Stochastic and reduced biophysical models of synaptic transmission

Abstract

Stochastic and reduced biophysical models of synaptic transmission are formulated and evaluated. The synaptic transmission involves presynaptic facilitation of neurotransmitter release, depletion and recovery of the presynaptic pool of readily releasable vesicles containing neurotransmitter molecules and saturation of postsynaptic receptors of both fast non-NMDA and slow NMDA types. The models are shown to display the principal dynamical characteristics experimentally observed of synaptic transmission. The two main types of neural coding, i.e. rate and temporal coding, can be distinguished by means of different dynamical properties of synaptic transmission determined by initial neurotransmitter release probability and presynaptic firing rate. From the temporal evolution of the postsynaptic membrane potential response to a train of presynaptic action potentials at a sustained firing rate, in particular the steady-state amplitude and steady-state average level of postsynaptic membrane potentials are determined as functions of both initial release probability and presynaptic firing rate. The models are applicable to studies of the primary stages of learning processes and can be extended tO incorporate short-term and long-term potentiation in memory consolidation processes.