Localizing targets for neuromodulation in drug-resistant epilepsy using intracranial EEG and computational model
Neuromodulation has emerged as a promising technique for the treatment of epilepsy. The target for neuromodulation is critical for the effectiveness of seizure control. About 30% of patients with drug-resistant epilepsy (DRE) fail to achieve seizure freedom after surgical intervention. It is difficu...
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Published in | Frontiers in physiology Vol. 13; p. 1015838 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Frontiers Media S.A
20.10.2022
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Subjects | |
Online Access | Get full text |
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Summary: | Neuromodulation has emerged as a promising technique for the treatment of epilepsy. The target for neuromodulation is critical for the effectiveness of seizure control. About 30% of patients with drug-resistant epilepsy (DRE) fail to achieve seizure freedom after surgical intervention. It is difficult to find effective brain targets for neuromodulation in these patients because brain regions are damaged during surgery. In this study, we propose a novel approach for localizing neuromodulatory targets, which uses intracranial EEG and multi-unit computational models to simulate the dynamic behavior of epileptic networks through external stimulation. First, we validate our method on a multivariate autoregressive model and compare nine different methods of constructing brain networks. Our results show that the directed transfer function with surrogate analysis achieves the best performance. Intracranial EEGs of 11 DRE patients are further analyzed. These patients all underwent surgery. In three seizure-free patients, the localized targets are concordant with the resected regions. For the eight patients without seizure-free outcome, the localized targets in three of them are outside the resected regions. Finally, we provide candidate targets for neuromodulation in these patients without seizure-free outcome based on virtual resected epileptic network. We demonstrate the ability of our approach to locate optimal targets for neuromodulation. We hope that our approach can provide a new tool for localizing patient-specific targets for neuromodulation therapy in DRE. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Rong Liu, Dalian University of Technology, China Reviewed by: Yangsong Zhang, Southwest University of Science and Technology, China Paulo Ricardo Protachevicz, University of São Paulo, Brazil This article was submitted to Computational Physiology and Medicine, a section of the journal Frontiers in Physiology |
ISSN: | 1664-042X 1664-042X |
DOI: | 10.3389/fphys.2022.1015838 |