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In this work, we propose a nonlinear stochastic model of a network of stochastic spiking neurons. We heuristically derive the mean-field limit of this system. We then design a Monte Carlo method for the simulation of the microscopic system,…

Numerical Analysis · Mathematics 2019-06-26 Benjamin Aymard , Fabien Campillo , Romain Veltz

Biochemical reaction networks are subjected to large fluctuations attributable to small molecule numbers, yet underlie reliable biological functions. Most theoretical approaches describe them as purely deterministic or stochastic dynamical…

Molecular Networks · Quantitative Biology 2013-06-11 Jingkui Wang , Marc Lefranc , Quentin Thommen

Excitable cellular automata with dynamical excitation interval exhibit a wide range of space-time dynamics based on an interplay between propagating excitation patterns which modify excitability of the automaton cells. Such interactions…

Cellular Automata and Lattice Gases · Physics 2015-06-11 Andrew Adamatzky

We study the evolution of a random weighted network with complex nonlinear dynamics at each node, whose activity may cease as a result of interactions with other nodes. Starting from a knowledge of the micro-level behaviour at each node, we…

Statistical Mechanics · Physics 2007-05-23 Sitabhra Sinha , Sudeshna Sinha

Evolution of a system of diffusing and proliferating mortal reactants is analyzed in the presence of randomly moving catalysts. While the continuum description of the problem predicts reactant extinction as the average growth rate becomes…

Soft Condensed Matter · Physics 2009-10-31 N. M. Shnerb , E. Bettelheim , Y. Louzoun , O. Agam , S. Solomon

We propose the concepts of distributed robustness and r-robustness, well adapted to functional genetics. Then we discuss the robustness of the relaxation time using a chemical reaction description of genetic and signalling networks. First,…

Molecular Networks · Quantitative Biology 2011-11-09 A. N. Gorban , O. Radulescu

Many membrane channels and receptors exhibit adaptive, or desensitized, response to a strong sustained input stimulus, often supported by protein activity-dependent inactivation. Adaptive response is thought to be related to various…

Molecular Networks · Quantitative Biology 2015-03-13 Tamar Friedlander , Naama Brenner

We propose a method that allows for a rigorous statistical analysis of neural responses to natural stimuli which are non-Gaussian and exhibit strong correlations. We have in mind a model in which neurons are selective for a small number of…

Biological Physics · Physics 2007-05-23 Tatyana Sharpee , Nicole C. Rust , William Bialek

Networks of contacts capable of spreading infectious diseases are often observed to be highly heterogeneous, with the majority of individuals having fewer contacts than the mean, and a significant minority having relatively very many…

Physics and Society · Physics 2016-12-21 César Parra-Rojas , Thomas House , Alan J. McKane

In the modified bootstrap percolation model, sites in the cube {1,...,L}^d are initially declared active independently with probability p. At subsequent steps, an inactive site becomes active if it has at least one active nearest neighbour…

Probability · Mathematics 2007-05-23 Alexander E. Holroyd

In a series of two papers, we investigate the large deviations and asymptotic behavior of stochastic models of brain neural networks with random interaction coefficients. In this first paper, we take into account the spatial structure of…

Probability · Mathematics 2017-01-05 Tanguy Cabana , Jonathan Touboul

Highly stratified shear layers are rendered unstable even at high stratifications by Holmboe instabilities when the density stratification is concentrated in a small region of the shear layer. These instabilities may cause mixing in highly…

Fluid Dynamics · Physics 2017-08-29 Navid C. Constantinou , Petros J. Ioannou

Biological neural networks are notoriously hard to model due to their stochastic behavior and high dimensionality. We tackle this problem by constructing a dynamical model of both the expectations and covariances of the fractions of active…

Neurons and Cognition · Quantitative Biology 2025-02-25 Vincent Painchaud , Patrick Desrosiers , Nicolas Doyon

We propose a method that would allow for a rigorous statistical analysis of neural responses to natural stimuli, which are non-Gaussian and exhibit strong correlations. We have in mind a model in which neurons are selective for a small…

Biological Physics · Physics 2007-05-23 Tatyana Sharpee , Nicole C. Rust , William Bialek

In the presence of multiscale dynamics in a reaction network, direct simulation methods become inefficient as they can only advance the system on the smallest scale. This work presents stochastic averaging techniques to accelerate…

Probability · Mathematics 2016-03-23 Araz Hashemi , Marcel Nunez , Petr Plechac , Dionisios G. Vlachos

For the reaction networks with one-dimensional stoichiometric subspaces, we show the following results. (1) If the maximum number of positive steady states is an even number N, then the maximum number of stable positive steady states is…

Dynamical Systems · Mathematics 2021-02-22 Xiaoxian Tang , Zhishuo Zhang

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively…

Neurons and Cognition · Quantitative Biology 2016-03-17 Luca Mazzucato , Alfredo Fontanini , Giancarlo La Camera

Within the cell, biopolymers are often situated in constrained, fluid environments, e.g., cytoskeletal networks, stretched DNAs in chromatin. It is of paramount importance to understand quantitatively how they, utilizing their flexibility,…

Biological Physics · Physics 2012-08-27 Won Kyu Kim , Wokyung Sung

The excess power, energy and intensity of a random electromagnetic field above a high threshold level are characterized based on a Slepian--Kac model for upcrossings. For quasi-static fields, the probability distribution of the excess…

Applied Physics · Physics 2020-12-14 Luk R. Arnaut

We study the stochastic dynamics of strongly-coupled excitable elements on a tree network. The peripheral nodes receive independent random inputs which may induce large spiking events propagating through the branches of the tree and leading…

Biological Physics · Physics 2017-07-14 Justus Kromer , Ali Khaledi-Nasab , Lutz Schimansky-Geier , Alexander B. Neiman