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Although recent neurophysiological experiments suggest that synchronous neural activity is involved in some perceptual and cognitive processes, the functional role of such coherent neuronal behavior is not well understood. As a first step…

Neurons and Cognition · Quantitative Biology 2007-05-23 Takaaki Aoki , Toshio Aoyagi

The response of a neuron to synaptic input strongly depends on whether or not it has just emitted a spike. We propose a neuron model that after spike emission exhibits a partial response to residual input charges and study its collective…

Neurons and Cognition · Quantitative Biology 2010-06-04 Christoph Kirst , Theo Geisel , Marc Timme

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 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…

Disordered Systems and Neural Networks · Physics 2019-05-29 Stefano Luccioli , David Angulo Garcia , Alessandro Torcini

Synchronized oscillations in networks of inhibitory and excitatory coupled bursting neurons are common in a variety of neural systems from central pattern generators to human brain circuits. One example of the latter is the subcortical…

Neurons and Cognition · Quantitative Biology 2011-09-21 Choongseok Park , Leonid L. Rubchinsky

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…

Disordered Systems and Neural Networks · Physics 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…

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…

Neurons and Cognition · Quantitative Biology 2016-09-22 Rodrigo Echeveste , Claudius Gros

Serotonergic, noradrenergic and dopaminergic brainstem (including midbrain) neurons, often exhibit spontaneous and fairly regular spiking with frequencies of order a few Hz, though dopaminergic and noradrenergic neurons only exhibit such…

Neurons and Cognition · Quantitative Biology 2017-04-18 Henry C. Tuckwell , Ying Zhou , Nicholas J. Penington

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…

Biological Physics · Physics 2021-04-28 Vitaly L. Galinsky , Lawrence R. Frank

Nonlinear dynamics of spiking neural networks has recently attracted much interest as an approach to understand possible information processing in the brain and apply it to artificial intelligence. Since information can be processed by…

A single neuron is known to generate almost identical spike trains when the same fluctuating input is repeatedly applied. Here, we study the reliability of spike firing in a pulse-coupled network of oscillator neurons receiving fluctuating…

Adaptation and Self-Organizing Systems · Physics 2015-05-13 Jun-nosuke Teramae , Tomoki Fukai

Networks of model neurons with balanced recurrent excitation and inhibition produce irregular and asynchronous spiking activity. We extend the analysis of balanced networks to include the known dependence of connection probability on the…

Neurons and Cognition · Quantitative Biology 2014-06-02 Robert Rosenbaum , Brent Doiron

In this manuscript, a silent resonator neuron is coupled with a spiking integrator neuron through the gap junction, when the coupled neurons are of different types of excitability and none of the coupled neurons exhibit mixed mode…

Dynamical Systems · Mathematics 2024-01-18 Mohammad Reza Razvan , Somaye Yasaman

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…

Neurons and Cognition · Quantitative Biology 2022-10-19 Matheus Hansen , Paulo R. Protachevicz , Kelly C. Iarosz , Ibere L. Caldas , Antonio M. Batista , Elbert E. N. Macau

The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks…

Neurons and Cognition · Quantitative Biology 2023-12-29 Logan A. Becker , Baowang Li , Nicholas J. Priebe , Eyal Seidemann , Thibaud Taillefumier

Many biological neuronal networks exhibit highly variable spiking activity. Balanced networks offer a parsimonious model of this variability. In balanced networks, strong excitatory synaptic inputs are canceled by strong inhibitory inputs…

Neurons and Cognition · Quantitative Biology 2016-05-04 Ryan Pyle , Robert Rosenbaum

The use of spikes to carry information between brain areas implies complete or partial synchronization of the neurons involved. The degree of synchronization reached by two coupled systems and the energy cost of maintaining their…

Chaotic Dynamics · Physics 2015-06-04 A. Moujahid , A. d'Anjou , F. J. Torrealdea

The dynamical properties of a diluted fully-inhibitory network of pulse-coupled neurons are investigated. Depending on the coupling strength, two different phases can be observed. At low coupling the evolution rapidly converges towards…

Disordered Systems and Neural Networks · Physics 2009-11-11 Ruediger Zillmer , Roberto Livi , Antonio Politi , Alessandro Torcini

Artificial neural networks built from two-state neurons are powerful computational substrates, whose computational ability is well understood by analogy with statistical mechanics. In this work, we introduce similar analogies in the context…

Neural and Evolutionary Computing · Computer Science 2010-09-29 Paul Merolla , Tristan Ursell , John Arthur
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