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Behavioral decomposition reveals rich encoding structure employed across neocortex in rats

The cortical population code is pervaded by activity patterns evoked by movement, but it remains largely unknown how such signals relate to natural behavior or how they might support processing in sensory cortices where they have been observed. To address this we compared high-density neural recordi...

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Autores principales: Mimica, Bartul, Tombaz, Tuçe, Battistin, Claudia, Fuglstad, Jingyi Guo, Dunn, Benjamin A., Whitlock, Jonathan R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10319800/
https://www.ncbi.nlm.nih.gov/pubmed/37402724
http://dx.doi.org/10.1038/s41467-023-39520-3
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author Mimica, Bartul
Tombaz, Tuçe
Battistin, Claudia
Fuglstad, Jingyi Guo
Dunn, Benjamin A.
Whitlock, Jonathan R.
author_facet Mimica, Bartul
Tombaz, Tuçe
Battistin, Claudia
Fuglstad, Jingyi Guo
Dunn, Benjamin A.
Whitlock, Jonathan R.
author_sort Mimica, Bartul
collection PubMed
description The cortical population code is pervaded by activity patterns evoked by movement, but it remains largely unknown how such signals relate to natural behavior or how they might support processing in sensory cortices where they have been observed. To address this we compared high-density neural recordings across four cortical regions (visual, auditory, somatosensory, motor) in relation to sensory modulation, posture, movement, and ethograms of freely foraging male rats. Momentary actions, such as rearing or turning, were represented ubiquitously and could be decoded from all sampled structures. However, more elementary and continuous features, such as pose and movement, followed region-specific organization, with neurons in visual and auditory cortices preferentially encoding mutually distinct head-orienting features in world-referenced coordinates, and somatosensory and motor cortices principally encoding the trunk and head in egocentric coordinates. The tuning properties of synaptically coupled cells also exhibited connection patterns suggestive of area-specific uses of pose and movement signals, particularly in visual and auditory regions. Together, our results indicate that ongoing behavior is encoded at multiple levels throughout the dorsal cortex, and that low-level features are differentially utilized by different regions to serve locally relevant computations.
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spelling pubmed-103198002023-07-06 Behavioral decomposition reveals rich encoding structure employed across neocortex in rats Mimica, Bartul Tombaz, Tuçe Battistin, Claudia Fuglstad, Jingyi Guo Dunn, Benjamin A. Whitlock, Jonathan R. Nat Commun Article The cortical population code is pervaded by activity patterns evoked by movement, but it remains largely unknown how such signals relate to natural behavior or how they might support processing in sensory cortices where they have been observed. To address this we compared high-density neural recordings across four cortical regions (visual, auditory, somatosensory, motor) in relation to sensory modulation, posture, movement, and ethograms of freely foraging male rats. Momentary actions, such as rearing or turning, were represented ubiquitously and could be decoded from all sampled structures. However, more elementary and continuous features, such as pose and movement, followed region-specific organization, with neurons in visual and auditory cortices preferentially encoding mutually distinct head-orienting features in world-referenced coordinates, and somatosensory and motor cortices principally encoding the trunk and head in egocentric coordinates. The tuning properties of synaptically coupled cells also exhibited connection patterns suggestive of area-specific uses of pose and movement signals, particularly in visual and auditory regions. Together, our results indicate that ongoing behavior is encoded at multiple levels throughout the dorsal cortex, and that low-level features are differentially utilized by different regions to serve locally relevant computations. Nature Publishing Group UK 2023-07-04 /pmc/articles/PMC10319800/ /pubmed/37402724 http://dx.doi.org/10.1038/s41467-023-39520-3 Text en © The Author(s) 2023 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
Mimica, Bartul
Tombaz, Tuçe
Battistin, Claudia
Fuglstad, Jingyi Guo
Dunn, Benjamin A.
Whitlock, Jonathan R.
Behavioral decomposition reveals rich encoding structure employed across neocortex in rats
title Behavioral decomposition reveals rich encoding structure employed across neocortex in rats
title_full Behavioral decomposition reveals rich encoding structure employed across neocortex in rats
title_fullStr Behavioral decomposition reveals rich encoding structure employed across neocortex in rats
title_full_unstemmed Behavioral decomposition reveals rich encoding structure employed across neocortex in rats
title_short Behavioral decomposition reveals rich encoding structure employed across neocortex in rats
title_sort behavioral decomposition reveals rich encoding structure employed across neocortex in rats
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10319800/
https://www.ncbi.nlm.nih.gov/pubmed/37402724
http://dx.doi.org/10.1038/s41467-023-39520-3
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