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PMID: 8792231 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. Research Support, U.S. Gov't, P.H.S. Review

Synthesis of models for excitable membranes, synaptic transmission and neuromodulation using a common kinetic formalism.

Journal of computational neuroscience ·Vol. 1 ·No. 3 ·1994-08-00 ·Pages 195-230

Destexhe A, Mainen ZF, Sejnowski TJ

Abstract

Markov kinetic models were used to synthesize a complete description of synaptic transmission, including opening of voltage-dependent channels in the presynaptic terminal, release of neurotransmitter, gating of postsynaptic receptors, and activation of second-messenger systems. These kinetic schemes provide a more general framework for modeling ion channels than the Hodgkin-Huxley formalism, supporting a continuous spectrum of descriptions ranging from the very simple and computationally efficient to the highly complex and biophysically precise. Examples are given of simple kinetic schemes based on fits to experimental data that capture the essential properties of voltage-gated, synaptic and neuromodulatory currents. The Markov formalism allows the dynamics of ionic currents to be considered naturally in the larger context of biochemical signal transduction. This framework can facilitate the integration of a wide range of experimental data and promote consistent theoretical analysis of neural mechanisms from molecular interactions to network computations.

MeSH Terms
Animals Cell Membrane/metabolism Kinetics Models, Neurological Neurotransmitter Agents/metabolism Synaptic Transmission/physiology
Chemicals
Neurotransmitter Agents
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Destexhe A
Howard Hughes Medical Institute, Computational Neurobiology Laboratory, La Jolla, CA 92037, USA.
Mainen Z F
Sejnowski T J
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Article Info
Journal
Journal of computational neuroscience
Abbr.
J Comput Neurosci
ISSN
0929-5313
DOI
10.1007/BF00961734
Published
1994-08-00
Pages
195-230
Language
English
Region
United States
NLM ID
9439510
Subset
IM
External Links
PubMed source DOI: 10.1007/BF00961734 View journal details
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