Conductance-based refractory density approach: comparison with experimental data and generalization to lognormal distribution of input current

DOI10.1007/s00422-017-0727-9zbMath1400.92087DBLPjournals/bc/Chizhov17OpenAlexW2749494937WikidataQ38618915 ScholiaQ38618915MaRDI QIDQ1990660

Anton V. Chizhov

Publication date: 25 October 2018

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00422-017-0727-9

zbMATH Keywords

lognormal distributionconductance-based refractory density modelfiring-rate modelneuronal population

Mathematics Subject Classification ID

Neural biology (92C20) PDEs in connection with biology, chemistry and other natural sciences (35Q92)

Related Items (2)

Conductance-based refractory density approach for a population of bursting neurons ⋮ Mapping input noise to escape noise in integrate-and-fire neurons: a level-crossing approach

Cites Work

• The parameters of the stochastic leaky integrate-and-fire neuronal model
• A population density approach that facilitates large-scale modeling of neural networks: Analysis and an application in orientation tuning
• Conductance-based refractory density model of primary visual cortex
• Modeling Neuronal Assemblies: Theory and Implementation
• Dynamics of Neuronal Populations: The Equilibrium Solution
• Spiking Neuron Models
• Rate Models for Conductance-Based Cortical Neuronal Networks

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