局灶性癫痫发作区内外神经活动的方向性。

IF 3.6 3区 医学 Q2 NEUROSCIENCES
Network Neuroscience Pub Date : 2025-06-30 eCollection Date: 2025-01-01 DOI:10.1162/netn_a_00454
Hamid Karimi-Rouzbahani, Aileen McGonigal
{"title":"局灶性癫痫发作区内外神经活动的方向性。","authors":"Hamid Karimi-Rouzbahani, Aileen McGonigal","doi":"10.1162/netn_a_00454","DOIUrl":null,"url":null,"abstract":"<p><p>Epilepsy affects over 50 million people worldwide, with approximately 30% experiencing drug-resistant forms that may require surgical intervention. Accurate localisation of the epileptogenic zone (EZ) is crucial for effective treatment, but how best to use intracranial EEG data to delineate the EZ remains unclear. Previous studies have used the directionality of neural activities across the brain to investigate seizure dynamics and localise the EZ. However, the different connectivity measures used across studies have often provided inconsistent insights about the direction and the localisation power of signal flow as a biomarker for EZ localisation. In a data-driven approach, this study employs a large set of 13 distinct directed connectivity measures to evaluate neural activity flow in and out the seizure onset zone (SOZ) during interictal and ictal periods. These measures test the hypotheses of \"sink SOZ\" (SOZ dominantly receiving neural activities during interictal periods) and \"source SOZ\" (SOZ dominantly transmitting activities during ictal periods). While the results were different across connectivity measures, several measures consistently supported higher connectivity directed towards the SOZ in interictal periods and higher connectivity directed away during ictal periods. Comparing six distinct metrics of node behaviour in the network, we found that SOZ separates itself from the rest of the network, allowing for the metric of \"<i>eccentricity</i>\" to localise the SOZ more accurately than any other metrics including \"<i>in strength</i>\" and \"<i>out strength</i>.\" This introduced a novel biomarker for localising the SOZ, leveraging the discriminative power of directed connectivity measures in an explainable machine learning pipeline. By using a comprehensive, objective, and data-driven approach, this study addresses previously unresolved questions on the direction of neural activities in seizure organisation and sheds light on dynamics of interictal and ictal activity in focal epilepsy.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"9 2","pages":"798-823"},"PeriodicalIF":3.6000,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12226147/pdf/","citationCount":"0","resultStr":"{\"title\":\"Directionality of neural activity in and out of the seizure onset zone in focal epilepsy.\",\"authors\":\"Hamid Karimi-Rouzbahani, Aileen McGonigal\",\"doi\":\"10.1162/netn_a_00454\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Epilepsy affects over 50 million people worldwide, with approximately 30% experiencing drug-resistant forms that may require surgical intervention. Accurate localisation of the epileptogenic zone (EZ) is crucial for effective treatment, but how best to use intracranial EEG data to delineate the EZ remains unclear. Previous studies have used the directionality of neural activities across the brain to investigate seizure dynamics and localise the EZ. However, the different connectivity measures used across studies have often provided inconsistent insights about the direction and the localisation power of signal flow as a biomarker for EZ localisation. In a data-driven approach, this study employs a large set of 13 distinct directed connectivity measures to evaluate neural activity flow in and out the seizure onset zone (SOZ) during interictal and ictal periods. These measures test the hypotheses of \\\"sink SOZ\\\" (SOZ dominantly receiving neural activities during interictal periods) and \\\"source SOZ\\\" (SOZ dominantly transmitting activities during ictal periods). While the results were different across connectivity measures, several measures consistently supported higher connectivity directed towards the SOZ in interictal periods and higher connectivity directed away during ictal periods. Comparing six distinct metrics of node behaviour in the network, we found that SOZ separates itself from the rest of the network, allowing for the metric of \\\"<i>eccentricity</i>\\\" to localise the SOZ more accurately than any other metrics including \\\"<i>in strength</i>\\\" and \\\"<i>out strength</i>.\\\" This introduced a novel biomarker for localising the SOZ, leveraging the discriminative power of directed connectivity measures in an explainable machine learning pipeline. By using a comprehensive, objective, and data-driven approach, this study addresses previously unresolved questions on the direction of neural activities in seizure organisation and sheds light on dynamics of interictal and ictal activity in focal epilepsy.</p>\",\"PeriodicalId\":48520,\"journal\":{\"name\":\"Network Neuroscience\",\"volume\":\"9 2\",\"pages\":\"798-823\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2025-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12226147/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Network Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1162/netn_a_00454\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Network Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1162/netn_a_00454","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

