Patrick Mineault

There's a new imaging modality in town: functional ultrasound imaging. I went down a deep rabbit hole to understand how it works physically and computationally. Follow me as I show you how *you* can use it and improve it www.neuroai.science/p/functional...

a good summary of how we got here and what it means. i would add is that everyone who works with the fly connectome datasets knows that they all far from "complete". each one, though monumental, has major reconstruction/annotation issues, not to mention the lack of a peripheral nervous system.

Are virtual flies playing Beat Saber? SM64? Doom? No. The new fly connectome is an incredible achievement! Less is going on in the sim videos than it seems. I'm stoked to see people engage with neuroscience though. My breakdown: www.neuroai.science/p/are-flies-...

I was floored to hear there are chemogenetics trials in humans. We're engineering neurons to have synthetic receptors that can be activated using normally inert drugs! How big of a deal is this for epilepsy, PD, pain? I did a deep dive into human chemogenetics www.neuroai.science/p/the-race-t...

How has neuroscience changed in the past 10 years? I reread The Future of the Brain, a 2014 compilation of essays from neuroscientists, to see if we accomplished what we said we would. Atlases! Connectomes! Whole brain simulations! TL;DR: we did pretty well! www.neuroai.science/p/the-future...

Excited to share our new paper accepted at ICML 2026 with @tyrellturing.bsky.social and Doina Precup! 🇰🇷 See you in Seoul. A major challenge in continual reinforcement learning is balancing: • plasticity (learning new things) • stability (not forgetting old ones) 🧵 1/15

🚨🧠 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

We have an implicit model of neurodegenerative disease: many discrete diseases, with their own disparate biology. Underlying all of them is the general process of aging. We must strike at the root of senescence. Here's our plan for addressing brain aging. blog.amaranth.foundation/p/solving-br...

From @tonyzador.bsky.social and crew, a paper showing that neurons' positions in the brain are not just determined by molecular, but also by lineage: www.cell.com/neuron/abstr... #neuroscience 🧪

Paradoxically, when you see a yellow on blue slide, you know you're about to get a fantastic lecture. Bonus points for Times New Roman.

🧵 New preprint led by @bingbrunton.bsky.social, @elliottabe.bsky.social, @lawrencehu.bsky.social We gave a worm brain control of a fly body and it walked What did we learn? Nothing, other than deep reinforcement learning is effective We call it the digital sphinx www.biorxiv.org/content/10.6...

If you have a good substack about neuro / AI and are cranking out solid content, happy to add it to my list of recs on substack—that little feature has driven 100's of subscribers to other newsletters

A cool insight here: CDM isn’t just hard to infer, it’s hard to train directly (because it can’t be specified as a loss on systems behavior). This means it either needs to emerge as a consequence of other losses, data, or architecture choices.

Current AI models are trained on human behavior -- the words we produce. New preprint explores the idea that we might be able to address some of the gaps in these systems by training on the latent variables behind that behavior: human cognition.

A remarkable journey of resilience and transformation, from the chaotic corridors of group homes to the halls of Columbia and Stanford, EMERGENCE is a coming-of-age tale where heartbreak and humor meet the scientific wonder of modern artificial intelligence. 🔗 Preorder: tinyurl.com/fzcxb5ea

We know about cosmological dark matter despite being unable to measure it because, without it, galaxies would fall apart. By analogy, let's talk about "cognitive dark matter" (CDM): brain functions that meaningfully shape behavior but are hard to infer from behavior alone. New paper! 🧵👇

There's no better way to learn than to teach! Help make NMA a resounding success!

Ran into David Chalmers at Wash Sq Park. Beautiful day to ponder the hard problem of consciousness.

Looking for YOUR INPUT on what we've learned in neuro in the past 20 years. I've only heard pessimistic takes! Come on, grid cells, manifolds, optogenetics, connectomes, moving past the monoamine theory of depression and the Ab theory of AD, glymphatics and lymphatics, what is sleep?! We did stuff!

I want to write a fun little post on what we've learned in neuroscience in the last 20 years. What are the most interesting results you can think of? Biggest trends?

