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A transcriptomic axis predicts state modulation of cortical interneurons
Transcriptomics has revealed that cortical inhibitory neurons exhibit a great diversity of fine molecular subtypes(1–6), but it is not known whether these subtypes have correspondingly diverse patterns of activity in the living brain. Here we show that inhibitory subtypes in primary visual cortex (V...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279161/ https://www.ncbi.nlm.nih.gov/pubmed/35794483 http://dx.doi.org/10.1038/s41586-022-04915-7 |
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author | Bugeon, Stéphane Duffield, Joshua Dipoppa, Mario Ritoux, Anne Prankerd, Isabelle Nicoloutsopoulos, Dimitris Orme, David Shinn, Maxwell Peng, Han Forrest, Hamish Viduolyte, Aiste Reddy, Charu Bai Isogai, Yoh Carandini, Matteo Harris, Kenneth D. |
author_facet | Bugeon, Stéphane Duffield, Joshua Dipoppa, Mario Ritoux, Anne Prankerd, Isabelle Nicoloutsopoulos, Dimitris Orme, David Shinn, Maxwell Peng, Han Forrest, Hamish Viduolyte, Aiste Reddy, Charu Bai Isogai, Yoh Carandini, Matteo Harris, Kenneth D. |
author_sort | Bugeon, Stéphane |
collection | PubMed |
description | Transcriptomics has revealed that cortical inhibitory neurons exhibit a great diversity of fine molecular subtypes(1–6), but it is not known whether these subtypes have correspondingly diverse patterns of activity in the living brain. Here we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain state, which are organized by a single factor: position along the main axis of transcriptomic variation. We combined in vivo two-photon calcium imaging of mouse V1 with a transcriptomic method to identify mRNA for 72 selected genes in ex vivo slices. We classified inhibitory neurons imaged in layers 1–3 into a three-level hierarchy of 5 subclasses, 11 types and 35 subtypes using previously defined transcriptomic clusters(3). Responses to visual stimuli differed significantly only between subclasses, with cells in the Sncg subclass uniformly suppressed, and cells in the other subclasses predominantly excited. Modulation by brain state differed at all hierarchical levels but could be largely predicted from the first transcriptomic principal component, which also predicted correlations with simultaneously recorded cells. Inhibitory subtypes that fired more in resting, oscillatory brain states had a smaller fraction of their axonal projections in layer 1, narrower spikes, lower input resistance and weaker adaptation as determined in vitro(7), and expressed more inhibitory cholinergic receptors. Subtypes that fired more during arousal had the opposite properties. Thus, a simple principle may largely explain how diverse inhibitory V1 subtypes shape state-dependent cortical processing. |
format | Online Article Text |
id | pubmed-9279161 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92791612022-07-15 A transcriptomic axis predicts state modulation of cortical interneurons Bugeon, Stéphane Duffield, Joshua Dipoppa, Mario Ritoux, Anne Prankerd, Isabelle Nicoloutsopoulos, Dimitris Orme, David Shinn, Maxwell Peng, Han Forrest, Hamish Viduolyte, Aiste Reddy, Charu Bai Isogai, Yoh Carandini, Matteo Harris, Kenneth D. Nature Article Transcriptomics has revealed that cortical inhibitory neurons exhibit a great diversity of fine molecular subtypes(1–6), but it is not known whether these subtypes have correspondingly diverse patterns of activity in the living brain. Here we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain state, which are organized by a single factor: position along the main axis of transcriptomic variation. We combined in vivo two-photon calcium imaging of mouse V1 with a transcriptomic method to identify mRNA for 72 selected genes in ex vivo slices. We classified inhibitory neurons imaged in layers 1–3 into a three-level hierarchy of 5 subclasses, 11 types and 35 subtypes using previously defined transcriptomic clusters(3). Responses to visual stimuli differed significantly only between subclasses, with cells in the Sncg subclass uniformly suppressed, and cells in the other subclasses predominantly excited. Modulation by brain state differed at all hierarchical levels but could be largely predicted from the first transcriptomic principal component, which also predicted correlations with simultaneously recorded cells. Inhibitory subtypes that fired more in resting, oscillatory brain states had a smaller fraction of their axonal projections in layer 1, narrower spikes, lower input resistance and weaker adaptation as determined in vitro(7), and expressed more inhibitory cholinergic receptors. Subtypes that fired more during arousal had the opposite properties. Thus, a simple principle may largely explain how diverse inhibitory V1 subtypes shape state-dependent cortical processing. Nature Publishing Group UK 2022-07-06 2022 /pmc/articles/PMC9279161/ /pubmed/35794483 http://dx.doi.org/10.1038/s41586-022-04915-7 Text en © The Author(s) 2022, corrected publication 2022 https://creativecommons.org/licenses/by/4.0/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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Bugeon, Stéphane Duffield, Joshua Dipoppa, Mario Ritoux, Anne Prankerd, Isabelle Nicoloutsopoulos, Dimitris Orme, David Shinn, Maxwell Peng, Han Forrest, Hamish Viduolyte, Aiste Reddy, Charu Bai Isogai, Yoh Carandini, Matteo Harris, Kenneth D. A transcriptomic axis predicts state modulation of cortical interneurons |
title | A transcriptomic axis predicts state modulation of cortical interneurons |
title_full | A transcriptomic axis predicts state modulation of cortical interneurons |
title_fullStr | A transcriptomic axis predicts state modulation of cortical interneurons |
title_full_unstemmed | A transcriptomic axis predicts state modulation of cortical interneurons |
title_short | A transcriptomic axis predicts state modulation of cortical interneurons |
title_sort | transcriptomic axis predicts state modulation of cortical interneurons |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279161/ https://www.ncbi.nlm.nih.gov/pubmed/35794483 http://dx.doi.org/10.1038/s41586-022-04915-7 |
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