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相关论文: Stability of splay states in globally coupled rota…

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The stability of the dynamical states characterized by a uniform firing rate ({\it splay states}) is analyzed in a network of globally coupled leaky integrate-and-fire neurons. This is done by reducing the set of differential equations to a…

无序系统与神经网络 · 物理学 2007-11-27 Rüdiger Zillmer , Roberto Livi , Antonio Politi , Alessandro Torcini

We analytically investigate the stability of {\it splay states} in networks of $N$ pulse-coupled phase-like models of neurons. By developing a perturbative technique, we find that, in the limit of large $N$, the Floquet spectrum scales as…

无序系统与神经网络 · 物理学 2014-09-08 Simona Olmi , Antonio Politi , Alessandro Torcini

The emergence and stability of splay states is studied in fully coupled finite networks of N excitable quadratic integrate-and-fire neurons, connected via synapses modeled as pulses of finite amplitude and duration. For such synapses, by…

无序系统与神经网络 · 物理学 2012-08-23 Mario Dipoppa , Martin Krupa , Alessandro Torcini , Boris S. Gutkin

A mystery surrounds the stability properties of the splay-phase periodic solutions to a series array of N Josephson junction oscillators. Contrary to what one would expect from dynamical systems theory, the splay state appears to be…

adap-org · 物理学 2015-06-30 Shinya Watanabe , James W. Swift

We study the dynamical stability of pulse coupled networks of leaky integrate-and-fire neurons against infinitesimal and finite perturbations. In particular, we compare current versus fluctuations driven networks, the former (latter) is…

无序系统与神经网络 · 物理学 2015-06-18 David Angulo-Garcia , Alessandro Torcini

In the present work, we revisit a recently proposed and experimentally realized topological 2D lattice with periodically time-dependent interactions. We identify the fundamental solitons, previously observed in experiments and direct…

斑图形成与孤子 · 物理学 2022-04-26 Ross Parker , Jesús Cuevas-Maraver , P. G. Kevrekidis , Alejandro Aceves

We experimentally investigate the stability of a quantum gas with repulsive interactions in an optical 1D lattice subjected to periodic driving. Excitations of the gas in the lowest lattice band are analyzed across the complete stability…

We study analytically the dynamics of a network of sparsely connected inhibitory integrate-and-fire neurons in a regime where individual neurons emit spikes irregularly and at a low rate. In the limit when the number of neurons N tends to…

无序系统与神经网络 · 物理学 2007-05-23 N. Brunel , V. Hakim

This paper studies the stability of synchronized states in networks where couplings between nodes are characterized by some distributed time delay, and develops a generalized master stability function approach. Using a generic example of…

混沌动力学 · 物理学 2014-10-28 Y. N. Kyrychko , K. B. Blyuss , E. Schoell

We investigate a stochastic network composed of Integrate-and-Fire spiking neurons, focusing on its mean-field asymptotics. We consider an invariant probability measure of the McKean-Vlasov equation and establish an explicit sufficient…

概率论 · 数学 2024-10-02 Quentin Cormier

Firing rate fluctuations in neural populations are observed experimentally over multiple time scales, in single neurons, across trials when elicited by stimuli, and across populations. In this work, we examine how firing rate fluctuations…

神经元与认知 · 定量生物学 2026-05-15 Wilten Nicola , Sue Ann Campbell

We investigate the dynamics of a neural network where each neuron evolves according to the combined effects of deterministic integrate-and-fire dynamics and purely inhibitory coupling with K randomly-chosen "neighbors". The inhibition…

适应与自组织系统 · 物理学 2009-11-07 P. L. Krapivsky , S. Redner

We consider an electrical chain of N nonlinear capacitors coupled by linear inductors assuming that voltage dependence of capacitors represents an even function. We prove that only 5 symmetry determined nonlinear normal modes (NNM) can…

斑图形成与孤子 · 物理学 2014-07-08 G. M. Chechin , S. A. Shcherbinin

Neural network dynamics emerge from the interaction of spiking cells. One way to formulate the problem is through a theoretical framework inspired by ideas coming from statistical physics, the so-called mean-field theory. In this document,…

偏微分方程分析 · 数学 2020-11-11 Grégory Dumont , Pierre Gabriel

Spiking neural networks (SNNs) are a promising paradigm for energy-efficient computation, yet their theoretical foundations-especially regarding stability and robustness-remain limited compared to artificial neural networks. In this work,…

机器学习 · 计算机科学 2025-11-25 Ernesto Araya , Massimiliano Datres , Gitta Kutyniok

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 study the long time evolution and stationary speed distribution of N point particles in 2D moving under the action of an external field E, and undergoing elastic collisions with either a fixed periodic array of convex scatterers, or with…

混沌动力学 · 物理学 2012-10-30 Federico Bonetto , Nikolai Chernov , Alexey Korepanov , Joel Lebowitz

In a first step towards the comprehension of neural activity, one should focus on the stability of the various dynamical states. Even the characterization of idealized regimes, such as a perfectly periodic spiking activity, reveals…

无序系统与神经网络 · 物理学 2014-09-08 Simona Olmi , Antonio Politi , Alessandro Torcini

In this note, we announce a complete classification of stability of periodic roll-wave solutions of the viscous shallow-water equations, from their onset at Froude number $F\approx 2$ up to the infinite-Froude limit. For intermediate Froude…

流体动力学 · 物理学 2016-06-08 Blake Barker , Mathew A. Johnson , Pascal Noble , L. Miguel Rodrigues , Kevin Zumbrun

We analyze the dynamics of networks of spiking neural oscillators. First, we present an exact linear stability theory of the synchronous state for networks of arbitrary connectivity. For general neuron rise functions, stability is…

神经元与认知 · 定量生物学 2009-11-11 Marc Timme , Theo Geisel , Fred Wolf
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