DNN models of the brain are getting bigger. Are we replacing one complicated system in vivo with another in silico? In new work, we seek the *smallest* DNN models of visual cortex, balancing prediction with parsimony. It turns out these compact models are surprisingly small! rdcu.be/e5H8G

Lots of things to think about in these posts from @patrickmineault.bsky.social -- nice to see more blog entries :)

I'm excited to announce that I had my first (co-authored) book published today! "The Rational Use of Cognitive Resources" with Falk Lieder and Tom Griffiths (@cocoscilab.bsky.social ). You can read it for free! (see thread)

The revised version of our paper on the impact of top-down feedback is now out @elife.bsky.social: doi.org/10.7554/eLif... tl;dr: we show that using human-brain-like feedback/anatomy in a deep RNN leads to human-like visual biases! This work was led by @tmshbr.bsky.social #NeuroAI 🧠📈 🧪

🚨 new work from the lab on how eye movements 👀 versus orofacial movements influence 🐭 visual cortex activity 🧠 #neuroscience #behavior #neuroAI

Discovered @patrickmineault.bsky.social's excellent Good Research Code Handbook today, which was always awesome, but is even more necessary as more scientists consider integrating coding agents into their workflows. goodresearch.dev

www.neuroai.science/p/claude-cod... Why yes this is very helpful for me as an undergrad. I like the way the methods that Patrick laid, how to aid research using AI and its pros vs cons

From @patrickmineault.bsky.social, on how scientists can use Claude Code to help with all the heavy data analysis coding that is a big part of our lives. use a make system, set up folder structures, write tests, use git, use package managers. Notes on notebooks and visualizations too. 🧪

🚨📜+🧵🚨 Very excited about this work showing that people with no hand function following a spinal cord injury can control the activity of motor units from those muscles to perform 1D, 2D and 3D tasks, play video games, or navigate a virtual wheelchair By a wonderful team co-mentored w Dario Farina

Just published my review of neuroscience in 2025, on The Spike. The 10th of these, would you believe? This year we have foundation models, breakthroughs in using light to understand the brain, a gene therapy, and more Enjoy! medium.com/the-spike/20...

✈️ Montreal AI and Neuroscience is over, off to Costa Rica. Great catching up all things NeuroAI with hometown friends. Thanks for the shirt and the bagels, folks!

🔴 Live: Panel discussion #1: @ MAIN2025 The future of Neuroscience - The role of AI ?  with Andreas Tolias, Siva Reddy, Joao Sacramento, Ching Fang + Eva Portelance Moderated by Patrick Mineault @patrickmineault.bsky.social @andreastolias.bsky.social

What I would have done for a dataset like this to exist in grad school! One day, we'll figure out the dorsal stream. openreview.net/forum?id=Ila...

Headed to NeurIPS, looking forward to catching up with you about NeuroAI, foundation models of the brain, AI safety and AI for science

This equivocation of oscillations and continual learning is a bit of stretch... I'm surprised they didn't get dinged by the reviewers for neuro-babble. openreview.net/forum?id=nbM...

We're almost at the end of the year, and that means an end-of-year review! Send me your favorite NeuroAI papers of the year (preprints or published, late last year is fine too).

New #NeuroAI #compneurosky preprint! To better understand how target-directed learning works in the brain, we sought to engineer an artificial neural network capable of solving complex image classification tasks that comprises only experimentally-supported biological building blocks. (1/15)

I had way too much fun making these diagrams. Sure, it's not as legible as if I had typed out the text; but I feel like these have a bit more personality

🚨 New preprint alert! 🧠🤖 We propose a theory of how learning curriculum affects generalization through neural population dimensionality. Learning curriculum is a determining factor of neural dimensionality - where you start from determines where you end up. 🧠📈 A 🧵: tinyurl.com/yr8tawj3

Thrilled to share that our work is now published in Science! ✨ We found a preference for visual objects in the mouse spatial navigation system where they dynamically refine head-direction coding. In short, objects boost our inner compass! 🧭 www.science.org/doi/10.1126/... 🧵1/