Abstract

An enhanced buildup of [Ca2+]i occurs during short-term facilitation (STF) at the crayfish neuromuscular junction (NMJ). As a model system, this NMJ allows discrete postsynaptic quantal events to be counted and characterized in relation to STF. Providing 10 pulses, at 20 and 40Hz, we monitored postsynaptic quantal events over a discrete region of a nerve terminal with a focal macropatch electrode. Characteristics of quantal events were clustered into groups by peak amplitude and time to the peak amplitude. Since the synapses at this NMJ have varied spacing of active zones, number of active zones and synaptic size, the graded nature of synaptic recruitment is likely one means of titrating synaptic efficacy for the graded depolarization on the non-spiking muscle fiber. Synapses in this preparation would appear to have a "quantal signature" that can be used for quantifying their activity which is useful in estimating the overall number of active sites. We use mixture modeling to estimate n (number of active sites) and p (probability of vesicle fusion) from the quantal characteristics. In a preparation that was stimulated at 40Hz, synapses were recruited (increase in n) and the number active synapses increased in p. In a different preparation, p increased as the stimulation was changed from 20 to 40Hz, but n did not show a substantial increase; however, during the STF train, p increases slightly. This study provides a novel approach in determining subsets of the single evoked quanta to better estimate n and p which describe synaptic function.

Document Type

Article

Publication Date

2008

Notes/Citation Information

Published in The Open Neuroscience Journal, v. 2, p. 24-35.

© Desai-Shah et al.; Licensee Bentham Open.

This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

Digital Object Identifier (DOI)

http://dx.doi.org/10.2174/1874082000802010024

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