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Abstract
A miniature postsynaptic current (mPSC) is a small, rare, and highly variable spontaneous synaptic event that is generally caused by the spontaneous release of single vesicles. The amplitude and variability of mPSCs are key measures of the postsynaptic processes and are taken as the main characteristics of an elementary unit (quantal size) in traditional quantal analysis of synaptic transmission. Due to different sources of biological and measurement noise, recordings of mPSCs exhibit high trial-to-trial heterogeneity, and experimental measurements of mPSCs are usually noisy and scarce, making their analysis demanding. Here, we present a sequential procedure for precise analysis of mPSC amplitude distributions for the range of small currents. To illustrate the developed approach, we chose previously obtained experimental data on the effect of the extracellular matrix on synaptic plasticity. The proposed statistical technique allowed us to identify previously unnoticed additional modality in the mPSC amplitude distributions, indicating the formation of new immature synapses upon ECM attenuation. We show that our approach can reliably detect multimodality in the distributions of mPSC amplitude, allowing for accurate determination of the size and variability of the quantal synaptic response. Thus, the proposed method can significantly expand the informativeness of both existing and newly obtained experimental data. We also demonstrated that mPSC amplitudes around the threshold of microcurrent excitation follow the Gumbel distribution rather than the binomial statistics traditionally used for a wide range of currents, either for a single synapse or when taking into consideration small influences of the adjacent synapses. Such behaviour is argued to originate from the theory of extreme processes. Specifically, recorded mPSCs represent instant random current fluctuations, among which there are relatively larger spikes (extreme events). They required more level of coherence that can be provided by different mechanisms of network or system level activation including neuron circuit signalling and extrasynaptic processes.
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1 Lobachevsky State University of Nizhny Novgorod, Scientific-Educational Mathematical Center “Mathematics of Future Technologies”, Nizhny Novgorod, Russia (GRID:grid.28171.3d) (ISNI:0000 0001 0344 908X); Samara State Medical University, Neuroscience Research Institute, Samara, Russia (GRID:grid.445780.a) (ISNI:0000 0001 0235 2817)
2 Russian Academy of Sciences, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia (GRID:grid.4886.2) (ISNI:0000 0001 2192 9124)
3 Kursk State University, Kursk, Russia (GRID:grid.445569.f) (ISNI:0000 0001 0816 8076)