Minneci, F and Kanichay, RT and Silver, RA (2012) Estimation of the time course of neurotransmitter release at central synapses from the first latency of postsynaptic currents. J Neurosci Methods , 205 (1) 49 - 64. 10.1016/j.jneumeth.2011.12.015.
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Measurement of the release time course (RTC) and of the quantal content is important for quantifying synaptic precision and understanding the molecular basis of the release process at central synapses. In theory, the RTC can be determined directly from the histogram of first latencies of quantal events only if a maximum of one vesicle is released per trial, but at most synapses multiple vesicles are released. Traditionally, first latency histograms have been corrected for multiple releases using a simple correction, derived by Barrett and Stevens (BS; 1972b) for quantifying release at the neuromuscular junction. This correction has also been used to quantify release at central synapses. We show, by combining an analytical approach and numerical simulations of stochastic quantal release, that the BS correction gives a biased estimate for RTC and quantal content. The bias increases with release probability, and is therefore particularly problematic for central synapses. We show that this is due to assuming infinite availability of releasable vesicles and we derive a formula for estimating the RTC from first latencies without this assumption. The resulting 'binomial correction' requires knowledge of the maximum number of quanta that can be released following an action potential (N), which can be estimated with variance-mean analysis. We show with simulations that estimating RTC and quantal content from first latencies using the binomial correction is robust in the presence of noise and when release probability is non-uniform. We also provide an alternative method for estimating RTC from the first latencies when N cannot be determined.
|Title:||Estimation of the time course of neurotransmitter release at central synapses from the first latency of postsynaptic currents.|
|Additional information:||PMCID: PMC3314961|
|Keywords:||Algorithms, Data Interpretation, Statistical, Miniature Postsynaptic Potentials, Models, Neurological, Neurotransmitter Agents, Normal Distribution, Reproducibility of Results, Stochastic Processes, Synapses, Synaptic Transmission, Synaptic Vesicles, Time Factors|
|UCL classification:||UCL > School of Life and Medical Sciences > Faculty of Life Sciences > Biosciences (Division of) > Neuroscience, Physiology and Pharmacology|
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
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