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Pigorini A, Avanzini P, Barborica A, Bénar CG, David O, Farisco M, Keller CJ, Manfridi A, Mikulan E, Paulk AC, Roehri N, Subramanian A, Vulliémoz S, Zelmann R. Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity. J Neurosci Methods 2024; 408:110160. [PMID: 38734149 DOI: 10.1016/j.jneumeth.2024.110160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 04/10/2024] [Accepted: 05/01/2024] [Indexed: 05/13/2024]
Abstract
Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.
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Affiliation(s)
- Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan, Italy; UOC Maxillo-facial Surgery and dentistry, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, Milan, Italy.
| | - Pietro Avanzini
- Institute of Neuroscience, Consiglio Nazionale delle Ricerche, Parma, Italy
| | | | - Christian-G Bénar
- Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Olivier David
- Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Michele Farisco
- Centre for Research Ethics and Bioethics, Department of Public Health and Caring Sciences, Uppsala University, P.O. Box 256, Uppsala, SE 751 05, Sweden; Science and Society Unit Biogem, Biology and Molecular Genetics Institute, Via Camporeale snc, Ariano Irpino, AV 83031, Italy
| | - Corey J Keller
- Department of Psychiatry & Behavioral Sciences, Stanford University Medical Center, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University Medical Center, Stanford, CA 94305, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA 94394, USA
| | - Alfredo Manfridi
- Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy
| | - Ezequiel Mikulan
- Department of Health Sciences, Università degli Studi di Milano, Milan, Italy
| | - Angelique C Paulk
- Department of Neurology and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicolas Roehri
- EEG and Epilepsy Unit, Dpt of Clinical Neurosciences, Geneva University Hospitals and University of Geneva, Switzerland
| | - Ajay Subramanian
- Department of Psychiatry & Behavioral Sciences, Stanford University Medical Center, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University Medical Center, Stanford, CA 94305, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA 94394, USA
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, Dpt of Clinical Neurosciences, Geneva University Hospitals and University of Geneva, Switzerland
| | - Rina Zelmann
- Department of Neurology and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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2
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Badier JM, Schwartz D, Bénar CG, Kanzari K, Daligault S, Romain R, Mitryukovskiy S, Fourcault W, Josselin V, Le Prado M, Jung J, Palacios-Laloy A, Romain C, Bartolomei F, Labyt E, Bonini F. Helium Optically Pumped Magnetometers Can Detect Epileptic Abnormalities as Well as SQUIDs as Shown by Intracerebral Recordings. eNeuro 2023; 10:ENEURO.0222-23.2023. [PMID: 37932045 PMCID: PMC10748329 DOI: 10.1523/eneuro.0222-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 09/22/2023] [Accepted: 09/26/2023] [Indexed: 11/08/2023] Open
Abstract
Magnetoencephalography based on superconducting quantum interference devices (SQUIDs) has been shown to improve the diagnosis and surgical treatment decision for presurgical evaluation of drug-resistant epilepsy. Still, its use remains limited because of several constraints such as cost, fixed helmet size, and the obligation of immobility. A new generation of sensors, optically pumped magnetometers (OPMs), could overcome these limitations. In this study, we validate the ability of helium-based OPM (4He-OPM) sensors to record epileptic brain activity thanks to simultaneous recordings with intracerebral EEG [stereotactic EEG (SEEG)]. We recorded simultaneous SQUIDs-SEEG and 4He-OPM-SEEG signals in one patient during two sessions. We show that epileptic activities on intracerebral EEG can be recorded by OPMs with a better signal-to noise ratio than classical SQUIDs. The OPM sensors open new venues for the widespread application of magnetoencephalography in the management of epilepsy and other neurologic diseases and fundamental neuroscience.
