Huifang E. Wang, Borana Dollomaja, Paul Triebkorn, Gian Marco Duma, Adam Williamson, Julia Makhalova, Jean-Didier Lemarechal, Fabrice Bartolomei, Viktor Jirsa
{"title":"虚拟脑双胞胎刺激癫痫。","authors":"Huifang E. Wang, Borana Dollomaja, Paul Triebkorn, Gian Marco Duma, Adam Williamson, Julia Makhalova, Jean-Didier Lemarechal, Fabrice Bartolomei, Viktor Jirsa","doi":"10.1038/s43588-025-00841-6","DOIUrl":null,"url":null,"abstract":"Estimating the epileptogenic zone network (EZN) is an important part of the diagnosis of drug-resistant focal epilepsy and has a pivotal role in treatment and intervention. Virtual brain twins provide a modeling method for personalized diagnosis and treatment. They integrate patient-specific brain topography with structural connectivity from anatomical neuroimaging such as magnetic resonance imaging, and dynamic activity from functional recordings such as electroencephalography (EEG) and stereo-EEG (SEEG). Seizures show rich spatial and temporal features in functional recordings, which can be exploited to estimate the EZN. Stimulation-induced seizures can provide important and complementary information. Here we consider invasive SEEG stimulation and non-invasive temporal interference stimulation as a complementary approach. This paper offers a high-resolution virtual brain twin framework for EZN diagnosis based on stimulation-induced seizures. It provides an important methodological and conceptual basis to make the transition from invasive to non-invasive diagnosis and treatment of drug-resistant focal epilepsy. A high-resolution virtual brain twin approach is proposed using stimulation-induced seizures to estimate the epileptogenic network, offering a step toward non-invasive diagnosis and treatment of drug-resistant focal epilepsy.","PeriodicalId":74246,"journal":{"name":"Nature computational science","volume":"5 9","pages":"754-768"},"PeriodicalIF":18.3000,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s43588-025-00841-6.pdf","citationCount":"0","resultStr":"{\"title\":\"Virtual brain twins for stimulation in epilepsy\",\"authors\":\"Huifang E. Wang, Borana Dollomaja, Paul Triebkorn, Gian Marco Duma, Adam Williamson, Julia Makhalova, Jean-Didier Lemarechal, Fabrice Bartolomei, Viktor Jirsa\",\"doi\":\"10.1038/s43588-025-00841-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Estimating the epileptogenic zone network (EZN) is an important part of the diagnosis of drug-resistant focal epilepsy and has a pivotal role in treatment and intervention. Virtual brain twins provide a modeling method for personalized diagnosis and treatment. They integrate patient-specific brain topography with structural connectivity from anatomical neuroimaging such as magnetic resonance imaging, and dynamic activity from functional recordings such as electroencephalography (EEG) and stereo-EEG (SEEG). Seizures show rich spatial and temporal features in functional recordings, which can be exploited to estimate the EZN. Stimulation-induced seizures can provide important and complementary information. Here we consider invasive SEEG stimulation and non-invasive temporal interference stimulation as a complementary approach. This paper offers a high-resolution virtual brain twin framework for EZN diagnosis based on stimulation-induced seizures. It provides an important methodological and conceptual basis to make the transition from invasive to non-invasive diagnosis and treatment of drug-resistant focal epilepsy. A high-resolution virtual brain twin approach is proposed using stimulation-induced seizures to estimate the epileptogenic network, offering a step toward non-invasive diagnosis and treatment of drug-resistant focal epilepsy.\",\"PeriodicalId\":74246,\"journal\":{\"name\":\"Nature computational science\",\"volume\":\"5 9\",\"pages\":\"754-768\"},\"PeriodicalIF\":18.3000,\"publicationDate\":\"2025-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.nature.comhttps://www.nature.com/articles/s43588-025-00841-6.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature computational science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.nature.com/articles/s43588-025-00841-6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature computational science","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43588-025-00841-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Estimating the epileptogenic zone network (EZN) is an important part of the diagnosis of drug-resistant focal epilepsy and has a pivotal role in treatment and intervention. Virtual brain twins provide a modeling method for personalized diagnosis and treatment. They integrate patient-specific brain topography with structural connectivity from anatomical neuroimaging such as magnetic resonance imaging, and dynamic activity from functional recordings such as electroencephalography (EEG) and stereo-EEG (SEEG). Seizures show rich spatial and temporal features in functional recordings, which can be exploited to estimate the EZN. Stimulation-induced seizures can provide important and complementary information. Here we consider invasive SEEG stimulation and non-invasive temporal interference stimulation as a complementary approach. This paper offers a high-resolution virtual brain twin framework for EZN diagnosis based on stimulation-induced seizures. It provides an important methodological and conceptual basis to make the transition from invasive to non-invasive diagnosis and treatment of drug-resistant focal epilepsy. A high-resolution virtual brain twin approach is proposed using stimulation-induced seizures to estimate the epileptogenic network, offering a step toward non-invasive diagnosis and treatment of drug-resistant focal epilepsy.