DurstewitzLab
durstewitzlab.bsky.social
DurstewitzLab
@durstewitzlab.bsky.social
Scientific AI/ machine learning, dynamical systems (reconstruction), generative surrogate models of brains & behavior, applications in neuroscience & mental health
Revised version of our #NeurIPS2025 paper with full code base in Julia & Python now online, see arxiv.org/abs/2505.13192
October 28, 2025 at 6:27 PM
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...
September 21, 2025 at 9:40 AM
We have openings for several fully-funded positions (PhD & PostDoc) at the intersection of AI/ML, dynamical systems, and neuroscience within a BMFTR-funded Neuro-AI consortium, at Heidelberg University & Central Institute of Mental Health:
www.einzigartigwir.de/en/job-offer...

More info below ...
August 15, 2025 at 7:46 AM
Reposted by DurstewitzLab
Is it possible to go from spikes to rates without averaging?

We show how to exactly map recurrent spiking networks into recurrent rate networks, with the same number of neurons. No temporal or spatial averaging needed!

Presented at Gatsby Neural Dynamics Workshop, London.
From Spikes To Rates
YouTube video by Gerstner Lab
youtu.be
August 8, 2025 at 3:25 PM
Reposted by DurstewitzLab
Today I joined >1900 members of US National Academies of Science, Engineering & Medicine signing this open letter (views our own).

Leadership of science by US has been paramount for >70yrs & Admin is now acting to throw it all away!

docs.google.com/document/d/1...

www.nytimes.com/2025/03/31/s...
Public Statement on Supporting Science for the Benefit of All Citizens
TO THE AMERICAN PEOPLE We all rely on science. Science gave us the smartphones in our pockets, the navigation systems in our cars, and life-saving medical care. We count on engineers when we drive acr...
docs.google.com
March 31, 2025 at 5:00 PM
Reposted by DurstewitzLab
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.
July 13, 2025 at 6:23 AM
We wrote a little #NeuroAI piece about in-context learning & neural dynamics vs. continual learning & plasticity, both mechanisms to flexibly adapt to changing environments:
arxiv.org/abs/2507.02103
We relate this to non-stationary rule learning tasks with rapid performance jumps.

Feedback welcome!
What Neuroscience Can Teach AI About Learning in Continuously Changing Environments
Modern AI models, such as large language models, are usually trained once on a huge corpus of data, potentially fine-tuned for a specific task, and then deployed with fixed parameters. Their training ...
arxiv.org
July 6, 2025 at 10:18 AM
Happy to discuss our work on parsimonious & math. tractable RNNs for dynamical systems reconstruction next week at
cns2025florence.sched.com/event/1z9Mt/...
CNS*2025 Florence: NeuroXAI: Explainable AI for Understandi...
View more about this event at CNS*2025 Florence
cns2025florence.sched.com
July 3, 2025 at 12:40 PM
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
June 26, 2025 at 3:30 PM
Reposted by DurstewitzLab
What a line up!! With Lorenzo Gaetano Amato, Demian Battaglia, @durstewitzlab.bsky.social, @engeltatiana.bsky.social,‪ @seanfw.bsky.social‬, Matthieu Gilson, Maurizio Mattia, @leonardopollina.bsky.social‬, Sara Solla.
June 21, 2025 at 10:24 AM
Reposted by DurstewitzLab
Into population dynamics? Coming to #CNS2025 but not quite ready to head home?

Come join us! at the Symposium on "Neural Population Dynamics and Latent Representations"! 🧠
📆 July 10th
📍 Scuola Superiore Sant’Anna, Pisa (and online)
👉 Free registration: neurobridge-tne.github.io
#compneuro
June 21, 2025 at 10:24 AM
I’m really looking so much forward to this! In wonderful Pisa!
Into population dynamics? Coming to #CNS2025 but not quite ready to head home?

