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Biological neurons exhibit diverse temporal spike patterns, which are believed to support efficient, robust, and adaptive neural information processing. While models such as Izhikevich can replicate a wide range of these firing dynamics,…

Neural and Evolutionary Computing · Computer Science 2025-05-08 Ayana Moshruba , Hamed Poursiami , Maryam Parsa

Based on the analysis of probability flow, where the First Passage (FP) is realised as the sink of probability, we summarise the protocol to find the distribution of the First Passage Time (FTP). We also describe the corresponding formula…

Statistical Mechanics · Physics 2022-03-30 Ken Sekimoto

We are interested in understanding the neural correlates of attentional processes using first principles. Here we apply a recently developed first principles approach that uses transmitted information in bits per joule to quantify the…

Information Theory · Computer Science 2016-05-13 Siavash Ghavami , Vahid Rahmati , Farshad Lahouti , Lars Schwabe

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 study the response of a Hodgkin-Huxley neuron stimulated by a periodic sequence of conductance pulses arriving through the synapse in the high frequency regime. In addition to the usual excitation threshold there is a smooth crossover…

Biological Physics · Physics 2010-04-08 L. S. Borkowski

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…

Statistics Theory · Mathematics 2016-10-04 Pierre Hodara , Nathalie Krell , Eva Löcherbach

This article contains two main theoretical results on neural spike train models. The first assumes that the spike train is modeled as a counting or point process on the real line where the conditional intensity function is a product of a…

Statistics Theory · Mathematics 2007-06-13 Hock Peng Chan , Wei-Liem Loh

One model of real-life spreading processes is First Passage Percolation (also called SI model) on random graphs. Social interactions often follow bursty patterns, which are usually modelled with i.i.d.~heavy-tailed passage times on edges.…

Probability · Mathematics 2018-12-05 Alexey Medvedev , Gábor Pete

Repeating spatiotemporal spike patterns exist and carry information. Here we investigated how a single spiking neuron can optimally respond to one given pattern (localist coding), or to either one of several patterns (distributed coding,…

Neural and Evolutionary Computing · Computer Science 2018-09-24 Timothée Masquelier , Saeed Reza Kheradpisheh

Animal interval timing is often studied through the peak interval (PI) procedure. In this procedure, the animal is rewarded for the first response after a fixed delay from the stimulus onset, but on some trials, the stimulus remains and no…

Neurons and Cognition · Quantitative Biology 2022-04-05 Jason Zwicker , Francois Rivest

We consider a fractional counting process with jumps of amplitude $1,2,\ldots,k$, with $k\in \mathbb{N}$, whose probabilities satisfy a suitable system of fractional difference-differential equations. We obtain the moment generating…

Probability · Mathematics 2016-03-10 Antonio Di Crescenzo , Barbara Martinucci , Alessandra Meoli

Recent years have seen significant progress in developing spiking neural networks (SNNs) as a potential solution to the energy challenges posed by conventional artificial neural networks (ANNs). However, our theoretical understanding of…

Machine Learning · Computer Science 2025-06-16 Duc Anh Nguyen , Ernesto Araya , Adalbert Fono , Gitta Kutyniok

Two neurons coupled by unreliable synapses are modeled by leaky integrate-and-fire neurons and stochastic on-off synapses. The dynamics is mapped to an iterated function system. Numerical calculations yield a multifractal distribution of…

Disordered Systems and Neural Networks · Physics 2007-05-23 Johannes Kestler , Wolfgang Kinzel

Consider $\Xi$ a homogeneous Poisson point process on $\mathbb{R}^d$ ($d\geq 2$) with unit intensity with respect to the Lebesgue measure. For $\varepsilon\geq 0$, we define the Boolean model $\Sigma_{p, \varepsilon}$ as the union of the…

Probability · Mathematics 2025-02-11 Anne-Laure Basdevant , Jean-Baptiste Gouéré , Marie Théret

The first-passage time (FPT) is a fundamental concept in stochastic processes, representing the time it takes for a process to reach a specified threshold for the first time. Often, considering a time-dependent threshold is essential for…

Probability · Mathematics 2024-12-23 Devika Khurana , Sascha Desmettre , Evelyn Buckwar

We study the behavior of epidemic routing in a delay tolerant network as a function of node density. Focusing on the probability of successful delivery to a destination within a deadline (PS), we show that PS experiences a phase transition…

Networking and Internet Architecture · Computer Science 2020-02-13 Leila Rashidi , Don Towsley , Arman Mohseni-Kabir , Ali Movaghar

We examine the effects of stochastic input currents on the firing behavior of two excitable neurons coupled with fast excitatory synapses. In such cells (models), typified by the quadratic integrate and fire model, mutual synaptic coupling…

Neurons and Cognition · Quantitative Biology 2007-07-31 Boris S. Gutkin , Juergen Jost , Henry C. Tuckwell

The first passage time (FPT) for random walks is a key indicator of how fast information diffuses in a given system. Despite the role of FPT as a fundamental feature in transport phenomena, its behavior, particularly in heterogeneous…

Statistical Mechanics · Physics 2015-06-05 S. Hwang , D. -S. Lee , B. Kahng

Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron's probability of spiking. One popular method, known as maximally informative dimensions (MID), uses…

Neurons and Cognition · Quantitative Biology 2015-02-26 Ross S. Williamson , Maneesh Sahani , Jonathan W. Pillow

In biochemical reaction networks, the first passage time (FPT) of a reaction quantifies the time it takes for the reaction to first occur, from the initial state. While the mean FPT historically served as a summary metric, a far more…

Molecular Networks · Quantitative Biology 2025-03-07 Changqian Rao , David Waxman , Wei Lin , Zhuoyi Song
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