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We investigate the performance of sparsely-connected networks of integrate-and-fire neurons for ultra-short term information processing. We exploit the fact that the population activity of networks with balanced excitation and inhibition…

Neurons and Cognition · Quantitative Biology 2007-05-23 Julien Mayor , Wulfram Gerstner

Complex networks have certain properties that distinguish them from their respective uniform or regular counterparts. One of these properties is the variation of topological properties along different hierarchical levels. In this work, we…

Pattern Formation and Solitons · Physics 2023-06-19 Alexandre Benatti , Luciano da Fontoura Costa

Using a stochastic generalization of the Hodgkin–Huxley model, we consider the influence of intrinsic channel noise on the synchronization between the spiking activity of the excitable membrane and an externally applied periodic…

Biological Physics · Physics 2007-05-23 Gerhard Schmid , Igor Goychuk , Peter Hanggi

Synchronisation is a collective phenomenon widely investigated in classical oscillators and, more recently, in quantum systems. However, it remains unclear what features distinguish synchronous behaviour in these two scenarios. Recent works…

Quantum Physics · Physics 2019-07-19 Stefan Siwiak-Jaszek , Alexandra Olaya-Castro

Neurons and networks in the cerebral cortex must operate reliably despite multiple sources of noise. To evaluate the impact of both input and output noise, we determine the robustness of single-neuron stimulus selective responses, as well…

Neurons and Cognition · Quantitative Biology 2018-01-24 Ran Rubin , L. F. Abbott , Haim Sompolinsky

We investigate numerically the dynamics of large networks of $N$ globally pulse-coupled integrate and fire neurons in a noise-induced synchronized state. The powerspectrum of an individual element within the network is shown to exhibit in…

chao-dyn · Physics 2009-10-28 Wouter-Jan Rappel , Alain Karma

Neural dynamics of energy-based models are governed by energy minimization and the patterns stored in the network are retrieved when the system reaches equilibrium. However, when the system is driven by time-varying external input, the…

Neurons and Cognition · Quantitative Biology 2020-12-25 Kevin S. Chen

Nowadays, explosive synchronization is a well documented phenomenon occurring in networks when the node frequency and its degree are correlated. This first-order transition, which may coexists with classical synchronization, has been…

Physics and Society · Physics 2023-05-17 Manuel Miranda , Mattia Frasca , Ernesto Estrada

For many natural and engineered systems, a central function or design goal is the synchronization of one or more rhythmic or oscillating processes to an external forcing signal, which may be periodic on a different time-scale from the…

Dynamical Systems · Mathematics 2014-01-10 Anatoly Zlotnik , Jr-Shin Li

Balance of excitation and inhibition is a fundamental feature of in vivo network activity and is important for its computations. However, its presence in the neocortex of higher mammals is not well established. We investigated the dynamics…

One major challenge in neuroscience is the identification of interrelations between signals reflecting neural activity and how information processing occurs in the neural circuits. At the cellular and molecular level, mechanisms of signal…

Applications · Statistics 2019-09-27 Giacomo Aletti , Davide Lonardoni , Giovanni Naldi , Thierry Nieus

Synchronization is an important collective phenomenon in interacting oscillatory agents. Many functional features of the brain are related to synchronization of neurons. The type of synchronization transition that may occur (explosive vs.…

Disordered Systems and Neural Networks · Physics 2020-03-18 Mahsa Khoshkhou , Afshin Montakhab

This article investigates the emergence of phase synchronization in a network of randomly connected neurons by chemical synapses. The study uses the classic Hodgkin-Huxley model to simulate the neuronal dynamics under the action of a train…

Networks of coupled neural systems represent an important class of models in computational neuroscience. In some applications it is required that equilibrium points in these networks remain stable under parameter variations. Here we present…

Disordered Systems and Neural Networks · Physics 2007-05-23 Wilson A. Truccolo , Govindan Rangarajan , Yonghong Chen , Mingzhou Ding

We study explosive synchronization, a phenomenon characterized by first-order phase transitions between incoherent and synchronized states in networks of coupled oscillators. While explosive synchronization has been the subject of many…

Adaptation and Self-Organizing Systems · Physics 2014-08-22 Per Sebastian Skardal , Alex Arenas

The phenomenon of synchronization, where entities exhibit stable oscillations with aligned frequencies and phases, has been detected in diverse areas of natural science. It plays a crucial role in achieving frequency locking in multiple…

Quantum Physics · Physics 2025-06-24 Tong Liu , Laura García-Álvarez , Giovanna Tancredi

We study analytically the dynamics of a network of sparsely connected inhibitory integrate-and-fire neurons in a regime where individual neurons emit spikes irregularly and at a low rate. In the limit when the number of neurons N tends to…

Disordered Systems and Neural Networks · Physics 2007-05-23 N. Brunel , V. Hakim

We revisit the dynamics of a prototypical model of balanced activity in networks of spiking neutrons. A detailed investigation of the thermodynamic limit for fixed density of connections (massive coupling) shows that, when inhibition…

Adaptation and Self-Organizing Systems · Physics 2018-09-03 Ekkehard Ullner , Antonio Politi , Alessandro Torcini

We explore the dynamics of an integrate-and-fire neuron with an oscillatory stimulus. The frustration due to the competition between the neuron's natural firing period and that of the oscillatory rhythm, leads to a rich structure of…

Statistical Mechanics · Physics 2013-05-29 Jan R. Engelbrecht , Renato Mirollo

In the past few years, the discoveries of small-world and scale-free properties of many natural and artificial complex networks have stimulated significant advances in better understanding the relationship between the topology and the…

Disordered Systems and Neural Networks · Physics 2009-09-29 Xiang Li