How Well Do Mean Field Theories of Spiking Quadratic-Integrate-And-Fire Networks Work in Realistic Parameter Regimes?

Journal of Computational Neuroscience - Netherlands
doi 10.1007/s10827-013-0481-5
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Springer Science and Business Media LLC

Related search

Mean-Field Analysis of Orientation Selectivity in Inhibition-Dominated Networks of Spiking Neurons

SpringerPlus
Multidisciplinary
2014English

A Mean-Field Approach to the Dynamics of Networks of Complex Neurons, From Nonlinear Integrate-And-Fire to Hodgkin-Huxley Models

Journal of Neurophysiology
NeurosciencePhysiology
2019English

A Mean-Field Description of Bursting Dynamics in Spiking Neural Networks With Short-Term Adaptation

2019English

Determinants of Associative Memory Performance in Spiking and Non-Spiking Neural Networks With Different Synaptic Plasticity Regimes

BMC Neuroscience
NeuroscienceCellularMolecular Neuroscience
2012English

Associative Memory of Phase-Coded Spatiotemporal Patterns in Leaky Integrate and Fire Networks

Journal of Computational Neuroscience
Molecular NeuroscienceSensory SystemsCellularCognitive Neuroscience
2012English

Optimal Detection of a Localized Perturbation in Random Networks of Integrate-And-Fire Neurons

Physical Review Letters
AstronomyPhysics
2017English

Topological Effects on Dynamics in Complex Pulse-Coupled Networks of Integrate-And-Fire Type

Physical Review E
2012English

Effect of Network Structure on Spike Train Correlations in Networks of Integrate-And-Fire Neurons

BMC Neuroscience
NeuroscienceCellularMolecular Neuroscience
2011English

Cooperative Linear-Quadratic Mean Field Control and Hamiltonian Matrix Analysis

English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy