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Dataset of cortical activity recorded with high spatial resolution from anesthetized rats

Publicly available neural recordings obtained with high spatial resolution are scarce. Here, we present an electrophysiological dataset recorded from the neocortex of twenty rats anesthetized with ketamine/xylazine. The wideband, spontaneous recordings were acquired with a single-shank silicon-based...

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Autores principales: Horváth, Csaba, Tóth, Lili Fanni, Ulbert, István, Fiáth, Richárd
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8282648/
https://www.ncbi.nlm.nih.gov/pubmed/34267214
http://dx.doi.org/10.1038/s41597-021-00970-3
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author Horváth, Csaba
Tóth, Lili Fanni
Ulbert, István
Fiáth, Richárd
author_facet Horváth, Csaba
Tóth, Lili Fanni
Ulbert, István
Fiáth, Richárd
author_sort Horváth, Csaba
collection PubMed
description Publicly available neural recordings obtained with high spatial resolution are scarce. Here, we present an electrophysiological dataset recorded from the neocortex of twenty rats anesthetized with ketamine/xylazine. The wideband, spontaneous recordings were acquired with a single-shank silicon-based probe having 128 densely-packed recording sites arranged in a 32 × 4 array. The dataset contains the activity of a total of 7126 sorted single units extracted from all layers of the cortex. Here, we share raw neural recordings, as well as spike times, extracellular spike waveforms and several properties of units packaged in a standardized electrophysiological data format. For technical validation of our dataset, we provide the distributions of derived single unit properties along with various spike sorting quality metrics. This large collection of in vivo data enables the investigation of the high-resolution electrical footprint of cortical neurons which in turn may aid their electrophysiology-based classification. Furthermore, the dataset might be used to study the laminar-specific neuronal activity during slow oscillation, a brain rhythm strongly involved in neural mechanisms underlying memory consolidation and sleep.
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spelling pubmed-82826482021-07-23 Dataset of cortical activity recorded with high spatial resolution from anesthetized rats Horváth, Csaba Tóth, Lili Fanni Ulbert, István Fiáth, Richárd Sci Data Data Descriptor Publicly available neural recordings obtained with high spatial resolution are scarce. Here, we present an electrophysiological dataset recorded from the neocortex of twenty rats anesthetized with ketamine/xylazine. The wideband, spontaneous recordings were acquired with a single-shank silicon-based probe having 128 densely-packed recording sites arranged in a 32 × 4 array. The dataset contains the activity of a total of 7126 sorted single units extracted from all layers of the cortex. Here, we share raw neural recordings, as well as spike times, extracellular spike waveforms and several properties of units packaged in a standardized electrophysiological data format. For technical validation of our dataset, we provide the distributions of derived single unit properties along with various spike sorting quality metrics. This large collection of in vivo data enables the investigation of the high-resolution electrical footprint of cortical neurons which in turn may aid their electrophysiology-based classification. Furthermore, the dataset might be used to study the laminar-specific neuronal activity during slow oscillation, a brain rhythm strongly involved in neural mechanisms underlying memory consolidation and sleep. Nature Publishing Group UK 2021-07-15 /pmc/articles/PMC8282648/ /pubmed/34267214 http://dx.doi.org/10.1038/s41597-021-00970-3 Text en © The Author(s) 2021 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
Horváth, Csaba
Tóth, Lili Fanni
Ulbert, István
Fiáth, Richárd
Dataset of cortical activity recorded with high spatial resolution from anesthetized rats
title Dataset of cortical activity recorded with high spatial resolution from anesthetized rats
title_full Dataset of cortical activity recorded with high spatial resolution from anesthetized rats
title_fullStr Dataset of cortical activity recorded with high spatial resolution from anesthetized rats
title_full_unstemmed Dataset of cortical activity recorded with high spatial resolution from anesthetized rats
title_short Dataset of cortical activity recorded with high spatial resolution from anesthetized rats
title_sort dataset of cortical activity recorded with high spatial resolution from anesthetized rats
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8282648/
https://www.ncbi.nlm.nih.gov/pubmed/34267214
http://dx.doi.org/10.1038/s41597-021-00970-3
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