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Related papers: Hydrodynamic limit for interacting neurons

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An accurate description of the structure and dynamics of interfacial water is essential for phospholipid membranes, since it determines their function and their interaction with other molecules. Here we consider water confined in stacked…

Soft Condensed Matter · Physics 2018-11-16 Sotiris Samatas , Carles Calero , Fausto Martelli , Giancarlo Franzese

We consider the hydrodynamic behavior of some conservative particle systems with degenerate jump rates without exclusive constraints. More precisely, we study the particle systems without restrictions on the total number of particles per…

Probability · Mathematics 2017-05-01 Makiko Sasada

We study the asymptotic law of a network of interacting neurons when the number of neurons becomes infinite. The dynamics of the neurons is described by a set of stochastic differential equations in discrete time. The neurons interact…

Probability · Mathematics 2014-07-10 Olivier Faugeras , James MacLaurin

There have been suggestions that heat caused by cerebral metabolic activity may constrain mammalian brain evolution, architecture, and function. This article investigates physical limits on brain wiring and corresponding changes in brain…

Neurons and Cognition · Quantitative Biology 2024-04-23 Jan Karbowski

We study the hydrodynamic limit for a periodic $1$-dimensional exclusion process with a dynamical constraint, which prevents a particle at site $x$ from jumping to site $x\pm1$ unless site $x\mp1$ is occupied. This process with degenerate…

Probability · Mathematics 2020-10-23 Oriane Blondel , Clément Erignoux , Makiko Sasada , Marielle Simon

We consider the behaviour of branching-selection particle systems in the large population limit. The dynamics of these systems is the combination of the following three components: (a) Motion: particles move on the real line according to a…

Probability · Mathematics 2023-11-22 Jean Bérard , Brieuc Frénais

We study the symmetric facilitated exclusion process (FEP) on the finite one-dimensional lattice $\lbrace 1,\dots ,N-1\rbrace$ when put in contact with boundary reservoirs, whose action is subject to an additional kinetic constraint in…

Probability · Mathematics 2026-02-09 Hugo Da Cunha , Clément Erignoux , Marielle Simon

We report a detailed study of neuromorphic switching behaviour in inherently complex percolating networks of self-assembled metal nanoparticles. We show that variation of the strength and duration of the electric field applied to this…

Disordered Systems and Neural Networks · Physics 2019-03-06 S. K. Bose , S. Shirai , J. B. Mallinson , S. A. Brown

Consider a large number $n$ of neurons, each being connected to approximately $N$ other ones, chosen at random. When a neuron spikes, which occurs randomly at some rate depending on its electric potential, its potential is set to a minimum…

Probability · Mathematics 2020-03-19 Nicolas Fournier , Etienne Tanré , Romain Veltz

This is the first of two articles on the study of a particle system model that exhibits a Turing instability type effect. The model is based on two discrete lines (or toruses) with Ising spins, that evolve according to a continuous time…

Probability · Mathematics 2017-07-19 Monia Capanna , Nahuel Soprano-Loto

Hydrodynamics provides a successful framework to effectively describe the dynamics of complex many-body systems ranging from subnuclear to cosmological scales by introducing macroscopic quantities such as particle densities and fluid…

We introduce a novel, biologically plausible local learning rule that provably increases the robustness of neural dynamics to noise in nonlinear recurrent neural networks with homogeneous nonlinearities. Our learning rule achieves higher…

Neurons and Cognition · Quantitative Biology 2022-10-12 Christopher H. Stock , Sarah E. Harvey , Samuel A. Ocko , Surya Ganguli

In this paper the first equation within a class of well known chemotaxis systems is derived as a hydrodynamic limit from a stochastic interacting many particle system on the lattice. The cells are assumed to interact with attractive…

Probability · Mathematics 2018-04-26 Stefan Grosskinsky , Daniel Marahrens , Angela Stevens

At chemical synapses, an arriving electric signal induces the fusion of vesicles with the presynaptic membrane, thereby releasing neurotransmitters into the synaptic cleft. After a fusion event, both the release site and the vesicle undergo…

Dynamical Systems · Mathematics 2023-07-06 Ariane Ernst , Nathalie Unger , Christof Schütte , Alexander Walter , Stefanie Winkelmann

We consider a neural network with adapting synapses whose dynamics can be analitically computed. The model is made of $N$ neurons and each of them is connected to $K$ input neurons chosen at random in the network. The synapses are…

Disordered Systems and Neural Networks · Physics 2009-10-30 G. Lattanzi , G. Nardulli , G. Pasquariello , S. Stramaglia

Spiking neural networks coupled with neuromorphic hardware and event-based sensors are getting increased interest for low-latency and low-power inference at the edge. However, multiple spiking neuron models have been proposed in the…

Neural and Evolutionary Computing · Computer Science 2022-11-16 Mohamed Sadek Bouanane , Dalila Cherifi , Elisabetta Chicca , Lyes Khacef

We report experimental studies of synchronization phenomena in a pair of biological neurons that interact through naturally occurring, electrical coupling. When these neurons generate irregular bursts of spikes, the natural coupling…

In this paper we consider a symmetric simple exclusion process (SSEP) on the $d$-dimensional discrete torus $\mathbb{T}^d_N$ with a spatial non-homogeneity given by a slow membrane. The slow membrane is defined here as the boundary of a…

Probability · Mathematics 2019-03-27 Tertuliano Franco , Mariana Tavares

The generation of action potential brings into play specific mechanosensory stimuli manifest in the variation of membrane capacitance, resulting from the selective membrane permeability to ions exchanges and testifying to the central role…

Neurons and Cognition · Quantitative Biology 2021-02-23 Alain M. Dikande

We deal with the problem of bridging the gap between two scales in neuronal modeling. At the first (microscopic) scale, neurons are considered individually and their behavior described by stochastic differential equations that govern the…

Biological Physics · Physics 2010-11-09 Olivier Faugeras , Jonathan Touboul , Bruno Cessac
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