Valentin Schmutz
@schmutz_val
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Theoretical Neuroscientist | 🔎 Emergent neural population dynamics | Postdoc in Carandini-Harris lab @UCL | PhD from Gerstner lab @EPFL
London, England
Joined November 2023
Concentration of measure, a notion from probability that is oddly little-known in neurotheory, can explain how a heterogeneous population of spiking neurons can approximate rate-based dynamics. This is shown in our new preprint from @compneuro_epfl.
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RT @DynamicsSIAM: Review article: "Nonlinear partial differential equations in neuroscience: from modelling to mathematical theory" (by Jos….
arxiv.org
Many systems of partial differential equations have been proposed as simplified representations of complex collective behaviours in large networks of neurons. In this survey, we briefly discuss...
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RT @bsimsek13: 📢 I'm on the faculty job market this year! . My research explores the foundations of deep learning and analyzes learning and….
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RT @janeliaconf: A big thanks to the early-career researchers who joined us this week @HHMIJanelia for the Junior Scientist Workshop on The….
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RT @soledad_gcogno: Had a great time chatting with @BjksPodcast about so many things, including my journey from 🇦🇷 to 🇳🇴, my lab and our re….
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Congrats Jacob @jzavatoneveth! Looking forward to reading your future work.
Early Independence Awardee Jacob Zavatone-Veth of @Harvard's Society of Fellows is researching how neural networks model large-scale #NeuralData to advance our understanding of #DeepLearning. Read more:
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RT @zdeborova: This mini-review is based on Hugo Cui's PhD thesis: . My advice to him was: "Write something you wo….
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RT @EnnyvBeest: [1/5] Our paper “Tracking neurons across days with high-density probes” is now out in @naturemethods! .
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RT @roxana_zeraati: Headed to @BernsteinNeuro Conference this weekend and interested in how biological computation is performed across diff….
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RT @EnnyvBeest: Excited for Nano42 on 'circuit dynamics across brain regions during navigation (across species)' at #SfN2024. Come check ou….
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6. The proof combines deterministic and probabilistic mean-field methods from interacting particle systems together with results from the theory of dense graph limits (graphons) and Lp spaces. This work was done at @PSUScience with the support of @compneuro_epfl.
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5. This mean-field PDE is a spatially extended version of the mean-field equation rigorously derived by De Masi, Galves, Löcherbach, and Presutti (2015) and conjectured by Gerstner in the '90s.
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4. We show that the stochastic dynamics of any sequence of networks of leaky integrate-and-fire neurons with "escape noise" converges (up to the extraction of a subsequence) to the deterministic solution to a spatially-extended mean-field PDE:
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3. To our knowledge, this surprising mathematical fact hasn't been conjectured, or even hinted at, in theoretical neuroscience. This is probably because this fact stems from relatively recent results in the graph theory (see Large Networks and Graph Limits by L. Lovász, 2012).
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2. This means that neural field-like equations are universal limits of large networks with O(1/N) synaptic weight scaling. Networks do not need to have an explicit spatial structure to converge to a neural field-like equation; O(1/N) weight scaling suffices for that.
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1. 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
The dynamics of spatially-structured networks of $N$ interacting stochastic neurons can be described by deterministic population equations in the mean-field limit. While this is known, a general...
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RT @d_g_clark: 1/ Excited to share new work with @MarschallOwen, @AlexVanMeegen, and Ashok Litwin-Kumar! "Connectivity Structure and Dynami….
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RT @ClaudiaMerger: We computed a fluctuation correction for the spread of disease. The corrections suppress a spurious self-feedback effect….
journals.aps.org
The susceptible-infected-recovered (SIR) model and its variants form the foundation of our understanding of the spread of diseases. Here, each agent can be in one of three states (susceptible,...
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RT @FlaviohMar: 📕Recovering network weights from a set of input-output neural activations 👀.Ever wondered if this is even possible? 🤔. Chec….
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RT @maxime_beau: It is an honour to have been awarded @ucl’s Jon Driver prize for my PhD work in the @NeuralCompLab. I am grateful to @dimv….
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RT @KiaNobre: Yale Psychology Department is hiring!.Open-rank position for a colleague interested in developing and employing novel analyti….
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