[Alterations of β-γ coupling of scalp electroencephalography during epilepsy].

Epilepsy Modulation index Phase-amplitude coupling Scalp electroencephalography

Journal

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
ISSN: 1001-5515
Titre abrégé: Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
Pays: China
ID NLM: 9426398

Informations de publication

Date de publication:
25 Aug 2023
Historique:
medline: 6 9 2023
pubmed: 5 9 2023
entrez: 4 9 2023
Statut: ppublish

Résumé

Uncovering the alterations of neural interactions within the brain during epilepsy is important for the clinical diagnosis and treatment. Previous studies have shown that the phase-amplitude coupling (PAC) can be used as a potential biomarker for locating epileptic zones and characterizing the transition of epileptic phases. However, in contrast to the θ-γ coupling widely investigated in epilepsy, few studies have paid attention to the β-γ coupling, as well as its potential applications. In the current study, we use the modulation index (MI) to calculate the scalp electroencephalography (EEG)-based β-γ coupling and investigate the corresponding changes during different epileptic phases. The results show that the β-γ coupling of each brain region changes with the evolution of epilepsy, and in several brain regions, the β-γ coupling decreases during the ictal period but increases in the post-ictal period, where the differences are statistically significant. Moreover, the alterations of β-γ coupling between different brain regions can also be observed, and the strength of β-γ coupling increases in the post-ictal period, where the differences are also significant. Taken together, these findings not only contribute to understanding neural interactions within the brain during the evolution of epilepsy, but also provide a new insight into the clinical treatment. 揭示癫痫过程中脑内信息交互变化对临床诊疗具有重要意义。早期研究表明,相位-幅度耦合(PAC)可作为定位致痫区域和表征癫痫状态转换的潜在生物标志物。然而,目前癫痫的相位-幅度耦合研究多集中于θ-γ耦合,对β-γ耦合在癫痫过程中的变化及潜在应用知之甚少。对此,本文基于癫痫头皮脑电(EEG)数据,采用调节指数(MI)的PAC方法,探究癫痫不同状态下β-γ耦合的变化。结果发现,癫痫过程中各脑区内β-γ耦合随状态发生改变,多数脑区内的β-γ耦合在发作期减小,在发作后期增加,其差异具有统计学意义。癫痫过程中不同脑区间也存在β-γ耦合,且β-γ耦合强度在发作后期增加,其差异具有统计学意义。这些研究结果既有助于理解癫痫过程中脑内信息交互的改变,也为癫痫的临床诊疗提供了新参考。.

Autres résumés

Type: Publisher (chi)
揭示癫痫过程中脑内信息交互变化对临床诊疗具有重要意义。早期研究表明,相位-幅度耦合(PAC)可作为定位致痫区域和表征癫痫状态转换的潜在生物标志物。然而,目前癫痫的相位-幅度耦合研究多集中于θ-γ耦合,对β-γ耦合在癫痫过程中的变化及潜在应用知之甚少。对此,本文基于癫痫头皮脑电(EEG)数据,采用调节指数(MI)的PAC方法,探究癫痫不同状态下β-γ耦合的变化。结果发现,癫痫过程中各脑区内β-γ耦合随状态发生改变,多数脑区内的β-γ耦合在发作期减小,在发作后期增加,其差异具有统计学意义。癫痫过程中不同脑区间也存在β-γ耦合,且β-γ耦合强度在发作后期增加,其差异具有统计学意义。这些研究结果既有助于理解癫痫过程中脑内信息交互的改变,也为癫痫的临床诊疗提供了新参考。.

Identifiants

pubmed: 37666760
doi: 10.7507/1001-5515.202212024
pmc: PMC10477402
doi:

Types de publication

English Abstract Journal Article

Langues

chi

Sous-ensembles de citation

IM

Pagination

700-708

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Auteurs

Kaijie Li (K)

Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China.

Junfeng Lu (J)

Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China.

Renping Yu (R)

Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China.
Research Center for Intelligent Science and Engineering Technology of Traditional Chinese Medicine, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China.

Rui Zhang (R)

Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China.
Research Center for Intelligent Science and Engineering Technology of Traditional Chinese Medicine, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China.

Mingming Chen (M)

Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China.
Research Center for Intelligent Science and Engineering Technology of Traditional Chinese Medicine, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China.

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