ArticleNeuromethods2016
Extracting quantal properties of transmission at central synapses.
Article in Neuromethods, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Inferring synaptic transmission from the stochastic dynamics of the quantal content: An analytical approach.PLoS computational biology · 2025Article
- Predation cues induce predator specific changes in olfactory neurons encoding defensive responses in agile frog tadpoles.PloS one · 2024Article
- Studying Synaptic Connectivity and Strength with Optogenetics and Patch-Clamp Electrophysiology.International journal of molecular sciences · 2022Review
- The functional properties of synapses made by regenerated axons across spinal cord lesion sites in lamprey.Neural regeneration research · 2022Article
- Overexpression of Neuregulin-1 Type III Has Impact on Visual Function in Mice.International journal of molecular sciences · 2022Article
- rTg(TauFrontiers in synaptic neuroscience · 2022Article
- Model-Based Inference of Synaptic Transmission.Frontiers in synaptic neuroscience · 2019Review
- Presynaptic Effects of N-Methyl-D-Aspartate Receptors Enhance Parvalbumin Cell-Mediated Inhibition of Pyramidal Cells in Mouse Prefrontal Cortex.Biological psychiatry · 2018Article
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Abstract
Chemical synapses enable neurons to communicate rapidly, process and filter signals and to store information. However, studying their functional properties is difficult because synaptic connections typically consist of multiple synaptic contacts that release vesicles stochastically and exhibit time-dependent behavior. Moreover, most central synapses are small and inaccessible to direct measurements. Estimation of synaptic properties from responses recorded at the soma is complicated by the presence of nonuniform release probability and nonuniform quantal properties. The presence of multivesicular release and postsynaptic receptor saturation at some synapses can also complicate the interpretation of quantal parameters. Multiple-probability fluctuation analysis (MPFA; also known as variance-mean analysis) is a method that has been developed for estimating synaptic parameters from the variance and mean amplitude of synaptic responses recorded at different release probabilities. This statistical approach, which incorporates nonuniform synaptic properties, has become widely used for studying synaptic transmission. In this chapter, we describe the statistical models used to extract quantal parameters and discuss their interpretation when applying MPFA.
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