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MEG–EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy
The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the u...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4600479/ https://www.ncbi.nlm.nih.gov/pubmed/26016950 http://dx.doi.org/10.1007/s10548-015-0437-3 |
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author | Chowdhury, Rasheda Arman Zerouali, Younes Hedrich, Tanguy Heers, Marcel Kobayashi, Eliane Lina, Jean-Marc Grova, Christophe |
author_facet | Chowdhury, Rasheda Arman Zerouali, Younes Hedrich, Tanguy Heers, Marcel Kobayashi, Eliane Lina, Jean-Marc Grova, Christophe |
author_sort | Chowdhury, Rasheda Arman |
collection | PubMed |
description | The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG–MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10548-015-0437-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4600479 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-46004792015-10-16 MEG–EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy Chowdhury, Rasheda Arman Zerouali, Younes Hedrich, Tanguy Heers, Marcel Kobayashi, Eliane Lina, Jean-Marc Grova, Christophe Brain Topogr Original Paper The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG–MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10548-015-0437-3) contains supplementary material, which is available to authorized users. Springer US 2015-05-28 2015 /pmc/articles/PMC4600479/ /pubmed/26016950 http://dx.doi.org/10.1007/s10548-015-0437-3 Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Paper Chowdhury, Rasheda Arman Zerouali, Younes Hedrich, Tanguy Heers, Marcel Kobayashi, Eliane Lina, Jean-Marc Grova, Christophe MEG–EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy |
title | MEG–EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy |
title_full | MEG–EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy |
title_fullStr | MEG–EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy |
title_full_unstemmed | MEG–EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy |
title_short | MEG–EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy |
title_sort | meg–eeg information fusion and electromagnetic source imaging: from theory to clinical application in epilepsy |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4600479/ https://www.ncbi.nlm.nih.gov/pubmed/26016950 http://dx.doi.org/10.1007/s10548-015-0437-3 |
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