全世界有5000多万人患有癫痫,其中约30%患有可能需要手术干预的耐药形式。准确定位癫痫区(EZ)对于有效治疗至关重要,但如何最好地使用颅内脑电图数据来划定EZ仍不清楚。以前的研究已经利用整个大脑的神经活动的方向性来调查癫痫发作的动态和定位EZ。然而,研究中使用的不同连通性测量方法通常对信号流的方向和定位能力作为EZ定位的生物标志物提供了不一致的见解。在数据驱动的方法中,本研究采用了大量的13种不同的定向连接测量来评估癫痫发作区(SOZ)在间歇期和发作期的神经活动流。这些测量方法验证了“sink SOZ”(在间歇期主要接收神经活动)和“source SOZ”(在间歇期主要传递神经活动)的假设。虽然不同连接性测量的结果不同,但有几个测量一致支持在间隔期指向SOZ的更高连接性和在临界期指向SOZ的更高连接性。比较网络中节点行为的六个不同指标,我们发现SOZ将自己与网络的其余部分分开,允许“偏心”指标比任何其他指标(包括“强度”和“强度”)更准确地定位SOZ。这为定位SOZ引入了一种新的生物标志物,在可解释的机器学习管道中利用定向连接测量的判别能力。通过使用全面、客观和数据驱动的方法,本研究解决了以前未解决的癫痫发作组织中神经活动方向的问题,并阐明了局灶性癫痫发作间期和发作期活动的动态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Directionality of neural activity in and out of the seizure onset zone in focal epilepsy.

Epilepsy affects over 50 million people worldwide, with approximately 30% experiencing drug-resistant forms that may require surgical intervention. Accurate localisation of the epileptogenic zone (EZ) is crucial for effective treatment, but how best to use intracranial EEG data to delineate the EZ remains unclear. Previous studies have used the directionality of neural activities across the brain to investigate seizure dynamics and localise the EZ. However, the different connectivity measures used across studies have often provided inconsistent insights about the direction and the localisation power of signal flow as a biomarker for EZ localisation. In a data-driven approach, this study employs a large set of 13 distinct directed connectivity measures to evaluate neural activity flow in and out the seizure onset zone (SOZ) during interictal and ictal periods. These measures test the hypotheses of "sink SOZ" (SOZ dominantly receiving neural activities during interictal periods) and "source SOZ" (SOZ dominantly transmitting activities during ictal periods). While the results were different across connectivity measures, several measures consistently supported higher connectivity directed towards the SOZ in interictal periods and higher connectivity directed away during ictal periods. Comparing six distinct metrics of node behaviour in the network, we found that SOZ separates itself from the rest of the network, allowing for the metric of "eccentricity" to localise the SOZ more accurately than any other metrics including "in strength" and "out strength." This introduced a novel biomarker for localising the SOZ, leveraging the discriminative power of directed connectivity measures in an explainable machine learning pipeline. By using a comprehensive, objective, and data-driven approach, this study addresses previously unresolved questions on the direction of neural activities in seizure organisation and sheds light on dynamics of interictal and ictal activity in focal epilepsy.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Network Neuroscience
Network Neuroscience NEUROSCIENCES-
CiteScore
6.40
自引率
6.40%
发文量
68
审稿时长
16 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信