(1/8) New paper from our team! Yu Duan & Hamza Chaudhry introduce POCO, a tool for predicting brain activity at the cellular & network level during spontaneous behavior. Find out how we built POCO & how it changes neurobehavioral research 👇 arxiv.org/abs/2506.14957

🚨 The call for demos is still open, the deadline is tomorrow! If you have a tool for visualizing large-scale data, pipelines for training foundation models, or BCI demos, we want to see it! Submission is only 500 words, and it's a great opportunity to showcase your work.

Excited to announce the Foundation Models for the Brain and Body workshop at #NeurIPS2025! 🧠📈 🧪 We invite short papers or interactive demos on AI for neural, physiological or behavioral data. Submit by Aug 22 👉 brainbodyfm-workshop.github.io

POSSM shows that monkey-to-human transfer works 🤯 This could change how we train neuro-foundation models. Multi-species pretraining! POYO x SSM = POSSM 🧠⚡ A big step toward real-time, generalizable brain decoders at scale. 🧠📈 🧪

New preprint! 🧠🤖 How do we build neural decoders that are: ⚡️ fast enough for real-time use 🎯 accurate across diverse tasks 🌍 generalizable to new sessions, subjects, and even species? We present POSSM, a hybrid SSM architecture that optimizes for all three of these axes! 🧵1/7

Our EEG-Foundation Challenge, on more than 3,000 subjects, is accepted at #Neurips 2025, go check it out: eeg2025.github.io Led by B Aristimunha D Truong P Guetschel and SY Shirazi!

Neural Encoding and Decoding at Scale (NEDS) is now accepted to @icmlconf.bsky.social as a spotlight (top 2.6%)! 🧠 🧪

Check out our new paper at #ICLR2025, where we show that multi-task neural decoding is both possible and beneficial. As well, the latents of a model trained only on neural activity capture information about brain regions and cell-types. Step-by-step, we're gonna scale up folks! 🧠📈 🧪 #NeuroAI

Scaling models across multiple animals was a major step toward building neuro-foundation models; the next frontier is enabling multi-task decoding to expand the scope of training data we can leverage. Excited to share our #ICLR2025 Spotlight paper introducing POYO+ 🧠 poyo-plus.github.io 🧵

Another step toward a foundation model of the mouse brain: "Neural Encoding and Decoding at Scale (NEDS)" Trained on neural and behavioral data from 70+ mice, NEDS achieves state-of-the-art prediction of behavior (decoding) and neural responses (encoding) on held-out animals. 🐀

Interested in foundation models for #neuroscience? Want to contribute to the development of the next-generation of multi-modal models? Come join us at IVADO in Montreal! We're hiring a full-time machine learning specialist for this work. Please share widely! #NeuroAI 🧠📈 🧪

#COSYNE2025 tutorial by Eva Dyer. Foundations of Transformers in Neuroscience youtu.be/CqS_sIrMZ2A... Materials: cosyne-tutorial-2025...#COSYNE2025

Really enjoyed TAing for this tutorial, had great discussions with several attendees. Do check out `torch_brain` and the other packages here: github.com/neuro-galaxy

Talk recordings from our COSYNE Workshop on Neuro-foundation Models 🌐🧠 are now up on the workshop website! neurofm-workshop.github.io

Come to my talk today at #COSYNE2025 where I will talk about developing spatiotemporal models of brain dynamics

Thanks to everyone who came to Day 1 of the Workshop! I had fun making this plot for the opening talk. It's exciting to see the exponential growth in the amount of pretraining data 🚀 I compiled a list of neuro-foundation models for EPhys and OPhys: github.com/mazabou/awes...

I'll be giving a talk at the foundation model workshop #Cosyne2025 tomorrow: neurofm-workshop.github.io In response to @thetransmitter.bsky.social article by @tyrellturing.bsky.social & Eva Dyer I'll be talking about: How do "foundation"/AI models help us (experimenters) study the brain?

Eva Dyer and I wrote an opinion piece for @thetransmitter.bsky.social on why neuroscience needs to embrace complexity and accept the "bitter lesson" by using a data-driven regime at scale. With commentary from several wonderful researchers! 🧠📈 #NeuroAI 🧪

Cosyne is this week! Looking forward to catching up with whoever is there. :-) #Cosyne2025 If you are sticking around for workshops, come checkout our 2-day workshop on building foundation models for the brain: neurofm-workshop.github.io 🧠 🧪

Join us at this #COSYNE2025 workshop to discuss foundation models for neuroscience!!! #neuroscience #NeuroAI #MLSky 🧪

Join us at #COSYNE2025 to explore recent advancements in large-scale training and analysis of brain data! 🧠🟦 We also made a starter pack with (most of) our speakers: go.bsky.app/Ss6RaEF

How can large-scale models + datasets revolutionize neuroscience 🧠🤖🌐? We are excited to announce our workshop: “Building a foundation model for the brain: datasets, theory, and models” at @cosynemeeting.bsky.social #COSYNE2025. Join us in Mont-Tremblant, Canada from March 31 – April 1!

Ported over from X! What will a foundation model for the brain look like? 🧠 We argue that it must be able to solve a diverse set of tasks across multiple brain regions and animals. Check out our NeurIPS paper which introduces a multi-region, multi-animal, multi-task model arxiv.org/abs/2407.14668

Excited to release what we’ve been working on at Amaranth Foundation, our latest whitepaper, NeuroAI for AI safety! A detailed, ambitious roadmap for how neuroscience research can help build safer AI systems while accelerating both virtual neuroscience and neurotech. 1/N

This study shows that spike sequences carry information beyond what rates and latency to first spike do: www.nature.com/articles/s41... My reactions: 1) Cool to see this in humans. 2) Are people still surprised that spike times carry information beyond rates/first-spike latency?!?!?! 🧠📈 🧪

Ok, so I wanted to try my hand at building a starter pack too :-). This pack includes developers of tools and methods for electrophysiology (focused on extracellular recordings). Please let me know if I missed anyone! Also, we need more people from X to switch to fill this out! go.bsky.app/DFWsuTJ

How can we extract insights from behavior modulated by multiple complex factors? 🐭🪰🤖🏃 Check out our #NeurIPS2023 Spotlight Paper where we present a SSL method for learning multiscale representations of behavior! 🧠🟦 Link: multiscale-behavior.github.io

Awesome work led by @mehdiazabou.bsky.social and @evadyer.bsky.social towards unifying large scale datasets into a single model. The real gem here is the spike tokenization, super clever way to solve a key problem. Check it out!

Neural spiking data and Transformers are a tricky match. Temporal segmentation and tokenization are the crux. Together with an all-star team, we figured out a scalable way to solve this. The results are exciting: training and transferring on multi-sessions, multi-subjects neural decoding tasks.

Check out this new paper! Led by @mehdiazabou.bsky.social and @evadyer.bsky.social, we show that it is possible to get SOTA brain decoding with transfer across individuals and tasks! The key is a clever way to tokenize spiking data for transformers. #neuroskyence #brain #neurotech

Dope paper on multi-subject, multi-session universal decoders for neural spike data. The key to making it all work? Spike embeddings! Same idea as word embeddings, map discrete tokens to a continuous space #neuroskyence

Is a universal brain decoder possible? Can we train a decoding system that easily transfers to new individuals/tasks? Check out our #NeurIPS2023 paper where we show that it’s possible to transfer from a large pretrained model to achieve SOTA! 🧠🟦 Link: poyo-brain.github.io 🧵