On numerical simulations of integrate-and-fire neural networks.
about
Towards reproducible descriptions of neuronal network models.A reafferent and feed-forward model of song syntax generation in the Bengalese finchSimulation of networks of spiking neurons: a review of tools and strategies."What" and "where" in visual working memory: a computational neurodynamical perspective for integrating FMRI and single-neuron data.A common cortical circuit mechanism for perceptual categorical discrimination and veridical judgment.Balanced cortical microcircuitry for spatial working memory based on corrective feedback control.Coarse-grained event tree analysis for quantifying Hodgkin-Huxley neuronal network dynamics.Asynchronous Rate Chaos in Spiking Neuronal CircuitsA model of high-frequency oscillatory potentials in retinal ganglion cellsCo-emergence of multi-scale cortical activities of irregular firing, oscillations and avalanches achieves cost-efficient information capacityContinuous and lurching traveling pulses in neuronal networks with delay and spatially decaying connectivity.Finite post synaptic potentials cause a fast neuronal response.A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations.A canonical neural mechanism for behavioral variability.Analytical integrate-and-fire neuron models with conductance-based dynamics and realistic postsynaptic potential time course for event-driven simulation strategies.A general and efficient method for incorporating precise spike times in globally time-driven simulations.Critical analysis of dimension reduction by a moment closure method in a population density approach to neural network modeling.Neuronal spike-train responses in the presence of threshold noise.Confidence estimation as a stochastic process in a neurodynamical system of decision making.Analyzing the effects of gap junction blockade on neural synchrony via a motoneuron network computational model.The functional consequences of cortical circuit abnormalities on gamma oscillations in schizophrenia: insights from computational modeling.How Chaotic is the Balanced State?Compositionality of arm movements can be realized by propagating synchrony.Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks.Singular behavior of slow dynamics of single excitable cells.Limits to high-speed simulations of spiking neural networks using general-purpose computers.On dynamics of integrate-and-fire neural networks with conductance based synapsesBalanced cortical microcircuitry for maintaining information in working memory.Equilibrium and Response Properties of the Integrate-and-Fire Neuron in Discrete Time.Similarity effect and optimal control of multiple-choice decision making.Precision and reliability of periodically and quasiperiodically driven integrate-and-fire neurons.Asynchronous states and the emergence of synchrony in large networks of interacting excitatory and inhibitory neurons.Attention and working memory: a dynamical model of neuronal activity in the prefrontal cortex.Potentiation decay of synapses and length distributions of synfire chains self-organized in recurrent neural networks.Quantization improves stabilization of dynamical systems with delayed feedback.Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.First-passage times in integrate-and-fire neurons with stochastic thresholds.On the performance of voltage stepping for the simulation of adaptive, nonlinear integrate-and-fire neuronal networks.Simplicity and efficiency of integrate-and-fire neuron models.Generalization of the event-based Carnevale-Hines integration scheme for integrate-and-fire models.
P2860
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P2860
On numerical simulations of integrate-and-fire neural networks.
description
1998 nî lūn-bûn
@nan
1998年の論文
@ja
1998年論文
@yue
1998年論文
@zh-hant
1998年論文
@zh-hk
1998年論文
@zh-mo
1998年論文
@zh-tw
1998年论文
@wuu
1998年论文
@zh
1998年论文
@zh-cn
name
On numerical simulations of integrate-and-fire neural networks.
@en
type
label
On numerical simulations of integrate-and-fire neural networks.
@en
prefLabel
On numerical simulations of integrate-and-fire neural networks.
@en
P2093
P2860
P1433
P1476
On numerical simulations of integrate-and-fire neural networks.
@en
P2093
P2860
P304
P356
10.1162/089976698300017845
P577
1998-02-01T00:00:00Z