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Inherent seizure susceptibility in patients with antihistamine-induced acute symptomatic seizure: a resting-state EEG analysis
We compared neural activities and network properties between the antihistamine-induced seizures (AIS) and seizure-free groups, with the hypothesis that patients with AIS might have inherently increased neural activities and network properties that are easily synchronized. Resting-state electroenceph...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241146/ https://www.ncbi.nlm.nih.gov/pubmed/37277514 http://dx.doi.org/10.1038/s41598-023-36415-7 |
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author | Kim, Hayom Wang, In-Nea Park, Jun-Su Kim, Keun-Tae Kong, Jooheon Kim, Jung Bin Kim, Dong-Joo |
author_facet | Kim, Hayom Wang, In-Nea Park, Jun-Su Kim, Keun-Tae Kong, Jooheon Kim, Jung Bin Kim, Dong-Joo |
author_sort | Kim, Hayom |
collection | PubMed |
description | We compared neural activities and network properties between the antihistamine-induced seizures (AIS) and seizure-free groups, with the hypothesis that patients with AIS might have inherently increased neural activities and network properties that are easily synchronized. Resting-state electroencephalography (EEG) data were collected from 27 AIS patients and 30 healthy adults who had never had a seizure. Power spectral density analysis was used to compare neural activities in each localized region. Functional connectivity (FC) was measured using coherence, and graph theoretical analyses were performed to compare network properties between the groups. Machine learning algorithms were applied using measurements found to be different between the groups in the EEG analyses as input features. Compared with the seizure-free group, the AIS group showed a higher spectral power in the entire regions of the delta, theta, and beta bands, as well as in the frontal areas of the alpha band. The AIS group had a higher overall FC strength, as well as a shorter characteristic path length in the theta band and higher global efficiency, local efficiency, and clustering coefficient in the beta band than the seizure-free group. The Support Vector Machine, k-Nearest Neighbor, and Random Forest models distinguished the AIS group from the seizure-free group with a high accuracy of more than 99%. The AIS group had seizure susceptibility considering both regional neural activities and functional network properties. Our findings provide insights into the underlying pathophysiological mechanisms of AIS and may be useful for the differential diagnosis of new-onset seizures in the clinical setting. |
format | Online Article Text |
id | pubmed-10241146 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102411462023-06-06 Inherent seizure susceptibility in patients with antihistamine-induced acute symptomatic seizure: a resting-state EEG analysis Kim, Hayom Wang, In-Nea Park, Jun-Su Kim, Keun-Tae Kong, Jooheon Kim, Jung Bin Kim, Dong-Joo Sci Rep Article We compared neural activities and network properties between the antihistamine-induced seizures (AIS) and seizure-free groups, with the hypothesis that patients with AIS might have inherently increased neural activities and network properties that are easily synchronized. Resting-state electroencephalography (EEG) data were collected from 27 AIS patients and 30 healthy adults who had never had a seizure. Power spectral density analysis was used to compare neural activities in each localized region. Functional connectivity (FC) was measured using coherence, and graph theoretical analyses were performed to compare network properties between the groups. Machine learning algorithms were applied using measurements found to be different between the groups in the EEG analyses as input features. Compared with the seizure-free group, the AIS group showed a higher spectral power in the entire regions of the delta, theta, and beta bands, as well as in the frontal areas of the alpha band. The AIS group had a higher overall FC strength, as well as a shorter characteristic path length in the theta band and higher global efficiency, local efficiency, and clustering coefficient in the beta band than the seizure-free group. The Support Vector Machine, k-Nearest Neighbor, and Random Forest models distinguished the AIS group from the seizure-free group with a high accuracy of more than 99%. The AIS group had seizure susceptibility considering both regional neural activities and functional network properties. Our findings provide insights into the underlying pathophysiological mechanisms of AIS and may be useful for the differential diagnosis of new-onset seizures in the clinical setting. Nature Publishing Group UK 2023-06-05 /pmc/articles/PMC10241146/ /pubmed/37277514 http://dx.doi.org/10.1038/s41598-023-36415-7 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kim, Hayom Wang, In-Nea Park, Jun-Su Kim, Keun-Tae Kong, Jooheon Kim, Jung Bin Kim, Dong-Joo Inherent seizure susceptibility in patients with antihistamine-induced acute symptomatic seizure: a resting-state EEG analysis |
title | Inherent seizure susceptibility in patients with antihistamine-induced acute symptomatic seizure: a resting-state EEG analysis |
title_full | Inherent seizure susceptibility in patients with antihistamine-induced acute symptomatic seizure: a resting-state EEG analysis |
title_fullStr | Inherent seizure susceptibility in patients with antihistamine-induced acute symptomatic seizure: a resting-state EEG analysis |
title_full_unstemmed | Inherent seizure susceptibility in patients with antihistamine-induced acute symptomatic seizure: a resting-state EEG analysis |
title_short | Inherent seizure susceptibility in patients with antihistamine-induced acute symptomatic seizure: a resting-state EEG analysis |
title_sort | inherent seizure susceptibility in patients with antihistamine-induced acute symptomatic seizure: a resting-state eeg analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241146/ https://www.ncbi.nlm.nih.gov/pubmed/37277514 http://dx.doi.org/10.1038/s41598-023-36415-7 |
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