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相关论文: Multiple firing coherence resonances in excitatory…

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We analyze the response of the Hodgkin-Huxley neuron to a large number of uncorrelated stochastic inhibitory and excitatory post-synaptic spike trains. In order to clarify the various mechanisms responsible for noise-induced spike…

无序系统与神经网络 · 物理学 2007-05-23 Alessandro Torcini , Stefano Luccioli , Thomas Kreuz

We study the noise activated dynamics of a model {\it autapse} neuron system that consists of a subcritical Hopf oscillator with a time delayed nonlinear feedback. The coherence of the noise driven pulses of the neuron exhibits a novel…

混沌动力学 · 物理学 2009-11-11 Gautam C Sethia , Juergen Kurths , Abhijit Sen

We numerically investigate the influence of intrinsic channel noise on the dynamical response of delay-coupling in neuronal systems. The stochastic dynamics of the spiking is modeled within a stochastic modification of the standard…

生物物理 · 物理学 2013-09-23 Xue Ao , Peter Hanggi , Gerhard Schmid

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

Numerical calculations have been made on the spike-train response of a pair of Hodgkin-Huxley (HH) neurons coupled by synapses and axons with time delay. The recurrent excitatory-excitatory, inhibitory-inhibitory, excitatory-inhibitory, and…

无序系统与神经网络 · 物理学 2007-05-23 Hideo Hasegawa

Model calculations have been performed on the spike-train response of a pair of Hodgkin-Huxley (HH) neurons coupled by recurrent excitatory-excitatory couplings with time delay. The coupled, excitable HH neurons are assumed to receive the…

无序系统与神经网络 · 物理学 2009-10-31 Hideo Hasegawa

The effect of intrinsic channel noise is investigated for the dynamic response of a neuronal cell with a delayed feedback loop. The loop is based on the so-called autapse phenomenon in which dendrites establish not only connections to…

生物物理 · 物理学 2014-12-22 Yunyun Li , Gerhard Schmid , Peter Hanggi , Lutz Schimansky-Geier

The coherence resonance (CR) of globally coupled Hodgkin-Huxley neurons is studied. When the neurons are set in the subthreshold regime near the firing threshold, the additive noise induces limit cycles. The coherence of the system is…

生物物理 · 物理学 2009-10-31 Yuqing Wang , David T. W. Chik , Z. D. Wang

Networks of fast-spiking interneurons are crucial for the generation of neural oscillations in the brain. Here we study the synchronous behavior of interneuronal networks that are coupled by delayed inhibitory and fast electrical synapses.…

神经元与认知 · 定量生物学 2012-06-22 Daqing Guo , Qingyun Wang , Matjaz Perc

We study the time delay in the synaptic conductance for suppression of spike synchronisation in a random network of Hodgkin Huxley neurons coupled by means of chemical synapses. In the first part, we examine in detail how the time delay…

The response of the Hodgkin-Huxley neuronal model subjected to stochastic uncorrelated spike trains originating from a large number of inhibitory and excitatory post-synaptic potentials is analyzed in detail. The model is examined in its…

无序系统与神经网络 · 物理学 2007-05-23 Stefano Luccioli , Thomas Kreuz , Alessandro Torcini

Recordings from area V4 of monkeys have revealed that when the focus of attention is on a visual stimulus within the receptive field of a cortical neuron, two distinct changes can occur: The firing rate of the neuron can change and there…

神经元与认知 · 定量生物学 2007-05-23 Paul H. E. Tiesinga , Jean-Marc Fellous , Emilio Salinas , Jorge V. Jose , Terrence J. Sejnowski

We study the influence of correlations among discrete stochastic excitatory or inhibitory inputs on the response of the FitzHugh-Nagumo neuron model. For any level of correlation the emitted signal exhibits at some finite noise intensity a…

无序系统与神经网络 · 物理学 2007-05-23 Thomas Kreuz , Stefano Luccioli , Alessandro Torcini

We study synaptically coupled neuronal networks to identify the role of coupling delays in network's synchronized behaviors. We consider a network of excitable, relaxation oscillator neurons where two distinct populations, one excitatory…

神经元与认知 · 定量生物学 2018-01-01 Hwayeon Ryu , Sue Ann Campbell

Time--delayed feedback is exploited for controlling noise--induced motion in coherence resonance oscillators. Namely, under the proper choice of time delay, one can either increase or decrease the regularity of motion. It is shown that in…

统计力学 · 物理学 2009-11-10 N. B. Janson , A. G. Balanov , E. Schoell

Neurons are connected to other neurons by axons and dendrites that conduct signals with finite velocities, resulting in delays between the firing of a neuron and the arrival of the resultant impulse at other neurons. Since delays greatly…

神经元与认知 · 定量生物学 2021-08-25 Akke Mats Houben

We demonstrate the existence of noise-induced periodicity (coherence resonance) in both a discrete-time model and a continuous-time model of an excitable neuron. In particular, we show that the effects of noise added to the fast and slow…

神经元与认知 · 定量生物学 2009-11-10 Robert C. Hilborn , Rebecca J. Erwin

The influence of time delay in systems of two coupled excitable neurons is studied in the framework of the FitzHugh-Nagumo model. Time-delay can occur in the coupling between neurons or in a self-feedback loop. The stochastic…

斑图形成与孤子 · 物理学 2009-11-13 E. Schoell , G. Hiller , P. Hoevel , M. A. Dahlem

We study a network model of two conductance-based pacemaker neurons of differing natural frequency, coupled with either mutual excitation or inhibition, and receiving shared random inhibitory synaptic input. The networks may phase-lock…

神经元与认知 · 定量生物学 2009-11-13 Ramana Dodla , Charles J. Wilson

We study the synchronisation of neurons in a realistic model under the Hodgkin-Huxley dynamics. To focus on the role of the different locations of the excitatory synapses, we use two identical neurons where the set of input signals is…

神经元与认知 · 定量生物学 2024-09-17 Alessandro Fiasconaro , Michele Migliore
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