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相关论文: Heterogeneity-Induced Inhibitory Coherence in An E…

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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

High-level brain function such as memory, classification or reasoning can be realized by means of recurrent networks of simplified model neurons. Analog neuromorphic hardware constitutes a fast and energy efficient substrate for the…

神经元与认知 · 定量生物学 2016-06-10 Thomas Pfeil , Jakob Jordan , Tom Tetzlaff , Andreas Grübl , Johannes Schemmel , Markus Diesmann , Karlheinz Meier

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

The impact of inhibitory and excitatory synapses in delay-coupled Hodgkin--Huxley neurons that are driven by noise is studied. If both synaptic types are used for coupling, appropriately tuned delays in the inhibition feedback induce…

神经元与认知 · 定量生物学 2012-05-01 Qingyun Wang , Honghui Zhang , Matjaz Perc , Guanrong Chen

The brain is characterized by a strong heterogeneity of inhibitory neurons. We report that spiking neural networks display a resonance to the heterogeneity of inhibitory neurons, with optimal input/output responsiveness occurring for levels…

神经元与认知 · 定量生物学 2021-09-30 Matteo di Volo , Alain Destexhe

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

The brain is composed of complex networks of interacting neurons that express considerable heterogeneity in their physiology and spiking characteristics. How does neural heterogeneity affect macroscopic neural dynamics and how does it…

神经元与认知 · 定量生物学 2022-06-20 Richard Gast , Sara A. Solla , Ann Kennedy

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…

无序系统与神经网络 · 物理学 2007-05-23 N. Brunel , V. Hakim

Neuronal heterogeneity, characterized by the presence of a multitude of spiking neuronal patterns, is a widespread phenomenon throughout the nervous system. In particular, the brain exhibits strong variability among inhibitory neurons.…

神经元与认知 · 定量生物学 2024-12-02 Katiele V. P. Brito , Joana M. G. L. Silva , Claudio R. Mirasso , Fernanda S. Matias

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

This article is devoted to the theoretical and numerical analysis of a network of excitatory and inhibitory neurons of Hodgkin-Huxley (HH) type, for which the topology is inspired by that of a single local layer of visual cortex V1. Our…

神经元与认知 · 定量生物学 2021-08-13 M. Maama , B. Ambrosio , M. A. Aziz-Alaoui , S. M. Mintchev

Recent advancements in measurement techniques have resulted in an increasing amount of data on neural activities recorded in parallel, revealing largely heterogeneous correlation patterns across neurons. Yet, the mechanistic origin of this…

无序系统与神经网络 · 物理学 2024-04-26 Moritz Layer , Moritz Helias , David Dahmen

The counter-intuitive phenomenon of coherence resonance describes a non-monotonic behavior of the regularity of noise-induced oscillations in the excitable regime, leading to an optimal response in terms of regularity of the excited…

适应与自组织系统 · 物理学 2021-03-24 Emre Baspinar , Leonhard Schülen , Simona Olmi , Anna Zakharova

We study some mechanisms responsible for synchronous oscillations and loss of synchrony at physiologically relevant frequencies (10-200 Hz) in a network of heterogeneous inhibitory neurons. We focus on the factors that determine the level…

神经元与认知 · 定量生物学 2007-05-23 J. A. White , C. C. Chow , J. Ritt , C. Soto-Trevino , N. Kopell

By varying the noise intensity, we study stochastic spiking coherence (i.e., collective coherence between noise-induced neural spikings) in an inhibitory population of subthreshold neurons (which cannot fire spontaneously without noise).…

生物物理 · 物理学 2011-11-01 Woochang Lim , Sang-Yoon Kim

Recurrent networks of dynamic elements frequently exhibit emergent collective oscillations, which can display substantial regularity even when the individual elements are considerably noisy. How noise-induced dynamics at the local level…

适应与自组织系统 · 物理学 2017-01-04 Belen Sancristobal , Beatriz Rebollo , Pol Boada , Maria V. Sanchez-Vives , Jordi Garcia-Ojalvo

Recent experiments suggest that inhibitory networks of interneurons can synchronize the neuronal discharge in in vitro hippocampal slices. Subsequent theoretical work has shown that strong synchronization by mutual inhibition is only…

统计力学 · 物理学 2007-05-23 P. H. E Tiesinga , Jorge V Jose

Noise can induce time order in the dynamics of nonlinear dynamical systems. For example, coherence resonance occurs in various neuron models driven by a noise. In studies of coherence resonance, ensemble-averaged measures of the coherence…

适应与自组织系统 · 物理学 2023-10-05 Go Uchida

Inhibitory neurons play a crucial role in maintaining persistent neuronal activity. Although connected extensively through electrical synapses (gap-junctions), these neurons also exhibit interactions through chemical synapses in certain…

神经元与认知 · 定量生物学 2021-04-08 R. Janaki , A. S. Vytheeswaran

The output signal is examined for the Jacobi neuronal model which is characterized by input-dependent multiplicative noise. The dependence of the noise on the rate of inhibition turns out to be of primary importance to observe maxima both…

神经元与认知 · 定量生物学 2019-09-04 Giuseppe D'Onofrio , Petr Lansky , Massimiliano Tamborrino
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