Matt Perich
@mattperich.bsky.social
1.6K followers 170 following 61 posts
Neuroscience, engineering, AI, music. Asst. Professor / PI at University of Montréal and Mila.
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mattperich.bsky.social
Check out our new paper led by @oliviercodol.bsky.social ! We use RNNs to explore possible learning rules that lead to the dynamics we see in brains during behavior.

www.biorxiv.org/content/10.1...

#neuroskyence #compneurosky #neuroai
mattperich.bsky.social
A big "get" for the Champalimaud! Excited to see what comes out of the Warehouse and the next phase of Juan's lab
juangallego.bsky.social
🚨Big news!🚨
The lab is relocating to Lisbon, joining a great team of experimental and theoretical neuroscientists, and the Neurotechnology Warehouse, a new initiative to bridge basic and translational research.

I'll be sharing postdoc openings soon. Come join us in this new incarnation of the lab!
champalimaudr.bsky.social
🧠🎼 What does it take to restore movement? Neuroscientist and engineer, @juangallego.bsky.social, joins the new Centre for Restorative Neurotechnology at the Champalimaud Foundation.

🔗 Find out more in this interview: www.fchampalimaud.org/news/juan-al...
Reposted by Matt Perich
endoeartha.bsky.social
Very excited and proud to share my postdoctoral research with @neurrriot.bsky.social looking at the context-specific encoding of social behavior 💃🕺 in hormone-sensitive, large-scale brain networks in mice!

www.biorxiv.org/content/10.1...

#neuroskyence #compneurosky 🧪
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mattperich.bsky.social
More info on our funded project is here: webapps.cihr-irsc.gc.ca/decisions/p/.... In many ways, this directly follows our 2020 paper: www.biorxiv.org/content/10.1.... But we have much broader ambitions too and are building a flexible platform for NHP motor ephys. Should be a fun 5 years!
mattperich.bsky.social
IMO Montreal is one of the best cities out there for neuro, and everyone in my lab will get to enjoy learning from and interacting with the NeuroAI folks at Mila. If modeling the computations behind multi-modal sensorimotor integration and adaptation is of interest to you, please reach out!
mattperich.bsky.social
🚨 I’m excited to say that my CIHR Project Grant was funded! My NHP lab is now full-speed-ahead, and I’m hiring experimentalists (postdoc, PhD student, and/or a tech/manager). We’ll do multi-region ephys during reaching/grasping in macaques, with behavioral and spinal perturbations.
mattperich.bsky.social
Awesome work from @juangallego.bsky.social and lab. An interface from single motoneuron control in tetraplegia!
juangallego.bsky.social
🚨 New preprint + thread 🧵
We've gone back to studying motoneuron control principles and their applications & here's paper #1:

A proof-of-concept study showing that people with tetraplegic spinal cord injury can control up to 2DoF from a single intramuscular implant

www.medrxiv.org/content/10.1...
Reposted by Matt Perich
juangallego.bsky.social
Very happy about my former mentor Sara Solla having received the Valentin Braitenberg Award for her lifelong contributions to computational neuroscience!

Sara will be giving a lecture at the upcoming @bernsteinneuro.bsky.social meeting which you shouldn't miss.

bernstein-network.de/en/newsroom/...
Sara A. Solla receives the Valentin Braitenberg Award for Computational Neuroscience 2025 – Bernstein Network Computational Neuroscience
bernstein-network.de
mattperich.bsky.social
Could be a cell type difference (Gardner 2022 focused on grid cells) or a region difference? Methods difference? Lots of interesting possibilities!
mattperich.bsky.social
Though I will say that some evidence suggests it's not going to always be 1:1 with environment. E.g. the 2022 Gardner ERC place cell paper we mention in the article has place cells mapping even square environments into a toroid shape. Though the Guo 2024 CA1 paper has environment-hspaed manifolds
mattperich.bsky.social
There's a long and fun conversation to be had here 🙂. But I agree, the "many-to-few" nature of neurons to manifolds allows considerable drift in single neuron activity without changing the manifold. Important in next steps to find out when, and how, neural drift changes manifold-level properties!
mattperich.bsky.social
Indeed, IMO behavior (and environment, etc) are inextricably linked to manifold properties. For this reason, comparative (e.g. for same behavior, are manifolds different in different regions?) and causal (e.g., move activity on the manifold and predict behavioral changes) experiments are essential.
mattperich.bsky.social
Thanks for the kind words and really glad you enjoyed the article!
mattperich.bsky.social
Thanks to @emilysingerneuro.bsky.social for another opportunity to work with The Transmitter (which is an awesome publication), and of course the many, many long conversations on manifolds with @juangallego.bsky.social that shaped these articles 🙂
mattperich.bsky.social
📰 I really enjoyed writing this article with @thetransmitter.bsky.social! In it, I summarize parts of our recent perspective article on neural manifolds (www.nature.com/articles/s41...), with a focus on highlighting just a few cool insights into the brain we've already seen at the population level.
Reposted by Matt Perich
juangallego.bsky.social
🚨New paper🚨

Neural manifolds went from a niche-y word to an ubiquitous term in systems neuro thanks to many interesting findings across fields. But like with any emerging term, people use it very differently.

Here, we clarify our take on the term, and review key findings & challenges rdcu.be/ex8hW
Reposted by Matt Perich
markhisted.org
'manifolds', and the overall conception of the brain using a dynamical systems framework, have come a long way.
mattperich.bsky.social
A lot has changed since we wrote our last perspective piece in 2017 (www.cell.com/neuron/fullt..., both in how we think about neural manifolds and in the prevalence in the field. We hope this paper provides a good primer for the ideas, and points towards some big open questions in this space.
mattperich.bsky.social
I guess I wouldn't think of babies as "learning" a foundation model. IMO a better analogy is that evolution learned the foundation model and babies during development are fine-tuning it (albeit in a "multi-task" way) for their bodies/experiences .
Reposted by Matt Perich
mattperich.bsky.social
Our new approach for scalable, generalizable, and efficient neural population decoding is now online! Here we focus on real-time BCI but I'm excited about all of our next steps building on this. Awesome work led by @averyryoo.bsky.social @nandahkrishna.bsky.social @ximengmao.bsky.social
averyryoo.bsky.social
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!

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