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利用CV分析确定突触可塑性位点的实用指南。

A Practical Guide to Using CV Analysis for Determining the Locus of Synaptic Plasticity.

作者信息

Brock Jennifer A, Thomazeau Aurore, Watanabe Airi, Li Sally Si Ying, Sjöström P Jesper

机构信息

Centre for Research in Neuroscience, Brain Repair and Integrative Neuroscience Program, Department of Medicine, The Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada.

Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada.

出版信息

Front Synaptic Neurosci. 2020 Mar 27;12:11. doi: 10.3389/fnsyn.2020.00011. eCollection 2020.

Abstract

Long-term synaptic plasticity is widely believed to underlie learning and memory in the brain. Whether plasticity is primarily expressed pre- or postsynaptically has been the subject of considerable debate for many decades. More recently, it is generally agreed that the locus of plasticity depends on a number of factors, such as developmental stage, induction protocol, and synapse type. Since presynaptic expression alters not just the gain but also the short-term dynamics of a synapse, whereas postsynaptic expression only modifies the gain, the locus has fundamental implications for circuits dynamics and computations in the brain. It therefore remains crucial for our understanding of neuronal circuits to know the locus of expression of long-term plasticity. One classical method for elucidating whether plasticity is pre- or postsynaptically expressed is based on analysis of the coefficient of variation (CV), which serves as a measure of noise levels of synaptic neurotransmission. Here, we provide a practical guide to using CV analysis for the purposes of exploring the locus of expression of long-term plasticity, primarily aimed at beginners in the field. We provide relatively simple intuitive background to an otherwise theoretically complex approach as well as simple mathematical derivations for key parametric relationships. We list important pitfalls of the method, accompanied by accessible computer simulations to better illustrate the problems (downloadable from GitHub), and we provide straightforward solutions for these issues.

摘要

长期突触可塑性被广泛认为是大脑学习和记忆的基础。几十年来,可塑性主要是在突触前还是突触后表达一直是相当多争论的主题。最近,人们普遍认为可塑性的位点取决于许多因素,如发育阶段、诱导方案和突触类型。由于突触前表达不仅改变了突触的增益,还改变了突触的短期动力学,而突触后表达仅改变增益,因此该位点对大脑中的电路动力学和计算具有重要意义。因此,了解长期可塑性的表达位点对于我们理解神经元回路仍然至关重要。一种阐明可塑性是在突触前还是突触后表达的经典方法是基于对变异系数(CV)的分析,CV用作突触神经传递噪声水平的度量。在这里,我们提供了一份实用指南,用于使用CV分析来探索长期可塑性的表达位点,主要针对该领域的初学者。我们为一种在理论上原本复杂的方法提供了相对简单直观的背景知识,以及关键参数关系的简单数学推导。我们列出了该方法的重要陷阱,并伴有易于理解的计算机模拟以更好地说明问题(可从GitHub下载),并且我们为这些问题提供了直接的解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c83/7118219/74ef0c0db342/fnsyn-12-00011-g001.jpg

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