🎉 "High-dimensional neuronal activity from low-dimensional latent dynamics: a solvable model" will be presented as an oral at #NeurIPS2025 🎉 Feeling very grateful that reviewers and chairs appreciated concise mathematical explanations, in this age of big models. www.biorxiv.org/content/10.1... 1/2

Lab members are at the Bernstein conference @bernsteinneuro.bsky.social with 9 posters! Here’s the list: TUESDAY 16:30 – 18:00 P1 62 “Measuring and controlling solution degeneracy across task-trained recurrent neural networks” by @flavioh.bsky.social

Check out our new preprint where we analyzed the dynamics of over ten thousand neurons across 223 brain areas and found a surprising universal principle that describes the organization of intrinsic timescales across the entire mouse brain, including subcortical structures! #neuroskyence

Since I'm back on BlueSky - with @frostedblakess.bsky.social and @cpehlevan.bsky.social we wrote a brief perspective on how ideas about summary statistics from the statistical physics of learning could potentially help inform neural data analysis... (1/2)

Excited to share new computational work, led by @jzv.bsky.social, driven by Juan Carlos Fernandez del Castillo + contribution from Farhad Pashakanloo. We recover 3 core motifs in the olfactory system of evolutionarily distant animals using a biophysically-grounded model + efficient coding ideas!

(1/26) Excited to share a new preprint led by grad student Albert Wakhloo, with me and Larry Abbott: "Associative synaptic plasticity creates dynamic persistent activity." www.biorxiv.org/content/10.1...

I wrote a Comment on neurotheory, and now you can read it! Some thoughts on where neurotheory has and has not taken root within the neuroscience community, how it has shaped those subfields, and where we theorists might look next for fresh adventures. www.nature.com/articles/s41...

Wanted to share a new version (much cleaner!) of a preprint on how connectivity structure shapes collective dynamics in nonlinear RNNs. Neural circuits have highly non-iid connectivity (e.g., rapidly decaying singular values, structured singular-vector overlaps), unlike classical random RNN models.

Excited to announce that my first postdoc paper is now online! Links: www.nature.com/articles/s41... rdcu.be/eAcN7 In it, we examine the perennial question: what changes in the brain when learning a new motor skill? Read more below to find out 👇

Coming March 17, 2026! Just got my advance copy of Emergence — a memoir about growing up in group homes and somehow ending up in neuroscience and AI. It’s personal, it’s scientific, and it’s been a wild thing to write. Grateful and excited to share it soon.

Physik studieren? Oder ein anderes Fach? In Göttingen geht jetzt beides, mit dem "Bachelor Interdisziplinär", der Physik mit spannenden Disziplinen Eurer Wahl, wie z.B. Künstlicher Intelligenz, Philosophie, Neurowissenschaften, ... kombiniert. www.uni-goettingen.de/de/studium/6...

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...

(1/23) In addition to the new Lady Gaga album "Mayhem," my paper with Manuel Beiran, "Structure of activity in multiregion recurrent neural networks," has been published today. PNAS link: www.pnas.org/doi/10.1073/... (see dclark.io for PDF) An explainer thread...

Interested in high-dim chaotic networks? Ever wondered about the structure of their state space? @jakobstubenrauch.bsky.social has answers - from a separation of fixed points and dynamics onto distinct shells to a shared lower-dim manifold and linear prediction of dynamics.

Our new preprint 👀

Our work on how continuous attractors emerge in unstructured RNNs is now out in PRX Life #PRXLife : journals.aps.org/prxlife/abst... Work done with @tankutcan.bsky.social @sesamedusa.bsky.social

I'll be presenting this at #cosyne2025 (poster 3-50)! I'll also be giving a talk at the "Collectively Emerged Timescales" workshop on this work, plus other projects on emergent dynamics in neural circuits. Looking forward to seeing everyone in 🇨🇦!

Excited to present the latest from the lab out today in Cell www.cell.com/cell/fulltex.... See Thread! 1/8

We always see that 1) neural responses are very diverse 2) the shattering dimensionality is as high as it can be. Now also in an extensive analysis of the IBL dataset. Wonderful collaboration with @lorenzoposani.com, Shuqi Wang, Samuel Muscinelli, Liam Paninski. Many new analyses in this new version

(1/5) Excited to share my work with @engeltatiana.bsky.social , out now in Nat Neuro! We show that RNNs use low-d latent circuit mechanisms for cognitive tasks. We find that context-dependent decisions in both RNNs and PFC arise from latent inhibitory mechanisms. www.nature.com/articles/s41...

Our new paper with @chrismlangdon is just out in @natureneuro.bsky.social! We show that high-dimensional RNNs use low-dimensional circuit mechanisms for cognitive tasks and identify a latent inhibitory mechanism for context-dependent decisions in PFC data. www.nature.com/articles/s41...

(1/30) New preprint! "Symmetries and continuous attractors in disordered neural circuits" with Larry Abbott and Haim Sompolinsky bioRxiv: www.biorxiv.org/content/10.1...

Pre-print 🧠🧪 Is mechanism modeling dead in the AI era? ML models trained to predict neural activity fail to generalize to unseen opto perturbations. But mechanism modeling can solve that. We say "perturbation testing" is the right way to evaluate mechanisms in data-constrained models 1/8

The unbearable slowness of being: Humans still clock in at just 10 bits/s. Even after peer review :) Share link: authors.elsevier.com/a/1kHVa3BtfH.... ArXiv: arxiv.org/abs/2408.10234

The official ad for this postdoc position is now (finally) live, see academicpositions.harvard.edu/postings/14486!

(1/5) Fun fact: Several classic results in the stat. mech. of learning can be derived in a couple lines of simple algebra! In this paper with Haim Sompolinsky, we simplify and unify derivations for high-dimensional convex learning problems using a bipartite cavity method. arxiv.org/abs/2412.01110

I've been pondering a lot on what is the most efficient entry route into the "fancy" ML stuff today for a dummy*. this is the roadmap I ended up with, and it's disappointing how little prob/stats you need—just Gaussians 🐢. *🙋‍♂️ me. I was the dummy, as I was getting ready to start a postdoc 4yrs ago.

I have created this space to focus on theoretical neuroscience. Totally biased to theory. go.bsky.app/3TNRgME

Joint the Comp Neuro conversation go.bsky.app/K8hiHqe