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Intrinsic electrophysiological properties predict variability in morphology and connectivity among striatal Parvalbumin-expressing Pthlh-cells

Determining the cellular content of the nervous system in terms of cell types and the rules of their connectivity represents a fundamental challenge to the neurosciences. The recent advent of high-throughput techniques, such as single-cell RNA-sequencing has allowed for greater resolution in the ide...

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Autores principales: Bengtsson Gonzales, Carolina, Hunt, Steven, Munoz-Manchado, Ana B., McBain, Chris J., Hjerling-Leffler, Jens
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518419/
https://www.ncbi.nlm.nih.gov/pubmed/32973206
http://dx.doi.org/10.1038/s41598-020-72588-1
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author Bengtsson Gonzales, Carolina
Hunt, Steven
Munoz-Manchado, Ana B.
McBain, Chris J.
Hjerling-Leffler, Jens
author_facet Bengtsson Gonzales, Carolina
Hunt, Steven
Munoz-Manchado, Ana B.
McBain, Chris J.
Hjerling-Leffler, Jens
author_sort Bengtsson Gonzales, Carolina
collection PubMed
description Determining the cellular content of the nervous system in terms of cell types and the rules of their connectivity represents a fundamental challenge to the neurosciences. The recent advent of high-throughput techniques, such as single-cell RNA-sequencing has allowed for greater resolution in the identification of cell types and/or states. Although most of the current neuronal classification schemes comprise discrete clusters, several recent studies have suggested that, perhaps especially, within the striatum, neuronal populations exist in continua, with regards to both their molecular and electrophysiological properties. Whether these continua are stable properties, established during development, or if they reflect acute differences in activity-dependent regulation of critical genes is currently unknown. We set out to determine whether gradient-like molecular differences in the recently described Pthlh-expressing inhibitory interneuron population, which contains the Pvalb-expressing cells, correlate with differences in morphological and connectivity properties. We show that morphology and long-range inputs correlate with a spatially organized molecular and electrophysiological gradient of Pthlh-interneurons, suggesting that the processing of different types of information (by distinct anatomical striatal regions) has different computational requirements.
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spelling pubmed-75184192020-09-29 Intrinsic electrophysiological properties predict variability in morphology and connectivity among striatal Parvalbumin-expressing Pthlh-cells Bengtsson Gonzales, Carolina Hunt, Steven Munoz-Manchado, Ana B. McBain, Chris J. Hjerling-Leffler, Jens Sci Rep Article Determining the cellular content of the nervous system in terms of cell types and the rules of their connectivity represents a fundamental challenge to the neurosciences. The recent advent of high-throughput techniques, such as single-cell RNA-sequencing has allowed for greater resolution in the identification of cell types and/or states. Although most of the current neuronal classification schemes comprise discrete clusters, several recent studies have suggested that, perhaps especially, within the striatum, neuronal populations exist in continua, with regards to both their molecular and electrophysiological properties. Whether these continua are stable properties, established during development, or if they reflect acute differences in activity-dependent regulation of critical genes is currently unknown. We set out to determine whether gradient-like molecular differences in the recently described Pthlh-expressing inhibitory interneuron population, which contains the Pvalb-expressing cells, correlate with differences in morphological and connectivity properties. We show that morphology and long-range inputs correlate with a spatially organized molecular and electrophysiological gradient of Pthlh-interneurons, suggesting that the processing of different types of information (by distinct anatomical striatal regions) has different computational requirements. Nature Publishing Group UK 2020-09-24 /pmc/articles/PMC7518419/ /pubmed/32973206 http://dx.doi.org/10.1038/s41598-020-72588-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Bengtsson Gonzales, Carolina
Hunt, Steven
Munoz-Manchado, Ana B.
McBain, Chris J.
Hjerling-Leffler, Jens
Intrinsic electrophysiological properties predict variability in morphology and connectivity among striatal Parvalbumin-expressing Pthlh-cells
title Intrinsic electrophysiological properties predict variability in morphology and connectivity among striatal Parvalbumin-expressing Pthlh-cells
title_full Intrinsic electrophysiological properties predict variability in morphology and connectivity among striatal Parvalbumin-expressing Pthlh-cells
title_fullStr Intrinsic electrophysiological properties predict variability in morphology and connectivity among striatal Parvalbumin-expressing Pthlh-cells
title_full_unstemmed Intrinsic electrophysiological properties predict variability in morphology and connectivity among striatal Parvalbumin-expressing Pthlh-cells
title_short Intrinsic electrophysiological properties predict variability in morphology and connectivity among striatal Parvalbumin-expressing Pthlh-cells
title_sort intrinsic electrophysiological properties predict variability in morphology and connectivity among striatal parvalbumin-expressing pthlh-cells
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518419/
https://www.ncbi.nlm.nih.gov/pubmed/32973206
http://dx.doi.org/10.1038/s41598-020-72588-1
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