Patrick Mineault

NeuroAI researcher @ Amaranth Foundation, safety, open science. Previously engineer @ Google, Meta, Mila.

[Patrick Mineault @patrickmineault]

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

[Neural Computation Lab @NeuralCompLab]

Neuropixels Opto is out! 🎉🥳🍾🚨 Congratulations to a fantastic team!

https://t.co/yrOSDmV4wa

[Prof. Michael Lin @MichaelLinLab]

Excited to announce a powerful new one-two punch for voltage imaging from our lab and collaborators! In two new preprints, we introduce ASAP6c for high-throughput population spike-recording, and ASAP7yfor deep, subthreshold 2P imaging.
🧵 1/14

[Ali H. Shaib @AliHShaib]

Hello world, meet 1,000× Expansion Microscopy.
1,000,000,000× expansion by volume! A gel that starts at a few centimeters will then expand to the volume of an Olympic swimming pool. https://t.co/E43kxx4O5M
In our new bioRxiv preprint, work carried out between MIT and UMG, led by Helena Hu in collaboration with scientists from the labs of @eboyden3 Ed Boyden, Silvio Rizzoli, and myself, we present Thousandfold Expansion Microscopy.
By enlarging biological specimens across multiple rounds of expansion, molecular-scale features, as small as the distances between adjacent amino acids, can be visualized with conventional optical microscopes.
Democratizing super-resolution microscopy.

[Matthieu wyart @MatthieuWyart]

LLMs learn by predicting tokens. World models (JEPA, data2vec) learn by predicting their own abstractions. Which needs more data? For data with hidden hierarchy, we prove the gap is exponential. https://t.co/r2uuX0lBCu

[David Klindt @klindt_david]

What does JEPA actually learn? We can finally prove it 🌍

So excited to share our theory of identifiable World Models: LeJEPA recovers the latent variables of the world.

Plan in the learned World Model as if it were real, same shortest path.

📄: https://t.co/lC9KK1AxVd

[Josh Wilson @Norcal_Neuro]

1/ New preprint with @dyamins + team! Ventral visual representations within areas evolve over the course of the response along the same hierarchical complexity axis that distinguishes the visual areas, potentially driven by local recurrence.
https://t.co/k9ugZYb9I9

[Patrick Mineault @patrickmineault]

@alfairhall @uwcnc I'm curious what the answers were to the Part III forward look convo. We should all be thinking deeply about that rn.

[Patrick Mineault @patrickmineault]

https://t.co/dA4f7lzR2f

[Rui Xu @ruix_mit]

New preprint: "Monosynaptic connections link functionally similar regions in human cortex." We use electrical stimulation + fMRI in epilepsy patients to map whole-brain monosynaptic connectivity at 42 cortical sites. https://t.co/rSSSVsMWCQ 1/n

[Brad Hulse @BradKHulse]

Story time friends...

Ring attractor networks rely on fine-tuned symmetric connectivity.

The fly head direction network has ring attractor dynamics but heterogeneous connectivity.

How is this possible? 1/🧵
Link: https://t.co/YEaM8gkwOy

[Prof. Michael Lin @MichaelLinLab]

There is a big elephant in the room in experimental systems neuroscience:

Before many trainees can test a single hypothesis, they spend 1–3 years becoming expert mouse surgeons rather than scientists.

Here's my proposal for how we can waste less time and do more research🧵

[Sam Rodriques @SGRodriques]

Our paper on Robin is out at Nature! Robin was the first multiagent system for end-to-end biological research, which we preprinted last year, and was published back to back with Google's awesome Coscientist from @vivnat. Great validation, and major congratulations to the team.

[Patrick Mineault @patrickmineault]

@miltonllera @EIiasNajarro @JakobSchauser @risi1979 Interesting. Also relevant: https://t.co/B00pAi4Zln

[Sam Rodriques @SGRodriques]

We live in a golden age of biology. So why are people still dying from disease?

Because discovery and development move slower than they should.

Today, we’re partnering with Incyte to change that.

Kosmos is now the first agent that can compress months of drug development into weeks, from the earliest stages of scientific discovery through to FDA approval. @Incyte will be the first company to deploy it across their pipeline.

Work that used to take a team of scientists months now happens in weeks.

Patients can't wait, and neither can we.

[Patrick Mineault @patrickmineault]

👀 a one-author Nature Physics paper nbd

[Christopher W. Lynn @ChrisWLynn]

Our understanding of neural computation (in the brain and artificial networks) is founded on an assumption: That neurons fire in response to a linear sum of inputs. But can real neurons be so simple?

In a new paper, I systematically test this assumption
https://t.co/vQtYVe8wKQ

[Goodfire @GoodfireAI]

Neural networks do math by rotating shapes.

We found a shape-rotating calculator hidden inside an LLM – and it’s used for more than just math! (1/6)

[Patrick Mineault @patrickmineault]

Read about our plan to solve brain aging here: https://t.co/znE7RKacdF

[Patrick Mineault @patrickmineault]

Underlying all neurogenerative diseases is the general process of aging. We must strike at the root! In the short term, we should restore the health of the support systems of the brain. In the long term, we must build discovery platforms that fully capture human biology.

[Goodfire @GoodfireAI]

Neural networks might speak English, but they think in shapes.

Understanding their rich *neural geometry* is key to understanding how they work – and to debugging and controlling them with precision.

Starting today, we’re releasing a series of posts on this research agenda. 🧵

[Fatih Dinc @fatihdin4en]

For decades, two revolutions in neuroscience ran in parallel:

- 🧠 In vivo imaging — watch neurons fire in living animals

- 🧬 Spatial transcriptomics — read cell's molecular identity

Meet TRU-FACT - a graph-based method that matches cells between these datasets at scale 🧵