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Super proud of PhD students Alessandro Marin Vargas and Alberto Chiappa for winning this challenge!! Alberto Chiappa already won it last year.

Really cool work that brings together lots of interesting threads!

Having talked a lot with Jonathan in the past couple years, this is a rocket ship to the forefront of the field. Get on it!

Bom dia CosyneMeeting Day1🤩 Thrilled to guide you through #Cosyne24! Come say 👋 Especially come say hello if you want to chat time series foundation models, generalizability, and getting the most out of your data 👏for👏all👏tasks👏 Here's a taste😉 x.com/SaberaTalukder…

Hi there, Lisbon 👋🏽 Next week, I’m presenting work from the lab in 2 #COSYNE2024 workshops with Tatiana Engel, Aldo Battista, Wayne Soo, Chethan Pandarinath Chris Versteeg & others to discuss exciting new findings. Want to get involved?👇🏽(1/2)

Thrilled to share that my PhD advisor, Larry Abbott, and pioneers Terry Sejnowski Terrence Sejnowski & Haim Sompolinsky Haim Sompolinsky clinched the prestigious Brain Prize for their groundbreaking work in computational and theoretical neuroscience. 🤘🤓🤘 This honor is a watershed

Amazing work from our friends at EPFL! A huge step towards a deeper understanding of the "goals" of proprioceptive processing, a question that kept me up at night!

How can we understand the way sequence models choose to combine info in their context to make good predictions? In our new ICML Conference workshop paper, Adam J. Eisen , FieteGroup and I provide a new theoretical lens from dynamical systems: delay embeddings arxiv.org/abs/2406.11993

What underlies the spinal cord’s intrinsic ability to adjust locomotor patterns on a step-by-step basis? We investigated this question in our new preprint! Follow along in the thread for the #tweeprint!

1/5 Excited to finally share our new paper (led by Laura Driscoll, now a group leader at the Allen!) in Nature Neuroscience on modular computation in neural networks! We've explored how artificial recurrent networks handle multiple tasks, offering insights into flexible computation.

pip install motornet

MotorNet is an amazing toolbox that everyone interested in musculoskeletal modeling should check out! Thanks to Jonathan A. Michaels and Olivier Codol for their hard work🦾🦾🧠🧠

Check out GNOCCHI! - Diffusion modeling of neural data: ✅ - Interpretable latent spaces: ✅ - Heldout data generation: ✅ - Named after a delicious pasta: ✅

Sergey Stavisky we're like the NEJM of publicly shared lab reading lists after all

I’ll see if it can replicate

Want recordings like this? Come get some Myomatrix arrays at Sfn!

How continuous neural activity learns and supports discrete, symbolic & compositional processes remains an important question for Cog Sci and AI. Here we explore ways to achieve both symbolic and sub-symbolic processing using attractor dynamics. arxiv.org/abs/2310.01807

My brain shorted out for a moment before I read the quoted tweet...