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The adaptive fitness of an organism in its ecological niche is highly reliant upon its ability to associate an environmental or internal stimulus with a behavior response through reinforcement. This simple but powerful observation has been…

Neurons and Cognition · Quantitative Biology 2023-12-01 Roy E. Clymer , Sanjeev V. Namjoshi

This paper focuses on the modeling of experiments conducted by Billock and Tsou [V. A. Billock and B. H. Tsou, Proc. Natl. Acad. Sci. USA, 104 (2007), pp. 8490--8495] using an Amari-type neural field that models the average membrane…

Neurons and Cognition · Quantitative Biology 2024-10-03 Cyprien Tamekue , Dario Prandi , Yacine Chitour

In this paper we study the following non-autonomous stochastic evolution equation on a UMD Banach space $E$ with type 2, {equation}\label{eq:SEab}\tag{SE} {{aligned} dU(t) & = (A(t)U(t) + F(t,U(t))) dt + B(t,U(t)) dW_H(t), \quad t\in [0,T],…

Probability · Mathematics 2009-09-14 Mark Veraar

In this paper we study the asymptotic behaviour of a nonlocal nonlinear parabolic equation governed by a parameter. After giving the existence of unique branch of solutions composed by stable solutions in stationary case, we gives for the…

Analysis of PDEs · Mathematics 2010-03-23 Armel Andami Ovono

Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and…

Neural and Evolutionary Computing · Computer Science 2015-06-18 Massimiliano Giulioni , Federico Corradi , Vittorio Dante , Paolo del Giudice

We study the asymptotics of strongly continuous operator semigroups defined on locally convex spaces in order to develop a stability theory for solutions of evolution equations beyond Banach spaces. In the classical case, there is only…

Analysis of PDEs · Mathematics 2016-03-03 Birgit Jacob , Sven-Ake Wegner

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

We describe a mechanism for biological learning and adaptation based on two simple principles: (I) Neuronal activity propagates only through the network's strongest synaptic connections (extremal dynamics), and (II) The strengths of active…

Disordered Systems and Neural Networks · Physics 2009-10-31 Per Bak , Dante R Chialvo

We consider an individual based model of phenotypic evolution in hermaphroditic populations which includes random and assortative mating of individuals. By increasing the number of individuals to infinity we obtain a nonlinear transport…

Probability · Mathematics 2013-09-13 Ryszard Rudnicki , Paweł Zwoleński

A massively recurrent neural network responds on one side to input stimuli and is autonomously active, on the other side, in the absence of sensory inputs. Stimuli and information processing depends crucially on the qualia of the…

Disordered Systems and Neural Networks · Physics 2012-02-01 Dimitrije Markovic , Claudius Gros

This paper explores a non-linear, non-local model describing the evolution of a single species. We investigate scenarios where the spatial domain is either an arbitrary bounded and open subset of the $n$-dimensional Euclidean space or a…

Analysis of PDEs · Mathematics 2024-03-19 Maciej Tadej

We consider a system of several nonlinear equations with a distributed delay and obtain absolute asymptotic stability conditions, independent of the delay. The ideas of the proofs are based on the notion of a strong attractor. The results…

Dynamical Systems · Mathematics 2021-05-26 Leonid Berezansky , Elena Braverman

Neural dynamical systems with stable attractor structures, such as point attractors and continuous attractors, are hypothesized to underlie meaningful temporal behavior that requires working memory. However, working memory may not support…

Neurons and Cognition · Quantitative Biology 2023-08-25 Il Memming Park , Ábel Ságodi , Piotr Aleksander Sokół

We study the asymptotic behavior as $t \to \infty$ of a time-dependent family $(\mu_t)_{t \geq 0}$ of probability measures on $\mathbb{R}$ solving the kinetic-type evolution equation $\partial_t \mu_t + \mu_t = Q(\mu_t)$ where $Q$ is a…

Probability · Mathematics 2020-07-21 Dariusz Buraczewski , Konrad Kolesko , Matthias Meiners

We consider nonautonomous semilinear evolution equations of the form \label{semilineq} \frac{dx}{dt}= A(t)x+f(t,x). Here $A(t)$ is a (possibly unbounded) linear operator acting on a real or complex Banach space $\X$ and $f: \R\times\X\to\X$…

Classical Analysis and ODEs · Mathematics 2012-11-22 Nguyen Van Minh , Gaston M. N'guérékata , Ciprian Preda

This paper studies the dynamics of families of monotone nonautonomous neutral functional differential equations with nonautonomous operator, of great importance for their applications to the study of the long-term behavior of the…

Dynamical Systems · Mathematics 2020-04-06 Sylvia Novo , Rafael Obaya , Victor M. Villarragut

Single trial analyses of ensemble activity in alert animals demonstrate that cortical circuits dynamics evolve through temporal sequences of metastable states. Metastability has been studied for its potential role in sensory coding, memory…

Neurons and Cognition · Quantitative Biology 2016-03-23 Luca Mazzucato , Alfredo Fontanini , Giancarlo La Camera

The paper studies the asymptotic behaviour of weighted functionals of long-range dependent data over increasing observation windows. Various important statistics, including sample means, high order moments, occupation measures can be given…

Statistics Theory · Mathematics 2019-05-27 Tareq Alodat , Andriy Olenko

In this work we define the generalized $\varphi$-pullback attractors for evolution processes in complete metric spaces, which are compact and positively invariant families, such that they pullback attract bounded sets with a rate determined…

Dynamical Systems · Mathematics 2023-11-28 Matheus C. Bortolan , Tomas Caraballo , Carlos Pecorari Neto

Biological nervous systems consist of networks of diverse, sophisticated information processors in the form of neurons of different classes. In most artificial neural networks (ANNs), neural computation is abstracted to an activation…

Neural and Evolutionary Computing · Computer Science 2023-06-12 Joachim Winther Pedersen , Sebastian Risi