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Multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs

Ischemic brain injuries are frequent and difficult to detect reliably or early. We present the multi-modal data set containing cardiovascular (blood pressure, blood flow, electrocardiogram) and brain electrical activities to derive electroencephalogram (EEG) biomarkers of corticothalamic communicati...

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Autores principales: Frasch, Martin G., Walter, Bernd, Herry, Christophe L., Bauer, Reinhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7791136/
https://www.ncbi.nlm.nih.gov/pubmed/33414507
http://dx.doi.org/10.1038/s41597-020-00781-y
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author Frasch, Martin G.
Walter, Bernd
Herry, Christophe L.
Bauer, Reinhard
author_facet Frasch, Martin G.
Walter, Bernd
Herry, Christophe L.
Bauer, Reinhard
author_sort Frasch, Martin G.
collection PubMed
description Ischemic brain injuries are frequent and difficult to detect reliably or early. We present the multi-modal data set containing cardiovascular (blood pressure, blood flow, electrocardiogram) and brain electrical activities to derive electroencephalogram (EEG) biomarkers of corticothalamic communication under normal, sedation, and hypoxic/ischemic conditions with ensuing recovery. We provide technical validation using EEGLAB. We also delineate the corresponding changes in the electrocardiogram (ECG)-derived heart rate variability (HRV) with the potential for future in-depth analyses of joint EEG-ECG dynamics. We review an open-source methodology to derive signatures of coupling between the ECoG and electrothalamogram (EThG) signals contained in the presented data set to better characterize the dynamics of thalamocortical communication during these clinically relevant states. The data set is presented in full band sampled at 2000 Hz, so the additional potential exists for insights from the full-band EEG and high-frequency oscillations under the bespoke experimental conditions. Future studies on the dataset may contribute to the development of new brain monitoring technologies, which will facilitate the prevention of neurological injuries.
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spelling pubmed-77911362021-01-15 Multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs Frasch, Martin G. Walter, Bernd Herry, Christophe L. Bauer, Reinhard Sci Data Data Descriptor Ischemic brain injuries are frequent and difficult to detect reliably or early. We present the multi-modal data set containing cardiovascular (blood pressure, blood flow, electrocardiogram) and brain electrical activities to derive electroencephalogram (EEG) biomarkers of corticothalamic communication under normal, sedation, and hypoxic/ischemic conditions with ensuing recovery. We provide technical validation using EEGLAB. We also delineate the corresponding changes in the electrocardiogram (ECG)-derived heart rate variability (HRV) with the potential for future in-depth analyses of joint EEG-ECG dynamics. We review an open-source methodology to derive signatures of coupling between the ECoG and electrothalamogram (EThG) signals contained in the presented data set to better characterize the dynamics of thalamocortical communication during these clinically relevant states. The data set is presented in full band sampled at 2000 Hz, so the additional potential exists for insights from the full-band EEG and high-frequency oscillations under the bespoke experimental conditions. Future studies on the dataset may contribute to the development of new brain monitoring technologies, which will facilitate the prevention of neurological injuries. Nature Publishing Group UK 2021-01-07 /pmc/articles/PMC7791136/ /pubmed/33414507 http://dx.doi.org/10.1038/s41597-020-00781-y 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
Frasch, Martin G.
Walter, Bernd
Herry, Christophe L.
Bauer, Reinhard
Multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs
title Multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs
title_full Multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs
title_fullStr Multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs
title_full_unstemmed Multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs
title_short Multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs
title_sort multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7791136/
https://www.ncbi.nlm.nih.gov/pubmed/33414507
http://dx.doi.org/10.1038/s41597-020-00781-y
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