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Constructing plasticity phenotypes to classify experience-dependent development of the visual cortex

View ORCID ProfileJustin L. Balsor, View ORCID ProfileDavid G. Jones, View ORCID ProfileKathryn M. Murphy
doi: https://doi.org/10.1101/2020.01.07.896191
Justin L. Balsor
1McMaster Integrative Neuroscience Discovery and Study (MiNDS) Program, McMaster University, Hamilton, ON, L8S 4K1, Canada
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David G. Jones
2Pairwise Affinity Inc, Dundas, ON, L9H 2R9, Canada
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Kathryn M. Murphy
1McMaster Integrative Neuroscience Discovery and Study (MiNDS) Program, McMaster University, Hamilton, ON, L8S 4K1, Canada
3Department of Psychology, Neuroscience & Behavior, McMaster University, Hamilton, ON, L8S 4K1, Canada
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  • For correspondence: kmurphy@mcmaster.ca
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Abstract

Many neural mechanisms regulate experience-dependent plasticity in the visual cortex (V1) and new techniques for quantifying large numbers of proteins or genes are transforming how plasticity is studied into the era of big data. With those large data sets comes the challenge of extracting biologically meaningful results about visual plasticity from data-driven analytical methods designed for high-dimensional data. In other areas of neuroscience, high-information content methodologies are revealing more subtle aspects of neural development and individual variations that give rise to a richer picture of brain disorders. We have developed an approach for studying V1 plasticity that takes advantage of the known functions of many synaptic proteins for regulating visual plasticity and using that to rebrand the results of high-dimensional analyses into a plasticity phenotype. Here we provide a primer for analyzing experience-dependent plasticity in V1 using example R code to identify high-dimensional changes in a group of proteins. We describe using PCA to classify high-dimensional plasticity features and use them to construct a plasticity phenotype. In the examples, we show how the plasticity phenotype can be visualized and used to identify neurobiological features in V1 that change during development or after different visual rearing conditions. We include an R package “v1hdexplorer” that aggregates the various coding packages and custom visualization scripts written in R Studio.

Footnotes

  • Funding Sources: NSERC Grant RGPIN-2015-06215 awarded to KM, Woodburn Heron OGS awarded to JB.

  • Data Availability: The data used to support the findings of this study are available from the corresponding author upon request.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted January 08, 2020.
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Constructing plasticity phenotypes to classify experience-dependent development of the visual cortex
Justin L. Balsor, David G. Jones, Kathryn M. Murphy
bioRxiv 2020.01.07.896191; doi: https://doi.org/10.1101/2020.01.07.896191
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Constructing plasticity phenotypes to classify experience-dependent development of the visual cortex
Justin L. Balsor, David G. Jones, Kathryn M. Murphy
bioRxiv 2020.01.07.896191; doi: https://doi.org/10.1101/2020.01.07.896191

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