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相关论文: Onset of Phase Synchronization in Neurons Conneted…

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We present an approach which enables to state about the existence of phase synchronization in coupled chaotic oscillators without having to measure the phase. This is done by observing the oscillators at special times, and analyzing whether…

统计力学 · 物理学 2009-11-13 T. Pereira , M. S. Baptista , J. Kurths

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…

We characterize the synchronization of an array of coupled chaotic elements as a phase transition where order parameters related to the joint probability at two sites obey power laws versus the mutual coupling strength; the phase transition…

混沌动力学 · 物理学 2007-05-23 F. T. Arecchi , M. Ciszak

We consider synchronization of chaotic systems coupled indirectly through a common environmnet where the environment has an intrinsic dynmics of its own modulated via feedback from the systems. We find that a rich vareity of synchronization…

混沌动力学 · 物理学 2010-05-05 V. Resmi , G. Ambika , R. E. Amritkar

A great deal of research has been devoted on the investigation of neural dynamics in various network topologies. However, only a few studies have focused on the influence of autapses, synapses from a neuron onto itself via closed loops, on…

神经元与认知 · 定量生物学 2020-11-09 P. R. Protachevicz , K. C. Iarosz , I. L. Caldas , C. G. Antonopoulos , A. M. Batista , J. Kurths

Consistency and predictability of brain functionalities depend on reproducible activity of a single neuron. We identify a reproducible non-chaotic neuronal phase where deviations between concave response latency profiles of a single neuron…

神经元与认知 · 定量生物学 2014-05-27 Hagar Marmari , Roni Vardi , Ido Kanter

The onset of regular bursts in a group of irregularly bursting neurons with different individual properties is one of the most interesting dynamical properties found in neurobiological systems. In this paper we show how synchronization…

混沌动力学 · 物理学 2009-10-31 Nikolai F. Rulkov

We present an approach which enables to identify phase synchronization in coupled chaotic oscillators without having to explicitly measure the phase. We show that if one defines a typical event in one oscillator and then observes another…

统计力学 · 物理学 2009-11-13 T. Pereira , M. S. Baptista , J. Kurths

Depending on temperature the modified Hodgkin-Huxley (MHH) equations exhibit a variety of dynamical behavior including intrinsic chaotic firing. We analyze synchronization in a large ensemble of MHH neurons that are interconnected with gap…

混沌动力学 · 物理学 2009-11-11 Masahiko Yoshioka

Synchronization is studied in a spatially-distributed network of weekly-coupled, excitatory neurons of Hodgkin-Huxley type. All neurons are coupled to each other synaptically with a fixed time delay and a coupling strength inversely…

软凝聚态物质 · 物理学 2007-05-23 Yuqing Wang , Z. D. Wang , Y. -X. Li , X. Pei

We report experimental studies of synchronization phenomena in a pair of biological neurons that interact through naturally occurring, electrical coupling. When these neurons generate irregular bursts of spikes, the natural coupling…

Phase synchronization is shown to occur between opposite cells of a ring consisting of chaotic Lorenz oscillators coupled unidirectionally through driving. As the coupling strength is diminished, full phase synchronization cannot be…

chao-dyn · 物理学 2015-06-24 D. Pazo , I. P. Marino , V. Perez-Munuzuri , V. Perez-Villar

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…

适应与自组织系统 · 物理学 2014-08-22 Per Sebastian Skardal , Alex Arenas

We investigate the entrainment of a neuron model exhibiting a chaotic spiking-bursting behavior in response to a weak periodic force. This model exhibits two types of oscillations with different characteristic time scales, namely, long and…

混沌动力学 · 物理学 2015-06-05 Hiroyasu Ando , Hiromichi Suetani , Juergen Kurths , Kazuyuki Aihara

Large sparse circuits of spiking neurons exhibit a balanced state of highly irregular activity under a wide range of conditions. It occurs likewise in sparsely connected random networks that receive excitatory external inputs and recurrent…

神经元与认知 · 定量生物学 2013-08-16 Sven Jahnke , Raoul-Martin Memmesheimer , Marc Timme

Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons…

神经元与认知 · 定量生物学 2023-08-15 Marius E. Yamakou , Mathieu Desroches , Serafim Rodrigues

For a system of type-I neurons bidirectionally coupled through a nonlinear feedback mechanism, we discuss the issue of noise-induced complete synchronization (CS). For the inputs to the neurons, we point out that the rate of change of…

适应与自组织系统 · 物理学 2015-05-18 Nishant Malik , B. Ashok , J. Balakrishnan

The behavior of two unidirectionally coupled chaotic oscillators near the generalized synchronization onset has been considered. The character of the boundaries of the generalized synchronization regime has been explained by means of the…

混沌动力学 · 物理学 2007-05-23 A. E. Hramov , A. A. Koronovskii , O. I. Moskalenko

We show that the unavoidable increase in neuronal response latency to ongoing stimulation serves as a nonuniform gradual stretching of neuronal circuit delay loops and emerges as an essential mechanism in the formation of various types of…

神经元与认知 · 定量生物学 2012-12-07 Roni Vardi , Reut Timor , Shimon Marom , Moshe Abeles , Ido Kanter

We study the frequency and phase synchronization in two coupled identical and nonidentical neurons with channel noise. The occupation number method is used to model the neurons in the context of stochastic Hodgkin-Huxley model in which the…

神经元与认知 · 定量生物学 2007-11-07 L. C. Yu , Yong Chen , Pan Zhang
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