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Affiliation(s)
- Jean-Michel Badier
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
| | - Denis Schwartz
- MEG Departement, CERMEP-Imagerie du Vivant, Lyon 69003, France
| | - Christian-George Bénar
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
| | - Khoubeib Kanzari
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
| | | | - Rudy Romain
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
- MAG4Health, Grenoble 38000, France
| | - Sergey Mitryukovskiy
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
- MAG4Health, Grenoble 38000, France
| | - William Fourcault
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
| | - Vincent Josselin
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
| | - Matthieu Le Prado
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
- MAG4Health, Grenoble 38000, France
| | - Julien Jung
- Centre de Recherche en Neurosciences de Lyon, Unité Mixte de Recherche S1028, Centre National de la Recherche Scientifique, Hospices Civils de Lyon, Institut National de la Santé et de la Recherche Médicale, Université Lyon 1, Lyon 69002, France
| | - Augustin Palacios-Laloy
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
- MAG4Health, Grenoble 38000, France
| | - Carron Romain
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
- Department of Functional and Stereotactic Neurosurgery, Hôpital de la Timone, Assistance Publique-Hôpitaux de Marseille, Marseille 3005, France
| | - Fabrice Bartolomei
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
- Department of Epileptology and Cerebral Rythmology, Hôpital de la Timone, Assistance Publique-Hôpitaux de Marseille, Marseille 3005, France
| | - Etienne Labyt
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
- MAG4Health, Grenoble 38000, France
| | - Francesca Bonini
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
- MEG Departement, CERMEP-Imagerie du Vivant, Lyon 69003, France
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Desbordes T, Lakretz Y, Chanoine V, Oquab M, Badier JM, Trébuchon A, Carron R, Bénar CG, Dehaene S, King JR. Dimensionality and Ramping: Signatures of Sentence Integration in the Dynamics of Brains and Deep Language Models. J Neurosci 2023; 43:5350-5364. [PMID: 37217308 PMCID: PMC10359032 DOI: 10.1523/jneurosci.1163-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 02/07/2023] [Accepted: 02/19/2023] [Indexed: 05/24/2023] Open
Abstract
A sentence is more than the sum of its words: its meaning depends on how they combine with one another. The brain mechanisms underlying such semantic composition remain poorly understood. To shed light on the neural vector code underlying semantic composition, we introduce two hypotheses: (1) the intrinsic dimensionality of the space of neural representations should increase as a sentence unfolds, paralleling the growing complexity of its semantic representation; and (2) this progressive integration should be reflected in ramping and sentence-final signals. To test these predictions, we designed a dataset of closely matched normal and jabberwocky sentences (composed of meaningless pseudo words) and displayed them to deep language models and to 11 human participants (5 men and 6 women) monitored with simultaneous MEG and intracranial EEG. In both deep language models and electrophysiological data, we found that representational dimensionality was higher for meaningful sentences than jabberwocky. Furthermore, multivariate decoding of normal versus jabberwocky confirmed three dynamic patterns: (1) a phasic pattern following each word, peaking in temporal and parietal areas; (2) a ramping pattern, characteristic of bilateral inferior and middle frontal gyri; and (3) a sentence-final pattern in left superior frontal gyrus and right orbitofrontal cortex. These results provide a first glimpse into the neural geometry of semantic integration and constrain the search for a neural code of linguistic composition.SIGNIFICANCE STATEMENT Starting from general linguistic concepts, we make two sets of predictions in neural signals evoked by reading multiword sentences. First, the intrinsic dimensionality of the representation should grow with additional meaningful words. Second, the neural dynamics should exhibit signatures of encoding, maintaining, and resolving semantic composition. We successfully validated these hypotheses in deep neural language models, artificial neural networks trained on text and performing very well on many natural language processing tasks. Then, using a unique combination of MEG and intracranial electrodes, we recorded high-resolution brain data from human participants while they read a controlled set of sentences. Time-resolved dimensionality analysis showed increasing dimensionality with meaning, and multivariate decoding allowed us to isolate the three dynamical patterns we had hypothesized.
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Affiliation(s)
- Théo Desbordes
- Meta AI Research, Paris 75002, France; and Cognitive Neuroimaging Unit NeuroSpin center, 91191, Gif-sur-Yvette, France
| | - Yair Lakretz
- Cognitive Neuroimaging Unit NeuroSpin center, Gif-sur-Yvette, 91191, France
| | - Valérie Chanoine
- Institute of Language, Communication and the Brain, Aix-en-Provence, 13100, France; and Aix-Marseille Université, Centre National de la Recherche Scientifique, LPL, Aix-en-Provence, 13100, France
| | | | - Jean-Michel Badier
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, CNRS, LPL, Aix-en-Provence 13100; and Inst Neurosci Syst, Marseille, 13005, France
| | - Agnès Trébuchon
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, CNRS, LPL, Aix-en-Provence 13100, France; and Inst Neurosci Syst, Marseille, 13005, France; and Assistance Publique Hopitaux de Marseille, Timone hospital, Epileptology and Cerebral Rythmology, Marseille, 13385, France
| | - Romain Carron
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, CNRS, LPL, Aix-en-Provence 13100, France; and Inst Neurosci Syst, Marseille, 13005, France; and Assistance Publique Hopitaux de Marseille, Timone hospital, Functional and Stereotactic Neurosurgery, Marseille, 13385, France
