Mathematical analysis and algorithms for efficiently and accurately implementing stochastic simulations of short-term synaptic depression and facilitation

Date

2013-05-10

Authors

McDonnell, Mark D.
Mohan, Ashutosh
Stricker, Christian

Journal Title

Journal ISSN

Volume Title

Publisher

Frontiers Research Foundation

Abstract

The release of neurotransmitter vesicles after arrival of a pre-synaptic action potential (AP) at cortical synapses is known to be a stochastic process, as is the availability of vesicles for release. These processes are known to also depend on the recent history of AP arrivals, and this can be described in terms of time-varying probabilities of vesicle release. Mathematical models of such synaptic dynamics frequently are based only on the mean number of vesicles released by each pre-synaptic AP, since if it is assumed there are sufficiently many vesicle sites, then variance is small. However, it has been shown recently that variance across sites can be significant for neuron and network dynamics, and this suggests the potential importance of studying short-term plasticity using simulations that do generate trial-to-trial variability. Therefore, in this paper we study several well-known conceptual models for stochastic availability and release. We state explicitly the random variables that these models describe and propose efficient algorithms for accurately implementing stochastic simulations of these random variables in software or hardware. Our results are complemented by mathematical analysis and statement of pseudo-code algorithms.

Description

Keywords

facilitation, short term depression, short term plasticity, short term synaptic dynamics, stochastic simulation, stochastic synapse, synaptic plasticity models, vesicle site model

Citation

Source

Frontiers in Computational Neuroscience

Type

Journal article

Book Title

Entity type

Access Statement

Open Access

License Rights

DOI

10.3389/fncom.2013.00058

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