This September, I will join the @flatironinstitute.org Center for Computational Neuroscience as a Group Leader, where I will launch the High-Dimensional Dynamics & Computation Group. Information for postdocs and grad students is forthcoming. I am grateful to my mentors who made this possible!

Our paper "Rarely categorical, highly separable representations along the cortical hierarchy" is now out in Nature! www.nature.com/articles/s41... In this paper, we studied whether the brain is well-organized and interpretable, both globally and locally. (See thread below.)

Both brains and RNNs can re-use components of computation across similar tasks or contexts. But what exactly are those “shared components”? How can they be used to solve several tasks? We address these questions in a new preprint with @avm.bsky.social! Link: www.biorxiv.org/content/10.6...

Interpretable compositional computation with recurrent neural networks

Flexible cognition utilizes reusable components to enable rapid adaptation of behavior to different contexts or tasks. Analysis of artificial neural networks trained on multiple tasks suggested that t...

biorxiv.org

Tremendously excited to announce that I will be joining @rockefeller.edu as an Assistant Professor and Head of Lab starting in January 2027! My group will be broadly focused on theoretical neuroscience, and mathematical problems in neural computation in the large.

New method for identifying the fine transcriptomic types of thousands of neurons recorded in vivo!

Unbelievably honoured to read Tatiana Engel's (@engeltatiana.bsky.social) wonderfully written Preview on our work "Linking neural manifolds to circtuit structure in recurrent networks" (with @lpezon.bsky.social & @gerstnerlab.bsky.social) in this issue of Neuron www.cell.com/neuron/fullt... 🙏

Finding clues to circuit structure in population dynamics and single-neuron selectivity

In this issue of Neuron, Pezon et al. introduce neural circuit models with flexible connectivity structure that can generate low-dimensional population dynamics with different distributions of single-...

cell.com

There is still time to apply to join our lab as a PhD student At @kavlintnu.bsky.social 💻🧠🇳🇴 www.jobbnorge.no/en/available... Apply before May 6.

PhD in Computational Neuroscience (298392) | NTNU - Norwegian University of Science and Technology

Job title: PhD in Computational Neuroscience (298392), Employer: NTNU - Norwegian University of Science and Technology, Deadline: Wednesday, May 6, 2026

jobbnorge.no

How do the basal ganglia turn what you see into what you do? New preprint w/ @kenneth-harris.bsky.social, @flickerfusion.bsky.social & @carandinilab.net: we recorded across striatum, GPe & SNr in a Go/NoGo task. Striatum encodes which stimulus, GPe & SNr encode action. 🧵 biorxiv.org/content/10.6...

Really excited to share a new preprint! 𝗛𝗼𝘄 𝗱𝗼 𝗯𝗿𝗮𝗶𝗻𝘀 𝘀𝘁𝗮𝘆 𝗿𝗼𝗯𝘂𝘀𝘁 & 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝘄𝗵𝗶𝗹𝗲 𝗯𝗲𝗶𝗻𝗴 𝗶𝗻𝗰𝗿𝗲𝗱𝗶𝗯𝗹𝘆 𝘀𝗽𝗮𝗿𝘀𝗲? We explore how! www.biorxiv.org/content/10.6... We built Connectome-based Neural Networks (CoNNs) using Drosophila wiring (larva&adult) & compared with random networks with same sparsity.

Ten years ago, I did a research internship with Tilo Schwalger (then in the @gerstnerlab.bsky.social) on deriving mean-field equations from networks of interacting neurons – I have been doing that ever since. I'm still very fond of the way he explains things "à la physicienne".

Gaute Einevoll@gauteeinevoll.bsky.social · 4mo ago

Episode #39 in #TheoreticalNeurosciencePodcast: On modeling neural population activity with mean-field models – with Tilo Schwalger theoreticalneuroscience.no/thn39 How can mean‑field models be systematically derived from the underlying microscopic dynamics of individual neurons?

Cortical circuits are often thought to be specialized, but the same large-scale activity patterns can arise from different circuit architectures. In other words, different instruments can play the same tune, and the same instrument can sometimes play different tunes. www.cell.com/neuron/fullt...

Linking neural manifolds to circuit structure in recurrent networks

Neural population activity can be described either by low-dimensional dynamics on neural manifolds or by single-neuron selectivities. Using a theoretical approach, Pezon et al. relate these two statis...

cell.com

I thought this was an exciting new theoretical perspective www.cell.com/neuron/fullt...

