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The relative timing of action potentials in neurons recorded from local cortical networks often shows a non-trivial dependence, which is then quantified by cross-correlation functions. Theoretical models emphasize that such spike train…

Neurons and Cognition · Quantitative Biology 2017-06-28 Taskin Deniz , Stefan Rotter

The leaky integrate and fire (LIF) neuron represents standard neuronal model used for numerical simulations. The leakage is implemented in the model as exponential decay of trans-membrane voltage towards its resting value. This makes…

Neurons and Cognition · Quantitative Biology 2015-05-26 A. K. Vidybida

Neurons in the brain continuously process the barrage of sensory inputs they receive from the environment. A wide array of experimental work has shown that the collective activity of neural populations encodes and processes this constant…

Neurons and Cognition · Quantitative Biology 2025-10-30 Siddharth Paliwal , Gabriel Koch Ocker , Braden A. W. Brinkman

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,…

Analysis of PDEs · Mathematics 2020-11-11 Grégory Dumont , Pierre Gabriel

The construction of transfer functions in theoretical neuroscience plays an important role in determining the spiking rate behavior of neurons in networks. These functions can be obtained through various fitting methods, but the biological…

Neurons and Cognition · Quantitative Biology 2023-05-25 Marcelo P. Becker , Marco A. P. Idiart

In this paper, we propose a shot noise-based leaky integrated and firing neuron model and provide a detailed analysis of the performance of this model compared to the traditional diffusion approximated model. In theoretical neuroscience,…

Neurons and Cognition · Quantitative Biology 2018-07-05 Zihao Xu

An inverse procedure is proposed and tested which aims at recovering the a priori unknown functional and structural information from global signals of living brains activity. To this end we consider a Leaky-Integrate and Fire (LIF) model…

One of the most important challenges in mathematical neuroscience is to properly illustrate the stochastic nature of neurons. Among different approaches, the noisy leaky integrate-and-fire and the escape rate models are probably the most…

Analysis of PDEs · Mathematics 2017-02-07 Grégory Dumont , Jacques Henry , Carmen Oana Tarniceriu

We consider a single Leaky integrate-and-fire neuron stimulated with Poisson process. We develop a method, which allows one to obtain the first passage time probability density function without any additional approximations.

Neurons and Cognition · Quantitative Biology 2016-07-25 K. Kravchuk

Stochastic integrate-and-fire (IF) neuron models have found widespread applications in computational neuroscience. Here we present results on the white-noise-driven perfect, leaky, and quadratic IF models, focusing on the spectral…

Neurons and Cognition · Quantitative Biology 2015-05-14 Rafael D. Vilela , Benjamin Lindner

In a generic neuron model, we present the linear response theory for the firing rate in response to both time dependent input currents and noise amplitudes. In both cases the signal transmission is strongly attenuated for frequencies above…

Biological Physics · Physics 2007-05-23 Bjoern Naundorf , Theo Geisel , Fred Wolf

We compute the firing rate of a leaky integrate-and-fire (LIF) neuron with stochastic conductance-based inputs in the limit when synaptic decay times are much shorter than the membrane time constant. A comparison of our analytical results…

Neurons and Cognition · Quantitative Biology 2020-02-27 Timothy D. Oleskiw , Wyeth Bair , Eric Shea-Brown , Nicolas Brunel

One of the fundamental characteristics of a nonlinear system is how it transfers correlations in its inputs to correlations in its outputs. This is particularly important in the nervous system, where correlations between spiking neurons are…

Neurons and Cognition · Quantitative Biology 2013-05-29 Eric Shea-Brown , Kresimir Josic , Jaime de la Rocha , Brent Doiron

Spiking Neural Networks (SNNs) are being explored to emulate the astounding capabilities of human brain that can learn and compute functions robustly and efficiently with noisy spiking activities. A variety of spiking neuron models have…

Neural and Evolutionary Computing · Computer Science 2020-06-17 Sayeed Shafayet Chowdhury , Chankyu Lee , Kaushik Roy

The study presents a numerical model of leaky integrate-and-fire neuron created on the basis of $VO_2$ switch. The analogue of the membrane potential in the model is the temperature of the switch channel, and the action potential from…

Emerging Technologies · Computer Science 2020-01-07 A. A. Velichko , M. A. Belyaev , D. V. Ryabokon , S. D. Khanin

An analytical description of the response properties of simple but realistic neuron models in the presence of noise is still lacking. We determine completely up to the second order the firing statistics of a single and a pair of leaky…

Neurons and Cognition · Quantitative Biology 2009-11-13 Ruben Moreno-Bote , Nestor Parga

We use mean field theory to study the response properties of a simple randomly-connected model cortical network of leaky integrate-and-fire neurons with balanced excitation and inhibition. The formulation permits arbitrary temporal…

Disordered Systems and Neural Networks · Physics 2007-05-23 John Hertz , Barry Richmond , Kristian Nilsen

The first-passage-time distribution of a leaky integrate-and-fire neuron driven by a characteristically coloured noise is approximated by matching a transient and a steady-state solution of the membrane voltage distribution. These…

Neurons and Cognition · Quantitative Biology 2021-02-04 Akke Mats Houben

The response properties of excitable systems driven by colored noise are of great interest, but are usually mathematically only accessible via approximations. For this reason, dichotomous noise, a rare example of a colored noise leading…

Biological Physics · Physics 2017-02-01 Felix Droste , Benjamin Lindner

We report about the main dynamical features of a model of leaky-integrate-and fire excitatory neurons with short term plasticity defined on random massive networks. We investigate the dynamics by a Heterogeneous Mean-Field formulation of…

Disordered Systems and Neural Networks · Physics 2015-06-22 Matteo di Volo , Raffaella Burioni , Mario Casartelli , Roberto Livi , Alessandro Vezzani
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