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In this report trial-to-trial variations in the synchronized responses of neural networks are offered as evidence for excitation-inhibition ratio being a dynamic variable over time scales of minutes. Synchronized network responses to…

神经元与认知 · 定量生物学 2015-01-05 Netta Haroush , Shimon Marom

Neural network models comprising elements which have exclusively excitatory or inhibitory synapses are capable of a wide range of dynamic behavior, including chaos. In this paper, a simple excitatory-inhibitory neural pair, which forms the…

无序系统与神经网络 · 物理学 2009-10-31 Sitabhra Sinha , Jayanta Basak

We investigate the synchronization properties between two excitatory coupled neurons in the presence of an inhibitory loop mediated by an interneuron. Dynamical inhibition together with noise independently applied to each neuron provide…

神经元与认知 · 定量生物学 2016-11-23 Fernanda S. Matias , Leonardo L. Gollo , Pedro V. Carelli , Claudio R. Mirasso , Mauro Copelli

In this work, we study the dynamic range of a neuronal network of excitable neurons with excitatory and inhibitory synapses. We obtain an analytical expression for the critical point as a function of the excitatory and inhibitory synaptic…

神经元与认知 · 定量生物学 2020-08-24 F S Borges , P R Protachevicz , V Santos , M S Santos , E C Gabrick , K C Iarosz , E L Lameu , M S Baptista , I L Caldas , A M Batista

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

In this paper, we investigated the neural spikes synchronisation in a neural network with synaptic plasticity and external perturbation. In the simulations the neural dynamics is described by the Hodgkin Huxley model considering chemical…

We consider a clustered network with small-world sub-networks of inhibitory fast spiking interneurons, and investigate the effect of inter-modular connection on emergence of fast sparsely synchronized rhythms by varying both the…

神经元与认知 · 定量生物学 2015-12-02 Sang-Yoon Kim , Woochang Lim

In this work we study the synchronization of Kuramoto oscillators driven by external forces in complex modular networks. The motivation is the neuronal dynamics that takes place during information processing in the neural cortex. The neuron…

适应与自组织系统 · 物理学 2020-04-02 Carolina Arruda Moreira

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

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

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

Many experiments have evidenced that electrical and chemical synapses -- hybrid synapses -- coexist in most organisms and brain structures. The role of electrical and chemical synapse connection in diversity of neural activity generation…

神经元与认知 · 定量生物学 2021-08-11 Kesheng Xu , Jean Paul Maidana , Patricio Orio

We consider clustered small-world networks with both inhibitory (I) and excitatory (E) populations. This I-E neuronal network has adaptive dynamic I to E and E to I interpopulation synaptic strengths, governed by interpopulation…

神经元与认知 · 定量生物学 2020-02-12 Sang-Yoon Kim , Woochang Lim

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

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

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

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

Fast cortical rhythms with stochastic and intermittent neural discharges have been observed in electric recordings of brain activity. Recently, Brunel et al. developed a framework to describe this kind of fast sparse synchronization in both…

神经元与认知 · 定量生物学 2014-09-03 Sang-Yoon Kim , Woochang Lim

We consider the Watts-Strogatz small-world network consisting of subthreshold neurons which exhibit noise-induced spikings. This neuronal network has adaptive dynamic synaptic strengths governed by the spike-timing-dependent plasticity…

神经元与认知 · 定量生物学 2017-08-16 Sang-Yoon Kim , Woochang Lim

The dynamical responses of complex neuronal networks to external stimulus injected on a \emph{single} neuron are investigated. Stimulating the largest-degree neuron in the network, it is found that as the intensity of the stimulus…

混沌动力学 · 物理学 2016-04-13 Mengjiao Chen , Weijie Lin , Hengtong Wang , Wei Ren , Xingang Wang
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