ArticleJournal of neurophysiology2013
Reliable evaluation of the quantal determinants of synaptic efficacy using Bayesian analysis.
Article in Journal of neurophysiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Spinal microcircuits go through multiphasic homeostatic compensations in a mouse model of motoneuron degeneration.Cell reports · 2024Article
- Spinal microcircuits go through multiphasic homeostatic compensations in a mouse model of motoneuron degeneration.bioRxiv : the preprint server for biology · 2024Article
- Efficient sampling-based Bayesian Active Learning for synaptic characterization.PLoS computational biology · 2023Article
- Article
- Article
- Linear-nonlinear cascades capture synaptic dynamics.PLoS computational biology · 2021Article
- Sensory neuron-derived NaScience advances · 2020Article
- Identifiability of a Binomial Synapse.Frontiers in computational neuroscience · 2020Article
- Strong preference for autaptic self-connectivity of neocortical PV interneurons facilitates their tuning to γ-oscillations.PLoS biology · 2019Article
- Model-Based Inference of Synaptic Transmission.Frontiers in synaptic neuroscience · 2019Review
- Parsing Out the Variability of Transmission at Central Synapses Using Optical Quantal Analysis.Frontiers in synaptic neuroscience · 2019Article
- Segregation of glutamatergic and cholinergic transmission at the mixed motoneuron Renshaw cell synapse.Scientific reports · 2017Article
- The readily releasable pool of synaptic vesicles.Current opinion in neurobiology · 2017Review
- Functional consequences of pre- and postsynaptic expression of synaptic plasticity.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017Review
- Extracting quantal properties of transmission at central synapses.Neuromethods · 2016Article
- Bayesian Inference of Synaptic Quantal Parameters from Correlated Vesicle Release.Frontiers in computational neuroscience · 2016Article
- Synaptic Connectivity between Renshaw Cells and Motoneurons in the Recurrent Inhibitory Circuit of the Spinal Cord.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2015Article
- The recurrent case for the Renshaw cell.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2014Article
- Probabilistic inference of short-term synaptic plasticity in neocortical microcircuits.Frontiers in computational neuroscience · 2013Article
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2 authors.
Funding
Abstract
Communication between neurones in the central nervous system depends on synaptic transmission. The efficacy of synapses is determined by pre- and postsynaptic factors that can be characterized using quantal parameters such as the probability of neurotransmitter release, number of release sites, and quantal size. Existing methods of estimating the quantal parameters based on multiple probability fluctuation analysis (MPFA) are limited by their requirement for long recordings to acquire substantial data sets. We therefore devised an algorithm, termed Bayesian Quantal Analysis (BQA), that can yield accurate estimates of the quantal parameters from data sets of as small a size as 60 observations for each of only 2 conditions of release probability. Computer simulations are used to compare its performance in accuracy with that of MPFA, while varying the number of observations and the simulated range in release probability. We challenge BQA with realistic complexities characteristic of complex synapses, such as increases in the intra- or intersite variances, and heterogeneity in release probabilities. Finally, we validate the method using experimental data obtained from electrophysiological recordings to show that the effect of an antagonist on postsynaptic receptors is correctly characterized by BQA by a specific reduction in the estimates of quantal size. Since BQA routinely yields reliable estimates of the quantal parameters from small data sets, it is ideally suited to identify the locus of synaptic plasticity for experiments in which repeated manipulations of the recording environment are unfeasible.
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