Linking neural manifolds to circuit structure in recurrent networks

Neural population activity can be described either by low-dimensional dynamics on neural manifolds or by single-neuron selectivities. Using a theoretical approach, Pezon et al. relate these two statis...

cell.com

Travelling to COSYNE seems to be the perfect opportunity to announce that I started my own lab at RWTH Aachen University earlier this year, funded by NRW's Ministry of Culture and Science through its Return Program. If you are at COSYNE and want to chat please reach out!

𝗪𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗿𝗲𝗹𝗮𝘁𝗶𝗼𝗻𝘀𝗵𝗶𝗽 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗺𝗮𝗻𝗶𝗳𝗼𝗹𝗱𝘀 𝗮𝗻𝗱 𝗿𝗲𝗰𝘂𝗿𝗿𝗲𝗻𝘁 𝗻𝗲𝘁𝘄𝗼𝗿𝗸𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗯𝗿𝗮𝗶𝗻? This looks like a must read (suppl material bursting with goodies). #neuroskeyence doi.org/10.1016/j.ne...

How are neural manifolds and single-neuron response properties related to circuit structure? How degenerate are these relationships? Theory and a plethora of examples can be found in the following paper, out today in Neuron 🌟 It was a privilege to co-supervise first author @lpezon.bsky.social!

Louis Pezon@lpezon.bsky.social · 5mo ago

Excited to share our new paper to be published in Neuron! With Valentin Schmutz @bio-emergent.bsky.social and Wulfram Gerstner @gerstnerlab.bsky.social, we explore how circuit structure in RNNs shapes network computation and single-neuron responses. www.sciencedirect.com/science/arti...

These workshops are absolutely amazing. I had the privilege to attend the theoretical neuroscience workshop in 2024; it was a memorable week.

Janelia Conferences@janeliaconf.bsky.social · 6mo ago

Apply by May 7 for two early-career #neuro workshops at Janelia! Featuring joint sessions to foster collaboration between theory & experiment. 🧠 🤝 Theoretical Neuroscience→ janelia.news/THE26 Mechanistic Cognitive Neuroscience→ janelia.news/CNW26 @ratecoding.bsky.social @jvoigts.bsky.social

Applications are now open for the summer school: 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐚𝐥 𝐌𝐞𝐭𝐡𝐨𝐝𝐬 𝐢𝐧 𝐂𝐨𝐦𝐩𝐮𝐭𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐍𝐞𝐮𝐫𝐨𝐬𝐜𝐢𝐞𝐧𝐜𝐞 🧠 Apply before March 15: www.compneuronrsn.org 📍 Located in beautiful Eresfjord 🇳🇴 🗓️ Between July 6-24 Supported by the @kavlifoundation.org In collaboration with @kavlintnu.bsky.social

Mathematical Methods in Computational Neuroscience

Summer school in Eresfjord, Norway (July 8th - 26th, 2024)

compneuronrsn.org

Turns out deep neural networks are better at extracting relevant features than I am... Meet "DeepUnitMatch", a DNN version of our neuron tracking tool: www.biorxiv.org/content/10.6... It has been a privilage to continue the collaboration with Célian, and cosupervise the talented Suyash & Wentao!

Summer school on Neuro AI in Cambridge. Registration Deadline: 16 Feb 2026 Speaker line up: G. Bellec A. Billard R. Bogacz R. Ponte Costa W. Gerstner M. Giugliano L. Hunt M. Sahani P. Series P. Tino www.fens.org/news-activit...

FENS-Chen Institute Summer Program on AI-Accelerated Neuroscience Discovery and Translation hosted by the University of Cambridge - Federation of European Neuroscience Societies

Application Submission Deadline: Monday 16th February 2026, midnight Applications will be open from Thursday 8th January to midnight on Monday 16th February. The application form and further details…

fens.org

Estimating the power-law exponent of the tail of the eigenspectrum from noisy data is a difficult problem. Here is an approach based on eigenmoment estimation. 👏🏻 A hard stats problem remains open: Can we find an estimator of the tail exponent for which we can PROVE unbiasedness, consistency, etc.?

