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The dynamics of two coupled piece-wise linear one-dimensional monostable maps is investigated. The single map is associated with Poincare section of the FitzHugh-Nagumo neuron model. It is found that a diffusive coupling leads to the…

混沌动力学 · 物理学 2009-11-10 M. Courbage , V. Kazentsev , V. I. Nekorkin , M. Senneret

Pulse-coupled systems such as spiking neural networks exhibit nontrivial invariant sets in the form of attracting yet unstable saddle periodic orbits where units are synchronized into groups. Heteroclinic connections between such orbits may…

适应与自组织系统 · 物理学 2020-11-03 Fabio Schittler Neves , Marc Timme

Triggering a single additional spike in a cerebral cortical neuron was recently demonstrated to cause a cascade of extra spikes in the network that is likely to rapidly decorrelate the network's microstate. The mechanisms involved in this…

神经元与认知 · 定量生物学 2011-03-01 Michael Monteforte , Fred Wolf

Directed transport is a characteristic feature of numerous biological systems in response to signals such as nutrient and chemical gradients. These signals often depend on time owing to the high complexity of interactions in these systems.…

软凝聚态物质 · 物理学 2026-03-04 Bhavesh Valecha , Jens-Uwe Sommer , Abhinav Sharma

We examine the large-network, low-loading behaviour of an attractor neural network, the so-called bistable gradient network (BGN). We use analytical and numerical methods to characterize the attractor states of the network and their basins…

无序系统与神经网络 · 物理学 2007-05-23 Patrick N. McGraw , Michael Menzinger

We study a network of spiking neurons with heterogeneous excitabilities connected via inhibitory delayed pulses. For globally coupled systems the increase of the inhibitory coupling reduces the number of firing neurons by following a Winner…

无序系统与神经网络 · 物理学 2019-05-29 Stefano Luccioli , David Angulo Garcia , Alessandro Torcini

Recurrent networks of non-linear units display a variety of dynamical regimes depending on the structure of their synaptic connectivity. A particularly remarkable phenomenon is the appearance of strongly fluctuating, chaotic activity in…

神经元与认知 · 定量生物学 2017-05-10 Francesca Mastrogiuseppe , Srdjan Ostojic

Finite-sized populations of spiking elements are fundamental to brain function, but also used in many areas of physics. Here we present a theory of the dynamics of finite-sized populations of spiking units, based on a quasi-renewal…

神经元与认知 · 定量生物学 2015-03-04 Moritz Deger , Tilo Schwalger , Richard Naud , Wulfram Gerstner

The present paper provides exact mathematical expressions for the high-order moments of spiking activity in a recurrently-connected network of linear Hawkes processes. It extends previous studies that have explored the case of a (linear)…

神经元与认知 · 定量生物学 2019-12-17 Matthieu Gilson , Jean-Pascal Pfister

We analyze the effects of spatiotemporal noise on stationary pulse solutions (bumps) in neural field equations on planar domains. Neural fields are integrodifferential equations whose integral kernel describes the strength and polarity of…

斑图形成与孤子 · 物理学 2015-04-21 Daniel Poll , Zachary P. Kilpatrick

Inhibitory interneurons, ubiquitous in the central nervous system, form networks connected through both chemical synapses and gap junctions. These networks are essential for regulating the activity of principal neurons, especially by…

神经元与认知 · 定量生物学 2025-05-09 Hélène Todd , Mathieu Desroches , Alex Cayco-Gajic , Boris Gutkin

The destruction of a chaotic attractor leading to rough changes in the dynamics of a dynamical system is studied. Local bifurcations are characterised by a single or a pair of characteristic exponents crossing the imaginary axis. The…

混沌动力学 · 物理学 2020-11-16 Alexis Tantet , Valerio Lucarini , Frank Lunkeit , Henk A. Dijkstra

Neuronal networks can generate burst events. It remains unclear how to analyse interburst periods and their statistics. We study here the phase-space of a mean-field model, based on synaptic short-term changes, that exhibit burst and…

统计力学 · 物理学 2020-12-17 Lou Zonca , David Holcman

Efficient path planning and navigation is critical for animals, robotics, logistics and transportation. We study a model in which spatial navigation problems can rapidly be solved in the brain by parallel mental exploration of alternative…

神经元与认知 · 定量生物学 2012-05-03 Filip Ponulak , John J. Hopfield

In the past decade, the cell-type specific connectivity and activity of local cortical networks have been characterized experimentally to some detail. In parallel, modeling has been established as a tool to relate network structure to…

神经元与认知 · 定量生物学 2011-06-29 Tobias C. Potjans , Markus Diesmann

In this paper, we report on the generation and propagation of traveling pulses in a homogeneous network of diffusively coupled, excitable, slow-fast dynamical neurons. The spatially extended system is modelled using the nearest neighbor…

Various classes of neurons alternate between high-frequency discharges and silent intervals. This phenomenon is called burst firing. To analyze burst activity in an insect system, grasshopper auditory receptor neurons were recorded in vivo…

神经元与认知 · 定量生物学 2008-07-17 Hugo G. Eyherabide , Ariel Rokem , Andreas V. M. Herz , Ines Samengo

Laminar-turbulent pattern formation is a distinctive feature of the intermittency regime in subcritical plane shear flows. By performing extensive numerical simulations of the plane channel flow, we show that the pattern emerges from a…

流体动力学 · 物理学 2022-12-16 Pavan V. Kashyap , Yohann Duguet , Olivier Dauchot

Biological information processing is often carried out by complex networks of interconnected dynamical units. A basic question about such networks is that of reliability: if the same signal is presented many times with the network in…

混沌动力学 · 物理学 2015-06-11 Guillaume Lajoie , Kevin K. Lin , Eric Shea-Brown

We study a pulse-coupled dynamics of excitable elements in uncorrelated scale-free networks. Regimes of self-sustained activity are found for homogeneous and inhomogeneous couplings, in which the system displays a wide variety of behaviors,…

神经元与认知 · 定量生物学 2017-03-10 P. Piedrahita , J. J. Mazo , L. M. Floría , Y. Moreno