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Synchronous oscillatory dynamics is frequently observed in the human brain. We analyze the fine temporal structure of phase-locking in a realistic network model and match it with the experimental data from parkinsonian patients. We show…

神经元与认知 · 定量生物学 2011-04-18 Choongseok Park , Robert M. Worth , Leonid L. Rubchinsky

Neural activity in the brain of parkinsonian patients is characterized by the intermittently synchronized oscillatory dynamics. This imperfect synchronization, observed in the beta frequency band, is believed to be related to the…

神经元与认知 · 定量生物学 2013-02-11 Choongseok Park , Leonid Rubchinsky

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

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…

A network of propagating nonlinear oscillatory modes (waves) in the human brain is shown to generate collectively synchronized spiking activity (hypersynchronous spiking) when both amplitude and phase coupling between modes are taken into…

生物物理 · 物理学 2021-04-28 Vitaly L. Galinsky , Lawrence R. Frank

We study the statistical physics of a surprising phenomenon arising in large networks of excitable elements in response to noise: while at low noise, solutions remain in the vicinity of the resting state and large-noise solutions show…

适应与自组织系统 · 物理学 2020-04-01 Jonathan D. Touboul , Charlotte Piette , Laurent Venance , G. Bard Ermentrout

Spontaneous cortical population activity exhibits a multitude of oscillatory patterns, which often display synchrony during slow-wave sleep or under certain anesthetics and stay asynchronous during quiet wakefulness. The mechanisms behind…

神经元与认知 · 定量生物学 2018-06-20 Rodrigo F. O. Pena , Michael A. Zaks , Antonio C. Roque

Suppression of excessively synchronous beta-band oscillatory activity in the brain is believed to suppress hypokinetic motor symptoms of Parkinson's disease. Recently, a lot of interest has been devoted to desynchronizing delayed feedback…

神经元与认知 · 定量生物学 2013-03-05 Andrey Dovzhenok , Choongseok Park , Robert M. Worth , Leonid L. Rubchinsky

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

We report on the origin of synchronized bursting dynamics in various networks of neural spiking oscillators, when a certain threshold in coupling strength is exceeded. These ensembles synchronize at relatively low coupling strength and lose…

混沌动力学 · 物理学 2007-05-23 Mikhail V. Ivanchenko , Grigory V. Osipov , Vladimir D. Shalfeev , Jurgen Kurths

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

The study of balanced networks of excitatory and inhibitory neurons has led to several open questions. On the one hand it is yet unclear whether the asynchronous state observed in the brain is autonomously generated, or if it results from…

神经元与认知 · 定量生物学 2016-09-22 Rodrigo Echeveste , Claudius Gros

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

In the brain, coherent neuronal activities often appear simultaneously in multiple frequency bands, e.g., as combinations of alpha (8-12 Hz), beta (12.5-30 Hz), gamma (30-120 Hz) oscillations, among others. These rhythms are believed to…

神经元与认知 · 定量生物学 2023-04-26 Tianyi Wu , Yuhang Cai , Ruilin Zhang , Zhongyi Wang , Louis Tao , Zhuo-Cheng Xiao

We observe and study a self-organized phenomenon whereby the activity in a network of spiking neurons spontaneously terminates. We consider different types of populations, consisting of bistable model neurons connected electrically by gap…

无序系统与神经网络 · 物理学 2018-11-22 Muhammet Uzuntarla , Joaquin J. Torres , Ali Çalım , Ernest Barreto

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…

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

The activity of neurons is correlated, and this correlation affects how the brain processes information. We study the neural circuit mechanisms of correlations by analyzing a network model characterized by strong and heterogeneous…

神经元与认知 · 定量生物学 2012-12-03 Alberto Bernacchia , Xiao-Jing Wang
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