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Journal of Computational Neuroscience

Erschienen in:

01.02.2014

Low dimensional model of bursting neurons

verfasst von: X. Zhao, J. W. Kim, P. A. Robinson, C. J. Rennie

Erschienen in: Journal of Computational Neuroscience | Ausgabe 1/2014

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Abstract

A computationally efficient, biophysically-based model of neuronal behavior is presented; it incorporates ion channel dynamics in its two fast ion channels while preserving simplicity by representing only one slow ion current. The model equations are shown to provide a wide array of physiological dynamics in terms of spiking patterns, bursting, subthreshold oscillations, and chaotic firing. Despite its simplicity, the model is capable of simulating an extensive range of spiking patterns. Several common neuronal behaviors observed in vivo are demonstrated by varying model parameters. These behaviors are classified into dynamical classes using phase diagrams whose boundaries in parameter space prove to be accurately delineated by linear stability analysis. This simple model is suitable for use in large scale simulations involving neural field theory or neuronal networks.

Vorheriger Artikel Gap junction permeability modulated by dopamine exerts effects on spatial and temporal correlation of retinal ganglion cells’ firing activities

Nächster Artikel A single functional model of drivers and modulators in cortex

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Titel: Low dimensional model of bursting neurons
verfasst von: X. Zhao
J. W. Kim
P. A. Robinson
C. J. Rennie
Publikationsdatum: 01.02.2014
Verlag: Springer US
Erschienen in: Journal of Computational Neuroscience / Ausgabe 1/2014
Print ISSN: 0929-5313
Elektronische ISSN: 1573-6873
DOI: https://doi.org/10.1007/s10827-013-0468-2

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