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Quantitative analysis of rabies virus-based synaptic connectivity tracing

Monosynaptically restricted rabies viruses have been used for more than a decade for synaptic connectivity tracing. However, the verisimilitude of quantitative conclusions drawn from these experiments is largely unknown. The primary reason is the simple metrics commonly used, which generally disrega...

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Detalles Bibliográficos
Autores principales: Tran-Van-Minh, Alexandra, Ye, Zhiwen, Rancz, Ede
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10062636/
https://www.ncbi.nlm.nih.gov/pubmed/36996085
http://dx.doi.org/10.1371/journal.pone.0278053
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author Tran-Van-Minh, Alexandra
Ye, Zhiwen
Rancz, Ede
author_facet Tran-Van-Minh, Alexandra
Ye, Zhiwen
Rancz, Ede
author_sort Tran-Van-Minh, Alexandra
collection PubMed
description Monosynaptically restricted rabies viruses have been used for more than a decade for synaptic connectivity tracing. However, the verisimilitude of quantitative conclusions drawn from these experiments is largely unknown. The primary reason is the simple metrics commonly used, which generally disregard the effect of starter cell numbers. Here we present an experimental dataset with a broad range of starter cell numbers and explore their relationship with the number of input cells across the brain using descriptive statistics and modelling. We show that starter cell numbers strongly affect input fraction and convergence index measures, making quantitative comparisons unreliable. Furthermore, we suggest a principled way to analyse rabies derived connectivity data by taking advantage of the starter vs input cell relationship that we describe and validate across independent datasets.
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spelling pubmed-100626362023-03-31 Quantitative analysis of rabies virus-based synaptic connectivity tracing Tran-Van-Minh, Alexandra Ye, Zhiwen Rancz, Ede PLoS One Research Article Monosynaptically restricted rabies viruses have been used for more than a decade for synaptic connectivity tracing. However, the verisimilitude of quantitative conclusions drawn from these experiments is largely unknown. The primary reason is the simple metrics commonly used, which generally disregard the effect of starter cell numbers. Here we present an experimental dataset with a broad range of starter cell numbers and explore their relationship with the number of input cells across the brain using descriptive statistics and modelling. We show that starter cell numbers strongly affect input fraction and convergence index measures, making quantitative comparisons unreliable. Furthermore, we suggest a principled way to analyse rabies derived connectivity data by taking advantage of the starter vs input cell relationship that we describe and validate across independent datasets. Public Library of Science 2023-03-30 /pmc/articles/PMC10062636/ /pubmed/36996085 http://dx.doi.org/10.1371/journal.pone.0278053 Text en © 2023 Tran-Van-Minh et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Tran-Van-Minh, Alexandra
Ye, Zhiwen
Rancz, Ede
Quantitative analysis of rabies virus-based synaptic connectivity tracing
title Quantitative analysis of rabies virus-based synaptic connectivity tracing
title_full Quantitative analysis of rabies virus-based synaptic connectivity tracing
title_fullStr Quantitative analysis of rabies virus-based synaptic connectivity tracing
title_full_unstemmed Quantitative analysis of rabies virus-based synaptic connectivity tracing
title_short Quantitative analysis of rabies virus-based synaptic connectivity tracing
title_sort quantitative analysis of rabies virus-based synaptic connectivity tracing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10062636/
https://www.ncbi.nlm.nih.gov/pubmed/36996085
http://dx.doi.org/10.1371/journal.pone.0278053
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