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

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 o...

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Autores principales: Brock, Jennifer A., Thomazeau, Aurore, Watanabe, Airi, Li, Sally Si Ying, Sjöström, P. Jesper
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118219/
https://www.ncbi.nlm.nih.gov/pubmed/32292337
http://dx.doi.org/10.3389/fnsyn.2020.00011
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author Brock, Jennifer A.
Thomazeau, Aurore
Watanabe, Airi
Li, Sally Si Ying
Sjöström, P. Jesper
author_facet Brock, Jennifer A.
Thomazeau, Aurore
Watanabe, Airi
Li, Sally Si Ying
Sjöström, P. Jesper
author_sort Brock, Jennifer A.
collection PubMed
description 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.
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spelling pubmed-71182192020-04-14 A Practical Guide to Using CV Analysis for Determining the Locus of Synaptic Plasticity Brock, Jennifer A. Thomazeau, Aurore Watanabe, Airi Li, Sally Si Ying Sjöström, P. Jesper Front Synaptic Neurosci Neuroscience 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. Frontiers Media S.A. 2020-03-27 /pmc/articles/PMC7118219/ /pubmed/32292337 http://dx.doi.org/10.3389/fnsyn.2020.00011 Text en Copyright © 2020 Brock, Thomazeau, Watanabe, Li and Sjöström. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Brock, Jennifer A.
Thomazeau, Aurore
Watanabe, Airi
Li, Sally Si Ying
Sjöström, P. Jesper
A Practical Guide to Using CV Analysis for Determining the Locus of Synaptic Plasticity
title A Practical Guide to Using CV Analysis for Determining the Locus of Synaptic Plasticity
title_full A Practical Guide to Using CV Analysis for Determining the Locus of Synaptic Plasticity
title_fullStr A Practical Guide to Using CV Analysis for Determining the Locus of Synaptic Plasticity
title_full_unstemmed A Practical Guide to Using CV Analysis for Determining the Locus of Synaptic Plasticity
title_short A Practical Guide to Using CV Analysis for Determining the Locus of Synaptic Plasticity
title_sort practical guide to using cv analysis for determining the locus of synaptic plasticity
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118219/
https://www.ncbi.nlm.nih.gov/pubmed/32292337
http://dx.doi.org/10.3389/fnsyn.2020.00011
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