Come join us! at the Symposium on "Neural Population Dynamics and Latent Representations"! 🧠
📆 July 10th
📍 Scuola Superiore Sant’Anna, Pisa (and online)
👉 Free registration: neurobridge-tne.github.io
#compneuro
June 21, 2025 at 12:18 PM
Just heading back from a fantastic workshop on neural dynamics at Gatsby/ London, organized by Tatiana Engel, Bruno Averbeck, & Peter Latham.
Enjoyed seeing so many old friends, Memming Park, Carlos Brody, Wulfram Gerstner, Nicolas Brunel & many others …
Discussed our recent DS foundation models …
June 19, 2025 at 11:37 AM
Can time series (TS) #FoundationModels (FM) like Chronos zero-shot generalize to unseen #DynamicalSystems (DS)?

No, they cannot!

But *DynaMix* can, the first TS/DS FM based on principles of DS reconstruction, capturing the long-term evolution of out-of-domain DS: arxiv.org/pdf/2505.131...
(1/6)
May 20, 2025 at 2:15 PM
I'm presenting our lab's work on *learning generative dynamical systems models from multi-modal and multi-subject data* in the world-wide theoretical neurosci seminar Wed 23rd, 11am ET:
www.wwtns.online

--> incl. recent work on building foundation models for #dynamical-systems reconstruction #AI 🧪
Home | Neuroscience | World Wide Theoretical Neuroscience Seminar
WWTNS is a weekly digital seminar on Zoom targeting the theoretical neuroscience community. Its aim is to be a platform to exchange ideas among theoreticians.
www.wwtns.online
April 21, 2025 at 3:37 PM
Reposted by DurstewitzLab
Reposted by DurstewitzLab
My latest post is now out.

I show how Trump's attacks on science and universities are neither random nor new - they fit very precisely into the authoritarian playbook.

This means we can guess what might come next and prepare - and we must!

christinapagel.substack.com/p/censor-pur...
Censor, purge, defund: how Trump following the authoritarian playbook on science and universities
I have mapped 35 of the Trump administration's attacks on science and universities to the authoritarian playbook - and consider what it means for attacks still to come
christinapagel.substack.com
March 10, 2025 at 2:58 PM
Our revised #iclr2025 paper and codebase for an architecture for foundation models for dynamical systems reconstruction is now online: openreview.net/pdf?id=Vp2OA...

... includes additional examples of how this may be harvested for identifying drivers (control par.) of non-stationary processes.
February 9, 2025 at 2:18 PM
Toward interpretable #AI foundation models for #DynamicalSystems reconstruction: Our paper on transfer & few-shot learning for dynamical systems just got accepted for #ICLR2025 !

Previous version: arxiv.org/pdf/2410.04814; strongly updated version will be available soon ...
(1/4)
January 26, 2025 at 11:28 AM
Reposted by DurstewitzLab
December 29, 2024 at 2:58 PM
That paper discusses an important issue for RNNs as used in neurosci. But we would argue that many RNN approaches do not truly reconstruct DS, for which we demand also agreement in long-term stats, attractor geometry, and generative perform. (esp. in chaotic systems, MSE as stats can be misleading).
December 25, 2024 at 12:09 PM
Reposted by DurstewitzLab
Great to see this group on Bluesky. Durstewitz and Seamans 2008 is one of my all time favorite papers on the function of dopamine in the PFC www.researchgate.net/profile/Dani...
December 24, 2024 at 8:33 PM
Now may be a good time to introduce our group on bsky with some of our contrib. to dynamical systems reconstruction (DSR) from past year. By DSR we mean learning a *generative surrogate model* of a dyn. process from TS data which reproduces full attractor & generalizes to new init. conditions (1/6)
December 24, 2024 at 12:39 PM
Good targets for foundation/ inference models/ LLMs …
Every educator struggles to inspire deep thinking in students.

We never want them memorizing just facts.

You've tried various techniques, but nothing consistently works.

The traditional Q&A approach only takes you so far.

Here's a thinking cube you could print, cut, build. And try out.
December 22, 2024 at 10:03 AM