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Matthijs Pals

@matthijspals.bsky.social

910 followers 610 following 16 posts

Using deep learning to study neural dynamics @mackelab.bsky.social

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Matthijs Pals @matthijspals.bsky.social · Nov 14

Seems like it's a good time to jump ship! I am working in @mackelab.bsky.social, on using deep learning (usually recurrent neural networks; RNNs) to study neural dynamics.

A cool example is recent work where we show how to generate long sequences of realistic neural data: arxiv.org/abs/2406.16749

Inferring stochastic low-rank recurrent neural networks from neural data

A central aim in computational neuroscience is to relate the activity of large populations of neurons to an underlying dynamical system. Models of these neural dynamics should ideally be both interpre...

arxiv.org

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Matthijs Pals @matthijspals.bsky.social · 8d

Really cool work! 🔥

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Machine Learning in Science @mackelab.bsky.social · 10d

The Macke lab is well-represented at the @bernsteinneuro.bsky.social conference in Frankfurt this year! We have lots of exciting new work to present with 7 posters (details👇) 1/9

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Richard Gao @rdgao.bsky.social · 17d

I've been waiting some years to make this joke and now it’s real:

I conned somebody into giving me a faculty job!

I’m starting as a W1 Tenure-Track Professor at Goethe University Frankfurt in a week (lol), in the Faculty of CS and Math

and I'm recruiting PhD students 🤗

a man wearing a white shirt and tie smiles in front of a window

ALT: a man wearing a white shirt and tie smiles in front of a window

media.tenor.com

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DurstewitzLab @durstewitzlab.bsky.social · 19d

Our #AI #DynamicalSystems #FoundationModel DynaMix was accepted to #NeurIPS2025 with outstanding reviews (6555) – first model which can *zero-shot*, w/o any fine-tuning, forecast the *long-term statistics* of time series provided a context. Test it on #HuggingFace:
huggingface.co/spaces/Durst...

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sbi - Simulation-based inference @sbi-devs.bsky.social · Sep 9

From hackathon to release: sbi v0.25 is here! 🎉

What happens when dozens of SBI researchers and practitioners collaborate for a week? New inference methods, new documentation, lots of new embedding networks, a bridge to pyro and a bridge between flow matching and score-based methods 🤯

1/7 🧵

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DurstewitzLab @durstewitzlab.bsky.social · Jul 13

Got prov. approval for 2 major grants in Neuro-AI & Dynamical Systems Reconstruction, on learning & inference in non-stationary environments, out-of-domain generalization, and DS foundation models. To all AI/math/DS enthusiasts: Expect job announcements (PhD/PostDoc) soon! Feel free to get in touch.

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Elkan Akyurek @elkanakyurek.bsky.social · Jul 3

Jelmer Borst and I are looking for a PhD candidate to build an EEG-based model of human working memory! This is a really cool project that I've wanted to kick off for a while, and I can't wait to see it happen. Please share and I'm happy to answer any Qs about the project!
www.rug.nl/about-ug/wor...

Vacatures bij de RUG

www.rug.nl

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The Transmitter @thetransmitter.bsky.social · Jun 30

The neurons that encode sequential information into working memory do not fire in that same order during recall, a finding that is at odds with a long-standing theory. Read more in this month’s Null and Noteworthy.

By @ldattaro.bsky.social

#neuroskyence

www.thetransmitter.org/null-and-not...

Null and Noteworthy: Neurons tracking sequences don’t fire in order

Instead, neurons encode the position of sequential items in working memory based on when they fire during ongoing brain wave oscillations—a finding that challenges a long-standing theory.

www.thetransmitter.org

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DurstewitzLab @durstewitzlab.bsky.social · Jun 26

How do animals learn new rules? By systematically testing diff. behavioral strategies, guided by selective attn. to rule-relevant cues: rdcu.be/etlRV
Akin to in-context learning in AI, strategy selection depends on the animals' "training set" (prior experience), with similar repr. in rats & humans.

Abstract rule learning promotes cognitive flexibility in complex environments across species

Nature Communications - Whether neurocomputational mechanisms that speed up human learning in changing environments also exist in other species remains unclear. Here, the authors show that both...

rdcu.be

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Tatiana Engel @engeltatiana.bsky.social · Jun 25

Out today in @nature.com: we show that individual neurons have diverse tuning to a decision variable computed by the entire population, revealing a unifying geometric principle for the encoding of sensory and dynamic cognitive variables.
www.nature.com/articles/s41...

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Valentin Schmutz @bio-emergent.bsky.social · Jun 9

Our new preprint 👀

Matteo Carandini @carandinilab.net · Jun 9

The firing of neural populations is high-dim even if their subthreshold activity is low-dim! This work by @bio-emergent.bsky.social and @haydari.bsky.social shows how, with a solvable model, a data analysis technique, and data from mouse visual cortex: www.biorxiv.org/content/10.1...

High-dimensional neuronal activity from low-dimensional latent dynamics: a solvable model

Computation in recurrent networks of neurons has been hypothesized to occur at the level of low-dimensional latent dynamics, both in artificial systems and in the brain. This hypothesis seems at odds ...

www.biorxiv.org

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Tim Vogels @tpvogels.bsky.social · Jun 2

We just pushed “Memory by a 1000 rules” onto bioRxiv, where we use clever #ML to find #plasticity quadruplets (EE, EI, IE, II) that learn basic stability in spiking nets. Why is it cool? We find 1000s!! of solutions, and they don’t just stabilise. They #memorise! www.biorxiv.org/content/10.1...

