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1024-channel electrophysiological recordings in macaque V1 and V4 during resting state

Co-variations in resting state activity are thought to arise from a variety of correlated inputs to neurons, such as bottom-up activity from lower areas, feedback from higher areas, recurrent processing in local circuits, and fluctuations in neuromodulatory systems. Most studies have examined restin...

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Autores principales: Chen, Xing, Morales-Gregorio, Aitor, Sprenger, Julia, Kleinjohann, Alexander, Sridhar, Shashwat, van Albada, Sacha J., Grün, Sonja, Roelfsema, Pieter R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917124/
https://www.ncbi.nlm.nih.gov/pubmed/35277528
http://dx.doi.org/10.1038/s41597-022-01180-1
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author Chen, Xing
Morales-Gregorio, Aitor
Sprenger, Julia
Kleinjohann, Alexander
Sridhar, Shashwat
van Albada, Sacha J.
Grün, Sonja
Roelfsema, Pieter R.
author_facet Chen, Xing
Morales-Gregorio, Aitor
Sprenger, Julia
Kleinjohann, Alexander
Sridhar, Shashwat
van Albada, Sacha J.
Grün, Sonja
Roelfsema, Pieter R.
author_sort Chen, Xing
collection PubMed
description Co-variations in resting state activity are thought to arise from a variety of correlated inputs to neurons, such as bottom-up activity from lower areas, feedback from higher areas, recurrent processing in local circuits, and fluctuations in neuromodulatory systems. Most studies have examined resting state activity throughout the brain using MRI scans, or observed local co-variations in activity by recording from a small number of electrodes. We carried out electrophysiological recordings from over a thousand chronically implanted electrodes in the visual cortex of non-human primates, yielding a resting state dataset with unprecedentedly high channel counts and spatiotemporal resolution. Such signals could be used to observe brain waves across larger regions of cortex, offering a temporally detailed picture of brain activity. In this paper, we provide the dataset, describe the raw and processed data formats and data acquisition methods, and indicate how the data can be used to yield new insights into the ‘background’ activity that influences the processing of visual information in our brain.
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spelling pubmed-89171242022-03-28 1024-channel electrophysiological recordings in macaque V1 and V4 during resting state Chen, Xing Morales-Gregorio, Aitor Sprenger, Julia Kleinjohann, Alexander Sridhar, Shashwat van Albada, Sacha J. Grün, Sonja Roelfsema, Pieter R. Sci Data Data Descriptor Co-variations in resting state activity are thought to arise from a variety of correlated inputs to neurons, such as bottom-up activity from lower areas, feedback from higher areas, recurrent processing in local circuits, and fluctuations in neuromodulatory systems. Most studies have examined resting state activity throughout the brain using MRI scans, or observed local co-variations in activity by recording from a small number of electrodes. We carried out electrophysiological recordings from over a thousand chronically implanted electrodes in the visual cortex of non-human primates, yielding a resting state dataset with unprecedentedly high channel counts and spatiotemporal resolution. Such signals could be used to observe brain waves across larger regions of cortex, offering a temporally detailed picture of brain activity. In this paper, we provide the dataset, describe the raw and processed data formats and data acquisition methods, and indicate how the data can be used to yield new insights into the ‘background’ activity that influences the processing of visual information in our brain. Nature Publishing Group UK 2022-03-11 /pmc/articles/PMC8917124/ /pubmed/35277528 http://dx.doi.org/10.1038/s41597-022-01180-1 Text en © The Author(s) 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/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Chen, Xing
Morales-Gregorio, Aitor
Sprenger, Julia
Kleinjohann, Alexander
Sridhar, Shashwat
van Albada, Sacha J.
Grün, Sonja
Roelfsema, Pieter R.
1024-channel electrophysiological recordings in macaque V1 and V4 during resting state
title 1024-channel electrophysiological recordings in macaque V1 and V4 during resting state
title_full 1024-channel electrophysiological recordings in macaque V1 and V4 during resting state
title_fullStr 1024-channel electrophysiological recordings in macaque V1 and V4 during resting state
title_full_unstemmed 1024-channel electrophysiological recordings in macaque V1 and V4 during resting state
title_short 1024-channel electrophysiological recordings in macaque V1 and V4 during resting state
title_sort 1024-channel electrophysiological recordings in macaque v1 and v4 during resting state
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917124/
https://www.ncbi.nlm.nih.gov/pubmed/35277528
http://dx.doi.org/10.1038/s41597-022-01180-1
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