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A new lattice model of interacting electrons is presented. It can be viewed as a classical Hubbard model in which the energy associated to electron itinerance is proportional to the total number of possible electron jumps. Symmetry…

Statistical Mechanics · Physics 2009-11-11 Andre M. C. Souza

Subthreshold oscillations in neurons are those oscillations which do not attain the critical value of the membrane's voltage needed for triggering an action potential (a spike). Their contribution to the forming of action potentials in…

Dynamical Systems · Mathematics 2024-03-22 G. Moza , R. Efrem

The extracellular space has an ambiguous role in neuroscience. It is present in every physiologically relevant system and often used as a measurement site in experimental recordings, but it has received subordinate attention compared to the…

Neurons and Cognition · Quantitative Biology 2017-05-02 Jurgis Pods

We propose an equivalent circuit model for photonic spike processing laser neurons with an embedded saturable absorber---a simulation model for photonic excitable lasers (SIMPEL). We show that by mapping the laser neuron rate equations into…

This paper presents an overview of some techniques and concepts coming from dynamical system theory and used for the analysis of dynamical neural networks models. In a first section, we describe the dynamics of the neuron, starting from the…

Adaptation and Self-Organizing Systems · Physics 2011-11-09 B. Cessac , M. Samuelides

A new classical interaction potential for water simulations is presented. Water is modeled as a fully dissociable set of atoms with a point dipole, determined self-consistently, on every oxygen atom. The oxygen polarizability is not fixed…

Condensed Matter · Physics 2009-11-10 E. Lussetti , G. Pastore , E. Smargiassi

In this paper, we present a computational framework based on fully Eulerian models for fluid-structure interaction for the numerical simulation of biological capsules. The flexibility of such models, given by the Eulerian treatment of the…

Fluid Dynamics · Physics 2024-03-20 Florian Desmons , Thomas Milcent , Anne-Virginie Salsac , Mirco Ciallella

We consider a continuum model of electrical signals in the human cortex, which takes the form of a system of semilinear, hyperbolic partial differential equations for the inhibitory and excitatory membrane potentials and the synaptic…

Neurons and Cognition · Quantitative Biology 2015-06-22 Lennaert van Veen , Kevin Green

Action potential generation underlies some of the most consequential dynamical systems on Earth, from brains to hearts. It is therefore interesting to develop synthetic cell-free systems, based on the same molecular mechanisms, which may…

Biological Physics · Physics 2024-03-07 Ziqi Pi , Giovanni Zocchi

We develop a mesoscopic approach to model the non-equilibrium behavior of membranes at the cellular scale. Relying on lattice Boltzmann methods, we develop a solution procedure to recover the Nernst-Planck equations and Gauss's law. A…

Mesoscale and Nanoscale Physics · Physics 2023-02-22 James E. McClure , Zhe Li

We describe here a model for inelastic collisions for electronic excitation and deexcitation processes in a general, multifluid plasma. The model is derived from kinetic theory, and applicable to any mixture and mass ratio. The principle of…

Plasma Physics · Physics 2015-10-08 H. P. Le , J. -L. Cambier

Simulating the irreversible quantum dynamics of exciton and electron transfer problems poses a nontrivial challenge. Because the irreversibility of the system dynamics is a result of quantum thermal activation and dissipation caused by the…

Chemical Physics · Physics 2021-03-30 Seiji Ueno , Yoshitaka Tanimura

Neuronal excitability is the phenomena that describes action potential generation due to a stimulus input. Commonly, neuronal excitability is divided into two classes: Type I and Type II, both having different properties that affect…

Neurons and Cognition · Quantitative Biology 2020-11-03 Jantine A. C. Broek , Guillaume Drion

The ionization potential distributions of hydrated hydroxide and hydronium are computed with many-body approach for electron excitations with configurations generated by {\it ab initio} molecular dynamics. The experimental features are well…

Chemical Physics · Physics 2014-01-20 Charles W. Swartz , Xifan Wu

This work introduces a novel methodology for designing biologically plausible bursting neuron circuits using a minimal number of components. We hypothesize that to design circuits capable of bursting, the neuron circuit design must mimic a…

Hardware Architecture · Computer Science 2025-09-23 Amr Nabil , T. Nandha Kumar , Haider Abbas F. Almurib

We study the response of the Hodgkin-Huxley neuron stimulated periodically by biphasic rectangular current pulses. The optimal response for charge-balanced input is obtained for cathodic-first pulses with an inter-phase gap (IPG)…

Biological Physics · Physics 2013-05-20 L. S. Borkowski

A one-dimensional, dynamic, two-phase, isothermal model of proton exchange membrane fuel cell systems using a finite-difference approach has been developed. This model balances the simplicity of lumped-parameter models with the detailed…

Systems and Control · Electrical Eng. & Systems 2026-01-28 Raphaël Gass , Zhongliang Li , Rachid Outbib , Samir Jemei , Daniel Hissel

Neurons are the central biological objects in understanding how the brain works. The famous Hodgkin-Huxley model, which describes how action potentials of a neuron are initiated and propagated, consists of four coupled nonlinear…

Neurons and Cognition · Quantitative Biology 2010-02-01 William Hanan , Dhagash Mehta , Guillaume Moroz , Sepanda Pouryahya

This paper deals with the mathematical modelling of signal propagation in nerve fibres. Due to the complexity of the processes where electrical, mechanical, and thermal effects are coupled, a phenomenological approach helps to build…

Biological Physics · Physics 2026-04-07 Jüri Engelbrecht , Kert Tamm , Tanel Peets

The stochastic Hodgkin-Huxley neurons considered in this paper replace time-constant deterministic input $a dt$ of the classical deterministic model by increments $\vartheta dt + dX_t$ of a stochastic process: $X$ is Ornstein-Uhlenbeck with…

Probability · Mathematics 2023-06-22 Reinhard Höpfner
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