Extracting nonlinear integrate-and-fire models from experimental data using dynamic \(I-V\) curves

DOI10.1007/S00422-008-0259-4zbMath1161.92005DBLPjournals/bc/BadelLBPGR08OpenAlexW2144993394WikidataQ33384647 ScholiaQ33384647MaRDI QIDQ999392

Carl C. H. Petersen, Magnus J. E. Richardson, Sandrine Lefort, Laurent Badel, Wulfram Gerstner, Thomas K. Berger

Publication date: 3 February 2009

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

Full work available at URL: https://doi.org/10.1007/s00422-008-0259-4

zbMATH Keywords

Exponential integrate-and-fireI-V curveRefractoriness

Mathematics Subject Classification ID

Neural biology (92C20) Computational methods for problems pertaining to biology (92-08)

Related Items (8)

Mathematical frameworks for oscillatory network dynamics in neuroscience ⋮ Dynamics of the exponential integrate-and-fire model with slow currents and adaptation ⋮ An Empirical Model for Reliable Spiking Activity ⋮ Feature Selection in Simple Neurons: How Coding Depends on Spiking Dynamics ⋮ Special issue on quantitative neuron modeling ⋮ Unnamed Item ⋮ Unnamed Item ⋮ A simple one-dimensional map-based model of spiking neurons with wide ranges of firing rates and complexities

Cites Work

• Spike-train spectra and network response functions for nonlinear integrate-and-fire neurons
• The quantitative single-neuron modeling competition
• A review of the integrate-and-fire neuron model: II. Inhomogeneous synaptic input and network properties
• A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input
• Frequency-dependent response properties of adapting spiking neurons
• Parabolic Bursting in an Excitable System Coupled with a Slow Oscillation
• Spiking Neuron Models

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