Literature DB >> 20407909

Numerical simulation for a neurotransmitter transport model in the axon terminal of a presynaptic neuron.

Andrzej Bielecki1, Piotr Kalita, Marian Lewandowski, Bartłomiej Siwek.   

Abstract

Neurotransmitters in the terminal bouton of a presynaptic neuron are stored in vesicles, which diffuse in the cytoplasm and, after a stimulation signal is received, fuse with the membrane and release its contents into the synaptic cleft. It is commonly assumed that vesicles belong to three pools whose content is gradually exploited during the stimulation. This article presents a model that relies on the assumption that the release ability is associated with the vesicle location in the bouton. As a modeling tool, partial differential equations are chosen as they allow one to express the continuous dependence of the unknown vesicle concentration on both the time and space variables. The model represents the synthesis, concentration-gradient-driven diffusion, and accumulation of vesicles as well as the release of neuroactive substances into the cleft. An initial and boundary value problem is numerically solved using the finite element method (FEM) and the simulation results are presented and discussed. Simulations were run for various assumptions concerning the parameters that govern the synthesis and diffusion processes. The obtained results are shown to be consistent with those obtained for a compartment model based on ordinary differential equations. Such studies can be helpful in gaining a deeper understanding of synaptic processes including physiological pathologies. Furthermore, such mathematical models can be useful for estimating the biological parameters that are included in a model and are hard or impossible to measure directly.

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Year:  2010        PMID: 20407909     DOI: 10.1007/s00422-010-0380-z

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  2 in total

Review 1.  Multiple sclerosis: integration of modeling with biology, clinical and imaging measures to provide better monitoring of disease progression and prediction of outcome.

Authors:  Shikha Jain Goodwin
Journal:  Neural Regen Res       Date:  2016-12       Impact factor: 5.135

2.  Synaptic bouton properties are tuned to best fit the prevailing firing pattern.

Authors:  Markus M Knodel; Romina Geiger; Lihao Ge; Daniel Bucher; Alfio Grillo; Gabriel Wittum; Christoph M Schuster; Gillian Queisser
Journal:  Front Comput Neurosci       Date:  2014-09-09       Impact factor: 2.380

  2 in total

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