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...

Excited to share our new work with @engeltatiana.bsky.social! RNNs are often used to explore how the brain may solve specific tasks. We show that, depending on the architecture, RNNs find distinct circuit solutions, behaving differently when exposed to novel stimuli. www.nature.com/articles/s42...

To the math/comp neuro folks in Oxford. I'll be giving a math neuro talk in the Partial Differential Equations Seminar at the MI on Monday 27 Oct at 16:30 (details in the link). www.maths.ox.ac.uk/node/74242 I'll be talking about the "universality" of spatially extended mean-field PDEs (see 🧵⬇️)

A study led by Cina Aghamohammadi is now out in ‪@natcomms.nature.com‬! We developed a mathematical framework for partitioning spiking variability, which revealed that spiking irregularity is nearly invariant for each neuron and decreases along the cortical hierarchy. www.nature.com/articles/s41...

Message for participants of the #SNUFA 2025 spiking neural network workshop. We got almost 60 awesome abstract submissions, and we'd now like your help to select which ones should be offered talks. Follow the "abstract voting" link at snufa.net/2025/ to take part. It should take <15m. Thanks! ❤️

New in @pnas.org: doi.org/10.1073/pnas... We study how humans explore a 61-state environment with a stochastic region that mimics a “noisy-TV.” Results: Participants keep exploring the stochastic part even when it’s unhelpful, and novelty-seeking best explains this behavior. #cogsci #neuroskyence

🎉 "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

Submissions (short!) due for SNUFA spiking neural networks conference in <2 weeks! 🤖🧠🧪 forms.cloud.microsoft/e/XkZLavhaJe More info at snufa.net/2025/ Note that we normally get around 700 participants and recordings go on YouTube and get 100s-1000s views. Please repost.

Westlake University (西湖大学), a few hours before the start of this year's Summer School on Mathematical Neuroscience its.westlake.edu.cn/info/1017/28...

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.

🚨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

Glad to see my PhD work out! Thanks to all my collaborators and to Kenneth and Matteo for making this possible!

New by Agnès Landemard (@agnesland.bsky.social‬) & co Brainwide blood volume reflects opposing neural populations Brainwide fluctuations in blood volume arise from two populations with opposite relation to brain state and distinct relationships to blood supply www.biorxiv.org/content/10.1...

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...

Our preprint is finally out! How can we understand the role of Behavioral Timescale Synaptic Plasticity in credit assignment? Does it fit into existing supervised and unsupervised learning frameworks? What theoretical gaps are still left unexplained? www.biorxiv.org/content/10.1...

🚀 We are excited to share that bombcell is now available in Python! 🐍 Automatically sort your units into good/MUA/noise/non-somatic using quality metrics and interpretable & adjustable classification thresholds. pip install and play around with our toy dataset: 🔗 github.com/Julie-Fabre/...

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 👀

Two (tenure track) Junior Professorship Chair in Nice, France on: 'Modeling in Neurosciences and Cognition' math.univ-cotedazur.fr/laboratoire/... 'Mathematics of Life" math.univ-cotedazur.fr/laboratoire/...

Delighted to join the Royal Society of London for Improving Natural Knowledge! It's been in the news since 1660, and more so lately. Grateful to all my collaborators over the years.

Excited to share my PhD paper! In it, we use targeted 2-photon optogenetic stimulation to determine how V1 activity is read-out in a detection task. We found that network influence, not visual coding properties, predicted the impact of ensembles on behavior - contradicting our expectations (1/5).

Many of us use 2p scopes to image 3D volumes of brain. But then we analyze the data plane by plane, resulting in duplicated neurons, missed neurons, and low s/n. Let's go 3D! Suite3D: Volumetric cell detection for two-photon microscopy by @haydari.bsky.social & team. www.biorxiv.org/content/10.1...

I am very proud to announce that my PhD paper finally came out in Cell! In this *very* collaborative study, we develop and release a deep-learning approach to predict neuron type identity from their electrical signature. doi.org/10.1016/j.ce... 1/16 🧵

Thrilled to share our latest work exploring new avenues for combining #Neuropixels with #Optogenetics! Congratulations to co-first author Anna Lakunina, the Neuropixels Opto Consortium and collaborators! www.biorxiv.org/content/10.1...

(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...

What's the right way to think about modularity in the brain? This devilish 😈 question is a big part of my research now, and it started with this paper with @solarpunkgabs.bsky.social, finally published after the first preprint in 2021! 🤖🧠🧪 www.nature.com/articles/s41...

A cool EPFL News article was written about our recent neurotheory paper on spikes vs rates! Super engaging text by science communicater Nik Papageorgiou. actu.epfl.ch/news/brain-m... Definitely more accessible than the original physics-style, 4.5-page letter 🤓 journals.aps.org/prl/abstract...

Super excited to see my PhD thesis featured by EPFL! 🎓 actu.epfl.ch/news/learnin... P.S.: There's even a French version of the article! It feels so fancy! 😎 👨‍🎨 🇫🇷 actu.epfl.ch/news/apprend...

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

New round of spike vs rate? The concentration of measure phenomenon can explain the emergence of rate-based dynamics in networks of spiking neurons, even when no two neurons are the same. This is what's shown in the last paper of my PhD, out today in Physical Review Letters 🎉 tinyurl.com/4rprwrw5

New results! Visual adaptation changes the geometry of V1 population activity: frequent stimuli elicit smaller responses but become more discriminable. Similar results are seen in ANNs trained with metabolic constraints, suggesting these changes emerge from efficient coding. bit.ly/3VJHXRn

Our preprint with @frostedblakess.bsky.social, @jzv.bsky.social, @cpehlevan.bsky.social is out! We develop a simple reinforcement learning model that recapitulates 3 disparate hippocampal dynamics. With ablation studies, these representations improve the speed and flexibility of policy learning.

"It's the clarity that made the impact." – W. Gerstner

Here are some things that neuroscientists don't like to call "correlation": 1990s: "reverse correlation" 2000s: "granger causality" 2010s: "functional connectivity" 2020s: "subspace communication"

Synaptic weight scaling in O(1/N) self-induces a form of (implicit) spatial structure in networks of spiking neurons, as the number of neurons N tends to infinity. This is what D.T. Zhou, P.-E. Jabin and I prove in arxiv.org/abs/2409.06325. 1/6 🧵