AUTHOR=Lamanna Jacopo , Signorini Maria G. , Cerutti Sergio , Malgaroli Antonio TITLE=A pre-docking source for the power-law behavior of spontaneous quantal release: application to the analysis of LTP JOURNAL=Frontiers in Cellular Neuroscience VOLUME=9 YEAR=2015 URL=https://www.frontiersin.org/journals/cellular-neuroscience/articles/10.3389/fncel.2015.00044 DOI=10.3389/fncel.2015.00044 ISSN=1662-5102 ABSTRACT=

In neurons, power-law behavior with different scaling exponents has been reported at many different levels, including fluctuations in membrane potentials, synaptic transmission up to neuronal network dynamics. Unfortunately in most cases the source of this non-linear feature remains controversial. Here we have analyzed the dynamics of spontaneous quantal release at hippocampal synapses and characterized their power-law behavior. While in control conditions a fractal exponent greater than zero was rarely observed, its value was greatly increased by α-latrotoxin (α-LTX), a potent stimulator of spontaneous release, known to act at the very last step of vesicle fusion. Based on computer modeling, we confirmed that at an increase in fusion probability would unmask a pre-docking phenomenon with 1/f structure, where α estimated from the release series appears to sense the increase in release probability independently from the number of active sites. In the simplest scenario the pre-docking 1/f process could coincide with the Brownian diffusion of synaptic vesicles. Interestingly, when the effect of long-term potentiation (LTP) was tested, a ~200% long-lasting increase in quantal frequency was accompanied by a significant increase in the scaling exponent. The similarity between the action of LTP and of α-LTX suggests an increased contribution of high release probability sites following the induction of LTP. In conclusion, our results indicate that the source of the synaptic power-law behavior arises before synaptic vesicles dock to the active zone and that the fractal exponent α is capable of sensing a change in release probability independently from the number of active sites or synapses.