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We study a model of interacting neurons. The structure of this neural system is composed of two layers of neurons such that the neurons of the first layer send their spikes to the neurons of the second one: if $N$ is the number of neurons…

概率论 · 数学 2023-06-22 Xavier Erny

We study the solutions of a McKean-Vlasov stochastic differential equation (SDE) driven by a Poisson process. In neuroscience, this SDE models the mean field limit of a system of $N$ interacting excitatory neurons with $N$ large. Each…

概率论 · 数学 2025-08-27 Romain Veltz

Neurons are spatially extended cells; different parts of a neuron have specific voltage dynamics. Important types of neurons even generate different spikes in different parts of the cell. Neurons' inputs are also often spatially…

神经元与认知 · 定量生物学 2026-02-06 Audrey O'Brien Teasley , Gabriel Koch Ocker

We consider a stochastic model describing the spiking activity of a countable set of neurons spatially organized into a homogeneous tree of degree $d$, $d \geq 2$; the degree of a neuron is just the number of connections it has. Roughly,…

概率论 · 数学 2022-05-17 A. M. B. Nascimento

We consider a model of interacting neurons where the membrane potentials of the neurons are described by a multidimensional piecewise deterministic Markov process (PDMP) with values in ${\mathbb R}^N, $ where $ N$ is the number of neurons…

统计理论 · 数学 2016-10-04 Pierre Hodara , Nathalie Krell , Eva Löcherbach

We continue the work of a series of previous studies of a mathematical model that describes the mean-field limit behavior of a homogeneous network of excitatory point spiking neurons. Contrary to other models, here noise is intrinsic to the…

神经元与认知 · 定量生物学 2017-07-20 Guillem Via

We continue the study of a stochastic system of interacting neurons introduced in De Masi-Galves-L\"ocherbach-Presutti (2014). The system consists of N neurons, each spiking randomly with rate depending on its membrane potential. At its…

概率论 · 数学 2015-05-05 Nicolas Fournier , Eva Löcherbach

We study the stochastic system of interacting neurons introduced in De Masi et al. (2015) and in Fournier and L\"ocherbach (2016) in a diffusive scaling. The system consists of $N$ neurons, each spiking randomly with rate depending on its…

概率论 · 数学 2020-03-03 Xavier Erny , Eva Löcherbach , Dasha Loukianova

The activity of a neural network is defined by patterns of spiking and silence from the individual neurons. Because spikes are (relatively) sparse, patterns of activity with increasing numbers of spikes are less probable, but with more…

神经元与认知 · 定量生物学 2025-02-13 Gasper Tkacik , Thierry Mora , Olivier Marre , Dario Amodei , Michael J. Berry , William Bialek

We study a stochastic system of interacting neurons and its metastable properties. The system consists of $N$ neurons, each spiking randomly with rate depending on its membrane potential. At its spiking time, the neuron potential is reset…

概率论 · 数学 2020-12-09 Eva Löcherbach , Pierre Monmarché

We consider finite systems of $N$ interacting neurons described by non-linear Hawkes processes in a mean field frame. Neurons are described by their membrane potential. They spike randomly, at a rate depending on their potential. In between…

概率论 · 数学 2025-07-01 Aline Duarte , Kadmo Laxa , Eva Löcherbach , Dasha Loukianova

This paper studies the hydrodynamic limit of a stochastic process describing the time evolution of a system with N neurons with mean-field interactions produced both by chemical and by electrical synapses. This system can be informally…

概率论 · 数学 2016-08-08 Anna De Masi , Antonio Galves , Eva Löcherbach , Errico Presutti

Neurons primarily communicate through the emission of action potentials, or spikes. To generate a spike, a neuron's membrane potential must cross a defined threshold. Does this spiking mechanism inherently prevent neurons from transmitting…

神经元与认知 · 定量生物学 2025-01-24 Valentin Schmutz

We consider a system of $N$ neurons, each spiking randomly with rate depending on its membrane potential. When a neuron spikes, its potential is reset to $0$ and all other neurons receive an additional amount $h/N$ of potential, where $ h >…

概率论 · 数学 2022-01-25 Eva Löcherbach

Many biological neuronal networks exhibit highly variable spiking activity. Balanced networks offer a parsimonious model of this variability. In balanced networks, strong excitatory synaptic inputs are canceled by strong inhibitory inputs…

神经元与认知 · 定量生物学 2016-05-04 Ryan Pyle , Robert Rosenbaum

The net of N ``physical'' neurons is considered as a dynamical system. These neurons form a complete graph. The state of any neuron is its electric potential. The potential linearly increases until reaches its maximal value. Then it falls…

动力系统 · 数学 2025-10-28 S. A. Pirogov , A. N. Rybko , D. D. Pervouchine , E. N. Petrova

We consider the stochastic system of interacting neurons introduced in De Masi et al. (2015) and in Fournier and L\"ocherbach (2016) and then further studied in Erny, L\"ocherbach and Loukianova (2021) in a diffusive scaling. The system…

概率论 · 数学 2022-11-30 Xavier Erny , Eva Löcherbach , Dasha Loukianova

The critical brain hypothesis receives increasing support from recent experimental results. It postulates that the brain is at a critical point between an ordered and a chaotic regime, sometimes referred to as the "edge of chaos." Another…

无序系统与神经网络 · 物理学 2022-02-08 Lorenz Baumgarten , Stefan Bornholdt

This paper proposes a neuronal circuitry layout and synaptic plasticity principles that allow the (pyramidal) neuron to act as a "combinatorial switch". Namely, the neuron learns to be more prone to generate spikes given those combinations…

生物物理 · 物理学 2017-05-09 Marat M. Rvachev

In recurrent networks of leaky integrate-and-fire (LIF) neurons, mean-field theory has proven successful in describing various statistical properties of neuronal activity at equilibrium, such as firing rate distributions. Mean-field theory…

神经元与认知 · 定量生物学 2023-11-10 Marina Vegué , Antoine Allard , Patrick Desrosiers
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