Literature DB >> 26972952

Determining synaptic parameters using high-frequency activation.

Monica S Thanawala1, Wade G Regehr2.   

Abstract

BACKGROUND: The specific properties of a synapse determine how neuronal activity evokes neurotransmitter release. Evaluating changes in synaptic properties during sustained activity is essential to understanding how genetic manipulations and neuromodulators regulate neurotransmitter release. Analyses of postsynaptic responses to high-frequency stimulation have provided estimates of the size of the readily-releasable pool (RRP) of vesicles (N0) and the probability of vesicular release (p) at multiple synapses. NEW
METHOD: Here, we introduce a model-based approach at the calyx of Held synapse in which depletion and the rate of replenishment (R) determine the number of available vesicles, and facilitation leads to a use-dependent increase in p when initial p is low.
RESULTS: When p is high and R is low, we find excellent agreement between estimates based on all three methods and the model. However, when p is low or when significant replenishment occurs between stimuli, estimates of different methods diverge, and model estimates are between the extreme estimates provided by the other approaches. COMPARISON WITH OTHER
METHODS: We compare our model-based approach to three other approaches that rely on different simplifying assumptions. Our findings suggest that our model provides a better estimate of N0 and p than previously-established methods, likely due to inaccurate assumptions about replenishment. More generally, our findings suggest that approaches commonly used to estimate N0 and p at other synapses are often applied under experimental conditions that yield inaccurate estimates.
CONCLUSIONS: Careful application of appropriate methods can greatly improve estimates of synaptic parameters.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Calyx of Held; Readily-releasable pool; Release probability; Synaptic transmission

Mesh:

Year:  2016        PMID: 26972952      PMCID: PMC4833598          DOI: 10.1016/j.jneumeth.2016.02.021

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


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