Memory by a thousand rules: Automated discovery of functional multi-type plasticity rules reveals variety & degeneracy at the heart of learning

Synaptic plasticity is the basis of learning and memory, but the link between synaptic changes and neural function remains elusive. Here, we used automated search algorithms to obtain thousands of str...

www.biorxiv.org

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sbi - Simulation-based inference @sbi-devs.bsky.social · May 12

Great news! Our March SBI hackathon in Tübingen was a huge success, with 40+ participants (30 onsite!). Expect significant updates soon: awesome new features & a revamped documentation you'll love! Huge thanks to our amazing SBI community! Release details coming soon. 🥁 🎉

A wide shot of approximately 30 individuals standing in a line, posing for a group photograph outdoors. The background shows a clear blue sky, trees, and a distant cityscape or hills.

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Joao Barbosa @jbarbosa.org · May 10

Please RT🙏

Reach out if you want to help understand cognition by modelling, analyzing and/or collect large scale intracortical data from 👩🐒🐁

We're a friendly, diverse group (n>25) w/ this terrace 😎 in the center of Paris! See👇 for + info about the lab

We have funding to support your application!

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Machine Learning in Science @mackelab.bsky.social · Apr 30

🎓Hiring now! 🧠 Join us at the exciting intersection of ML and Neuroscience! #AI4science
We’re looking for PhDs, Postdocs and Scientific Programmers that want to use deep learning to build, optimize and study mechanistic models of neural computations. Full details: www.mackelab.org/jobs/ 1/5

Jobs - mackelab

The MackeLab is a research group at the Excellence Cluster Machine Learning at Tübingen University!

www.mackelab.org

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Shervin Safavi @neuroprinciplist.bsky.social · Feb 20

Re-posting is appreciated: We have a fully funded PhD position in CMC lab @cmc-lab.bsky.social (at @tudresden_de). You can use forms.gle/qiAv5NZ871kv... to send your application and find more information. Deadline is April 30. Find more about CMC lab: cmclab.org and email me if you have questions.

forms.gle

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Machine Learning in Science @mackelab.bsky.social · Apr 25

Excited to present our work on compositional SBI for time series at #ICLR2025 tomorrow!

If you're interested in simulation-based inference for time series, come chat with Manuel Gloeckler or Shoji Toyota

at Poster #420, Saturday 10:00–12:00 in Hall 3.

📰: arxiv.org/abs/2411.02728

Compositional simulation-based inference for time series

Amortized simulation-based inference (SBI) methods train neural networks on simulated data to perform Bayesian inference. While this strategy avoids the need for tractable likelihoods, it often requir...

arxiv.org

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Amin Nejatbakhsh @aminejat.bsky.social · Apr 22

Excited to announce that our paper on "Comparing noisy neural population dynamics using optimal transport distances" has been selected for an oral presentation in #ICLR2025 (1.8% top papers). Check the thread for paper details (0/n).

Presentation info: iclr.cc/virtual/2025....

ICLR 2025 Comparing noisy neural population dynamics using optimal transport distances OralICLR 2025

iclr.cc

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Matthijs Pals @matthijspals.bsky.social · Mar 28

Happening tomorrow morning :).

Machine Learning in Science @mackelab.bsky.social · Mar 27

Interested in obtained models that are both interpretable and that can generate realistic neural data?

@matthijspals.bsky.social will give a contributed talk on fitting stochastic low-rank RNNs to neural data, Saturday 10:00 at the main conference! 🤩

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Machine Learning in Science @mackelab.bsky.social · Mar 27

The @mackelab.bsky.social is represented at @cosynemeeting.bsky.social #cosyne2025 in Montreal

with 3 posters, 2 workshop talks, and a main conference contributed talk (for the very first time in Mackelab history 🎉)!

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Jakob Macke @jakhmack.bsky.social · Mar 24

Out now 'in print'--- a true labor of love, in more ways than one. See the paper and press-release below!

Also, go and see @matthijspals.bsky.social's talk at #Cosyne, where he will talk about related/follow up work!

uni-tuebingen.de/en/research/...

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Matthijs Pals @matthijspals.bsky.social · Mar 24

Our study on sequence working memory using human spiking data and RNNs, is finally published :). Check it out! 👇

C3N @c3neuro.bsky.social · Mar 24

Science Alert 🚨: Our paper is now out in @natureneuro.bsky.social - We show that the firing phase of neurons in human MTL doesn’t reflect the order of events, challenging a long-standing theory of human memory.
nature.com/articles/s41593-025-01893-7

Phase of firing does not reflect temporal order in sequence memory of humans and recurrent neural networks - Nature Neuroscience

The temporal order of events in working memory is thought to be reflected by ordered neuronal firing at different phases. Here the authors show that this is not the case and that phase order is linked...

www.nature.com

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T. Anderson Keller @andykeller.bsky.social · Mar 10

In the physical world, almost all information is transmitted through traveling waves -- why should it be any different in your neural network?

Super excited to share recent work with the brilliant @mozesjacobs.bsky.social: "Traveling Waves Integrate Spatial Information Through Time"

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Michael Deistler @deismic.bsky.social · Feb 28

Together with @dendritesgr.bsky.social, we’ll be hosting a tutorial on constructing and optimizing biophysical models (via Jaxley & DendroTweaks) 🚀

Join us in Florence if you like dendrites, biophysics, or optimization!

Roman Makarov @roman-makarov.bsky.social · Feb 26

We are thrilled to host a tutorial on biophysical modeling with Jaxley & DendroTweaks at #CNS2025! 📍 Florence, July 5 — looking forward to seeing you there! www.cnsorg.org/cns-2025 @cnsorg.bsky.social

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Auguste Schulz @auschulz.bsky.social · Feb 3

1) Some exciting science in turbulent times:

How do mice distinguish self-generated vs. object-generated looming stimuli? Our new study combines VR and neural recordings from superior colliculus (SC) 🧠🐭 to explore this question.

Check out our preprint doi.org/10.1101/2024... 🧵

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