On the relation between bursts and dynamic synapse properties: a modulation-based Ansatz

Authors:
Christian Mayr;Johannes Partzsch;Rene Schüffny
Affiliations:
Chair for Parallel VLSI Systems and Neural Circuits, Dresden University of Technology, Dresden, Germany;Chair for Parallel VLSI Systems and Neural Circuits, Dresden University of Technology, Dresden, Germany;Chair for Parallel VLSI Systems and Neural Circuits, Dresden University of Technology, Dresden, Germany
Venue:
Computational Intelligence and Neuroscience
Year:
2009

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Abstract

When entering a synapse, presynaptic pulse trains are filtered according to the recent pulse history at the synapse and also with respect to their own pulse time course. Various behavioral models have tried to reproduce these complex filtering properties. In particular, the quantal model of neurotransmitter release has been shown to be highly selective for particular presynaptic pulse patterns. However, since the original, pulse-iterative quantal model does not lend itself to mathematical analysis, investigations have only been carried out via simulations. In contrast, we derive a comprehensive explicit expression for the quantal model. We show the correlation between the parameters of this explicit expression and the preferred spike train pattern of the synapse. In particular, our analysis of the transmission of modulated pulse trains across a dynamic synapse links the original parameters of the quantal model to the transmission efficacy of two major spiking regimes, that is, bursting and constant-rate ones.