reduce AI energy use!!! #MLSky 🧪

Log-Normal Multiplicative Dynamics for Stable Low-Precision Training of Large Networks

Studies in neuroscience have shown that biological synapses follow a log-normal distribution whose transitioning can be explained by noisy multiplicative dynamics. Biological networks can function sta...

arxiv.org

This looks like a very cool result! 😀 Can't wait to read in detail.

Samuel Liebana@samuel-liebana.bsky.social · last yr.

Does the brain learn by gradient descent? It's a pleasure to share our paper at @cp-cell.bsky.social, showing how mice learning over long timescales display key hallmarks of gradient descent (GD). The culmination of my PhD supervised by @laklab.bsky.social, @saxelab.bsky.social and Rafal Bogacz!

Fantastic work on Multi-agent RL from @dvnxmvlhdf5.bsky.social & @tyrellturing.bsky.social! 🤩

Dane Carnegie Malenfant@dvnxmvlhdf5.bsky.social · last yr.

Preprint Alert 🚀 Multi-agent reinforcement learning (MARL) often assumes that agents know when other agents cooperate with them. But for humans, this isn’t always the case. For example, plains indigenous groups used to leave resources for others to use at effigies called Manitokan. 1/8

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

Also, big shoutout to @quentin-garrido.bsky.social+gang and @aggieinca.bsky.social+gang for developing Rankme and Lidar, respectively. Reptrix incorporates these representation quality metrics. 🚀 Let's make it easier to select good SSL/foundation models. 💪

Arna Ghosh@arnaghosh.bsky.social · last yr.

Are you training self-supervised/foundation models, and worried if they are learning good representations? We got you covered! 💪 🦖Introducing Reptrix, a #Python library to evaluate representation quality metrics for neural nets: github.com/BARL-SSL/rep... 🧵👇[1/6] #DeepLearning

Are you training self-supervised/foundation models, and worried if they are learning good representations? We got you covered! 💪 🦖Introducing Reptrix, a #Python library to evaluate representation quality metrics for neural nets: github.com/BARL-SSL/rep... 🧵👇[1/6] #DeepLearning

Super cool paper! It formalizes a lot of ideas I have been mulling over the past year, and connects tons of historical ideas neatly. Definitely worth a read if you are working/interested in mechanistic interp and neural representations.

David Klindt@david-klindt.bsky.social · last yr.

🔵 New paper! We explore sparse coding, superposition, and the Linear Representation Hypothesis (LRH) through identifiability theory, compressed sensing, and interpretability. If you’re curious about lifting neural reps out of superposition, this might interest you! 🤓 arxiv.org/abs/2503.01824

Just over a week since I defended my 🤖+🧠PhD thesis, and the feeling is just sinking in. Extremely grateful to @tyrellturing.bsky.social for supporting me through this amazing journey! 🙏 Big thanks to all members of the LiNC lab, and colleagues at mcgill University and @mila-quebec.bsky.social. ❤️😁

Just giving this a boost for those who may not have seen it yet... we have a PI position (molecular and cellular basis of cognition) at The Hospital for Sick Children (Toronto). The position comes with an appointment at Assist/Assoc Prof level at U of T. Share widely! can-acn.org/scientist-se...

Come say hi at the noon poster session today in the East hall, poster #2201. 🚀 #NeurIPS2024

Arna Ghosh@arnaghosh.bsky.social · 2y ago

The problem with current SSL? It's hungry. Very hungry. 🤖 Training time: Weeks Dataset size: Millions of images Compute costs: 💸💸💸 Our #NeurIPS2024 poster makes SSL pipelines 2x faster and achieves similar accuracy at 50% pretraining cost! 💪🏼✨ 🧵 1/8

The problem with current SSL? It's hungry. Very hungry. 🤖 Training time: Weeks Dataset size: Millions of images Compute costs: 💸💸💸 Our #NeurIPS2024 poster makes SSL pipelines 2x faster and achieves similar accuracy at 50% pretraining cost! 💪🏼✨ 🧵 1/8