Stochastic model of central synapses: slow diffusion of transmitter interacting with spatially distributed receptors and transporters

J Theor Biol. 1999 May 7;198(1):101-20. doi: 10.1006/jtbi.1999.0905.

Abstract

A detailed mathematical analysis of the diffusion process of neurotransmitter inside the synaptic cleft is presented and the spatio-temporal concentration profile is calculated. Using information about the experimentally observed time course of glutamate in the cleft the effective diffusion coefficient Dnet is estimated as Dnet approximately 20-50 nm(2) microseconds(-1), implying a strong reduction compared with free diffusion in aqueous solution. The tortuosity of the cleft and interactions with transporter molecules are assumed to affect the transmitter motion. We estimate the transporter density to be 5170 to 8900 micrometer(-2) in the synaptic cleft and its vicinity, using the experimentally observed time constant of glutamate. Furthermore a theoretical model of synaptic transmission is presented, taking the spatial distribution of post-synaptic (AMPA-) receptors into account. The transmitter diffusion and receptor dynamics are modeled by Monte Carlo simulations preserving the typically observed noisy character of post-synaptic responses. Distributions of amplitudes, rise and decay times are calculated and shown to agree well with experiments. Average open probabilities are computed from a novel kinetic model and are shown to agree with averages over many Monte Carlo runs. Our results suggest that post-synaptic currents are only weakly potentiated by clustering of post-synaptic receptors, but increase linearly with the total number of receptors. Distributions of amplitudes and rise times are used to discriminate between different morphologies, e.g. simple and perforated synapses. A skew in the miniature amplitude distribution can be caused by multiple release of pre-synaptic vesicles at perforated synapses.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computer Simulation*
  • Glutamic Acid / physiology
  • Models, Neurological*
  • Monte Carlo Method
  • Neurotransmitter Agents / physiology*
  • Receptors, Neurotransmitter / physiology*
  • Synaptic Transmission / physiology*
  • Time Factors

Substances

  • Neurotransmitter Agents
  • Receptors, Neurotransmitter
  • Glutamic Acid