@deanpospisil.bsky.social · 6mo ago

New paper out at PNAS: www.pnas.org/doi/10.1073/... Revisiting the high-dimensional geometry of population responses in the visual cortex with @jpillowtime.bsky.social. The review took forever because a reviewer was doubtful our new estimator can infer eigenvalues beyond the rank of the data! (1/6)

Talk on "High-dimensional neuronal activity from low-dimensional latent dynamics" at NeurIPS 2025 with @haydari.bsky.social now accessible online 🎥: neurips.cc/virtual/2025... Please reach out if you have any comments or ideas for follow-up work!

If you recently finished your PhD in ML for life science and are looking for a new job early next year, please apply! Göttingen is a lovely town and a great scientific environment.

Fabian Sinz@sinzlab.bsky.social · 8mo ago

🔬 We're hiring a Junior Group Leader for Data-Driven Digital Twins/System Models in medicine/life sciences at @uni_goettingen! Perfect opportunity for early-career researchers who want to: - Lead their own research group - Work at the intersection of AI, simulation, and biomedicine

Very excited about this new work from the omnipotent Owen, with me and Ashok Litwin-Kumar! Can we reconcile low- and high-dimensional activity in neural circuits by recognizing that these circuits ~multitask~? (Plausibly, yes 😊)

Owen Marschall@omarschall.bsky.social · 8mo ago

1/X Excited to present this preprint on multi-tasking, with @david-g-clark.bsky.social and Ashok Litwin-Kumar! Timely too, as “low-D manifold” has been trending again. (If you read thru the end, we escape Flatland and return to the glorious high-D world we deserve.) www.biorxiv.org/content/10.6...

I'm more and more convinced that low-dimensional manifolds in the brain are just an artifact of the experimental designs and analyses we use... 🧠📈 🧪

Mick Bonner@mickbonner.bsky.social · 8mo ago

Dimensionality reduction may be the wrong approach to understanding neural representations. Our new paper shows that across human visual cortex, dimensionality is unbounded and scales with dataset size—we show this across nearly four orders of magnitude. journals.plos.org/ploscompbiol...

"Low-d neural activity" would probably look high-D if you plot the spectrum on a log-log scale. @engeltatiana.bsky.social made a similar point recently on @braininspired.bsky.social. Also agrees with our claim with @bio-emergent.bsky.social that low-D and high-D can be two sides of the same coin!

Best part about being a scientist is the people I get to work with. Valentin (@bio-emergent.bsky.social) and I got to give a talk at NeurIPS, bridging a gap between low- and high-dim perspectives of the brain. Thankfully, the audience was (somewhat) more awake than the San Diego desert 🏜️

Thank you for having me on BrainInspired, Paul @braininspired.bsky.social! It was such an honor to be on my favorite show—a rare place where we can leisurely talk about manifolds, latent circuits, power laws, and other esoteric ideas, and still be taken seriously in knowing they are all real.

Paul Middlebrooks@braininspired.bsky.social · 8mo ago

Are manifolds real? Are latent circuits real? Tatiana @engeltatiana.bsky.social uses one, infers the other, and says yes to both. Also, how timescales are different and the same across the entire brain... braininspired.co/podcast/226/

Tomorrow at #NeurIPS2025! Oral at 10 am in UL Ballroom 20D and poster #2016 at 11 am. @haydari.bsky.social and I are looking forward to hearing your thoughts.

Valentin Schmutz@bio-emergent.bsky.social · 11mo ago

🎉 "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

🧵Excited to present our latest work at #Neurips25! Together with @avm.bsky.social, we discover 𝐜𝐡𝐚𝐧𝐧𝐞𝐥𝐬 𝐭𝐨 𝐢𝐧𝐟𝐢𝐧𝐢𝐭𝐲: regions in neural networks loss landscapes where parameters diverge to infinity (in regression settings!) We find that MLPs in these channels can take derivatives and compute GLUs 🤯

1. New preprint resolving a conundrum in systems neuroscience with an AI scientist, and humans Reilly Tilbury, Dabin Kwon, @haydari.bsky.social, @jacobmratliff.bsky.social, @bio-emergent.bsky.social, @carandinilab.net, @kevinjmiller.bsky.social, @neurokim.bsky.social www.biorxiv.org/content/10.1...

Characterizing neuronal population geometry with AI equation discovery

The visual cortex contains millions of neurons, whose combined activity forms a population code representing visual stimuli. There is, however, a discrepancy between our understanding of this code at ...

biorxiv.org