ArticleJournal of neuroscience methods2012
Estimation of the time course of neurotransmitter release at central synapses from the first latency of postsynaptic currents.
Article in Journal of neuroscience methods, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- SyNC, a Computationally Extensive and Realistic Neural Net to Identify Relative Impacts of Synaptopathy Mechanisms on Glutamatergic Neurons and Their Networks in Autism and Complex Neurological Disorders.Frontiers in cellular neuroscience · 2021Article
- Article
- SpiFoG: an efficient supervised learning algorithm for the network of spiking neurons.Scientific reports · 2020Article
- A Delay Learning Algorithm Based on Spike Train Kernels for Spiking Neurons.Frontiers in neuroscience · 2019Article
- NeuroMatic: An Integrated Open-Source Software Toolkit for Acquisition, Analysis and Simulation of Electrophysiological Data.Frontiers in neuroinformatics · 2018Article
- Synaptic reliability and temporal precision are achieved via high quantal content and effective replenishment: auditory brainstem versus hippocampus.The Journal of physiology · 2017Article
- Extracting quantal properties of transmission at central synapses.Neuromethods · 2016Article
- GABA Signaling and Neuroactive Steroids in Adrenal Medullary Chromaffin Cells.Frontiers in cellular neuroscience · 2016Review
- Bayesian analysis of the kinetics of quantal transmitter secretion at the neuromuscular junction.Journal of computational neuroscience · 2015Article
- Strength and duration of perisomatic GABAergic inhibition depend on distance between synaptically connected cells.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- Data-driven modeling of synaptic transmission and integration.Progress in molecular biology and translational science · 2014Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
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.
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