title: Model of an excitatory synapse based on stochastic processes.
abstract: We present a mathematical model of a biological synapse based on stochastic processes to establish the temporal behavior of the postsynaptic potential following a quantal synaptic transmission. This potential form is the basis of the neural code. We suppose that the release of neurotransmitters in the synaptic cleft follows a Poisson process, and that they diffuse according to integrated Ornstein-Uhlenbeck processes in 3-D with random initial positions and velocities. The diffusion occurs in an isotropic environment between two infinite parallel planes representing the pre- and postsynaptic membrane. We state that the presynaptic membrane is perfectly reflecting and that the other is perfectly absorbing. The activation of the receptors polarizes the postsynaptic membrane according to a parallel RC circuit scheme. We present the results obtained by simulations according to a Gillespie algorithm and we show that our model exhibits realistic postsynaptic behaviors from a simple quantal occurrence.
authors.forename: Pierre-Yves
authors.initials: PY
authors.lastname: L'Espérance
authors.forename: Richard
authors.initials: R
authors.lastname: Labib
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D008959:Models, Neurological; D018377:Neurotransmitter Agents / Q000378:metabolism; D013269:Stochastic Processes; D013569:Synapses / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*
chemical_list: D018377:Neurotransmitter Agents