{"title":"颞叶和颞叶外癫痫功能连通性的时间动态：基于脑磁图的研究","authors":"Suhas M.V;N. Mariyappa;Karunakar Kotegar;Ravindranadh Chowdary M;Raghavendra K;Ajay Asranna;Viswanathan L.G;Sanjib Sinha;Anitha H","doi":"10.1109/OJEMB.2025.3587954","DOIUrl":null,"url":null,"abstract":"<italic>Goal:</i> This study aims to explore the temporal dynamics of functional connectivity in drug-resistant focal epilepsy, focusing on Temporal Lobe Epilepsy (TLE) and Extra-Temporal Lobe Epilepsy (ETLE), using magnetoencephalography (MEG). <italic>Methods:</i> Temporal metrics such as Change Between States, Entropy of Transition Patterns, Entropy of Transition Probabilities, Dwell Time, Stability, and Max L1 Distance derived from dynamic functional connectivity matrices were analyzed across eight frequency bands (delta, theta, alpha, beta, low gamma, mid gamma, high gamma and broadband) in TLE and ETLE patients. <italic>Results:</i> Significant differences were observed between TLE and ETLE. ETLE exhibited more widespread and unpredictable connectivity transitions, while TLE demonstrated localized and structured patterns. Entropy metrics indicated higher randomness in ETLE, and dwell time analysis revealed shorter state persistence in ETLE compared to TLE. <italic>Conclusions:</i> The findings highlight the potential of MEG-based temporal connectivity metrics in characterizing network disruptions in focal epilepsy.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"6 ","pages":"507-514"},"PeriodicalIF":2.9000,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11077383","citationCount":"0","resultStr":"{\"title\":\"Temporal Dynamics of Functional Connectivity in Temporal and Extra-Temporal Lobe Epilepsy: A Magnetoencephalography-Based Study\",\"authors\":\"Suhas M.V;N. Mariyappa;Karunakar Kotegar;Ravindranadh Chowdary M;Raghavendra K;Ajay Asranna;Viswanathan L.G;Sanjib Sinha;Anitha H\",\"doi\":\"10.1109/OJEMB.2025.3587954\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<italic>Goal:</i> This study aims to explore the temporal dynamics of functional connectivity in drug-resistant focal epilepsy, focusing on Temporal Lobe Epilepsy (TLE) and Extra-Temporal Lobe Epilepsy (ETLE), using magnetoencephalography (MEG). <italic>Methods:</i> Temporal metrics such as Change Between States, Entropy of Transition Patterns, Entropy of Transition Probabilities, Dwell Time, Stability, and Max L1 Distance derived from dynamic functional connectivity matrices were analyzed across eight frequency bands (delta, theta, alpha, beta, low gamma, mid gamma, high gamma and broadband) in TLE and ETLE patients. <italic>Results:</i> Significant differences were observed between TLE and ETLE. ETLE exhibited more widespread and unpredictable connectivity transitions, while TLE demonstrated localized and structured patterns. Entropy metrics indicated higher randomness in ETLE, and dwell time analysis revealed shorter state persistence in ETLE compared to TLE. <italic>Conclusions:</i> The findings highlight the potential of MEG-based temporal connectivity metrics in characterizing network disruptions in focal epilepsy.\",\"PeriodicalId\":33825,\"journal\":{\"name\":\"IEEE Open Journal of Engineering in Medicine and Biology\",\"volume\":\"6 \",\"pages\":\"507-514\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11077383\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Open Journal of Engineering in Medicine and Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11077383/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of Engineering in Medicine and Biology","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11077383/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
Temporal Dynamics of Functional Connectivity in Temporal and Extra-Temporal Lobe Epilepsy: A Magnetoencephalography-Based Study
Goal: This study aims to explore the temporal dynamics of functional connectivity in drug-resistant focal epilepsy, focusing on Temporal Lobe Epilepsy (TLE) and Extra-Temporal Lobe Epilepsy (ETLE), using magnetoencephalography (MEG). Methods: Temporal metrics such as Change Between States, Entropy of Transition Patterns, Entropy of Transition Probabilities, Dwell Time, Stability, and Max L1 Distance derived from dynamic functional connectivity matrices were analyzed across eight frequency bands (delta, theta, alpha, beta, low gamma, mid gamma, high gamma and broadband) in TLE and ETLE patients. Results: Significant differences were observed between TLE and ETLE. ETLE exhibited more widespread and unpredictable connectivity transitions, while TLE demonstrated localized and structured patterns. Entropy metrics indicated higher randomness in ETLE, and dwell time analysis revealed shorter state persistence in ETLE compared to TLE. Conclusions: The findings highlight the potential of MEG-based temporal connectivity metrics in characterizing network disruptions in focal epilepsy.
期刊介绍：
The IEEE Open Journal of Engineering in Medicine and Biology (IEEE OJEMB) is dedicated to serving the community of innovators in medicine, technology, and the sciences, with the core goal of advancing the highest-quality interdisciplinary research between these disciplines. The journal firmly believes that the future of medicine depends on close collaboration between biology and technology, and that fostering interaction between these fields is an important way to advance key discoveries that can improve clinical care.IEEE OJEMB is a gold open access journal in which the authors retain the copyright to their papers and readers have free access to the full text and PDFs on the IEEE Xplore® Digital Library. However, authors are required to pay an article processing fee at the time their paper is accepted for publication, using to cover the cost of publication.
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