Scientific-Educational Mathematical Center "Mathematics of Future Technologies", Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.
Neuroscience Research Institute, Samara State Medical University, Samara, Russia, 443079.
Sci Rep. 2023 Sep 20;13(1):15660. doi: 10.1038/s41598-023-42882-9.
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.
微突触后电流（mPSC）是一种微小、罕见且高度变化的自发性突触事件，通常由单个囊泡的自发性释放引起。mPSC 的幅度和变异性是突触后过程的关键衡量标准，被视为传统突触传递量子分析中基本单元（量子大小）的主要特征。由于生物和测量噪声的不同来源，mPSC 的记录表现出高度的试验间异质性，并且 mPSC 的实验测量通常是嘈杂和稀缺的，这使得它们的分析具有挑战性。在这里，我们提出了一种用于精确分析小电流范围内 mPSC 幅度分布的顺序程序。为了说明所提出的方法，我们选择了先前关于细胞外基质对突触可塑性影响的实验数据。所提出的统计技术使我们能够识别 mPSC 幅度分布中以前未被注意到的附加模态，表明在 ECM 衰减时形成新的不成熟突触。我们表明，我们的方法可以可靠地检测 mPSC 幅度分布中的多模态，从而能够准确确定量子突触反应的大小和变异性。因此，所提出的方法可以显著扩展现有和新获得的实验数据的信息量。我们还证明，在微电流激发的阈值附近，mPSC 幅度遵循 Gumbel 分布，而不是传统上用于广泛电流范围的二项式统计，无论是对于单个突触还是考虑到相邻突触的小影响时都是如此。这种行为被认为源自极端过程理论。具体来说，记录的 mPSC 代表随机电流波动的瞬间，其中存在相对较大的尖峰（极端事件）。它们需要更高的相干性，这可以由包括神经元电路信号和 extrasynaptic 过程在内的网络或系统级激活的不同机制提供。