| | - Christian-G Bénar
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, CNRS, LPL, Aix-en-Provence 13100, France; and Inst Neurosci Syst, Marseille, 13005, France
| | - Stanislas Dehaene
- Université Paris Saclay, Institut National de la Santé et de la Recherche Médicale, Commissariat à l'Energie Atomique, Cognitive Neuroimaging Unit, NeuroSpin center, Saclay, 91191, France; and Collège de France, PSL University, Paris, 75231, France
| | - Jean-Rémi King
- Meta AI Research, Paris 75002, France; and Cognitive Neuroimaging Unit NeuroSpin center, 91191, Gif-sur-Yvette, France
- LSP, École normale supérieure, PSL (Paris Sciences & Lettres) University, CNRS, 75005 Paris, France
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4
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Jawata A, Nicolás von E, Jean-Marc L, Giovanni P, Giorgio A, Zhengchen C, Tanguy H, Chifaou A, Hassan K, Birgit F, Jean G, Christophe G. Validating MEG source imaging of resting state oscillatory patterns with an intracranial EEG atlas. Neuroimage 2023; 274:120158. [PMID: 37149236 DOI: 10.1016/j.neuroimage.2023.120158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 03/27/2023] [Accepted: 05/04/2023] [Indexed: 05/08/2023] Open
Abstract
BACKGROUND Magnetoencephalography (MEG) is a widely used non-invasive tool to estimate brain activity with high temporal resolution. However, due to the ill-posed nature of the MEG source imaging (MSI) problem, the ability of MSI to identify accurately underlying brain sources along the cortical surface is still uncertain and requires validation. METHOD We validated the ability of MSI to estimate the background resting state activity of 45 healthy participants by comparing it to the intracranial EEG (iEEG) atlas (https://mni-open-ieegatlas. RESEARCH mcgill.ca/). First, we applied wavelet-based Maximum Entropy on the Mean (wMEM) as an MSI technique. Next, we converted MEG source maps into intracranial space by applying a forward model to the MEG-reconstructed source maps, and estimated virtual iEEG (ViEEG) potentials on each iEEG channel location; we finally quantitatively compared those with actual iEEG signals from the atlas for 38 regions of interest in the canonical frequency bands. RESULTS The MEG spectra were more accurately estimated in the lateral regions compared to the medial regions. The regions with higher amplitude in the ViEEG than in the iEEG were more accurately recovered. In the deep regions, MEG-estimated amplitudes were largely underestimated and the spectra were poorly recovered. Overall, our wMEM results were similar to those obtained with minimum norm or beamformer source localization. Moreover, the MEG largely overestimated oscillatory peaks in the alpha band, especially in the anterior and deep regions. This is possibly due to higher phase synchronization of alpha oscillations over extended regions, exceeding the spatial sensitivity of iEEG but detected by MEG. Importantly, we found that MEG-estimated spectra were more comparable to spectra from the iEEG atlas after the aperiodic components were removed. CONCLUSION This study identifies brain regions and frequencies for which MEG source analysis is likely to be reliable, a promising step towards resolving the uncertainty in recovering intracerebral activity from non-invasive MEG studies.
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Affiliation(s)
- Afnan Jawata
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, H3A 2B4, Canada; Integrated Program in Neuroscience, McGill University, Montréal, Québec H3A 1A1, Canada; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec H3A 2B4, Canada.
| | - Ellenrieder Nicolás von
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec H3A 2B4, Canada
| | - Lina Jean-Marc
- Centre De Recherches En Mathématiques, Montréal, Québec H3C 3J7, Canada; Electrical Engineering Department, École De Technologie Supérieure, Montréal, Québec H3C 1K3, Canada
| | - Pellegrino Giovanni
- Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
| | - Arcara Giorgio
- Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
| | - Cai Zhengchen
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec H3A 2B4, Canada
| | - Hedrich Tanguy
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, H3A 2B4, Canada
| | - Abdallah Chifaou
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, H3A 2B4, Canada
| | - Khajehpour Hassan
- Physics Department and PERFORM Centre, Concordia University, Montréal, Québec H4B 1R6, Canada
| | - Frauscher Birgit
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec H3A 2B4, Canada
| | - Gotman Jean
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec H3A 2B4, Canada
| | - Grova Christophe
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, H3A 2B4, Canada; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec H3A 2B4, Canada; Centre De Recherches En Mathématiques, Montréal, Québec H3C 3J7, Canada; Physics Department and PERFORM Centre, Concordia University, Montréal, Québec H4B 1R6, Canada.
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Frauscher B, Bénar CG, Engel JJ, Grova C, Jacobs J, Kahane P, Wiebe S, Zjilmans M, Dubeau F. Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy. Epilepsy Behav 2023; 143:109221. [PMID: 37119580 DOI: 10.1016/j.yebeh.2023.109221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 05/01/2023]
Abstract
Since the discovery of the human electroencephalogram (EEG), neurophysiology techniques have become indispensable tools in our armamentarium to localize epileptic seizures. New signal analysis techniques and the prospects of artificial intelligence and big data will offer unprecedented opportunities to further advance the field in the near future, ultimately resulting in improved quality of life for many patients with drug-resistant epilepsy. This article summarizes selected presentations from Day 1 of the two-day symposium "Neurophysiology, Neuropsychology, Epilepsy, 2022: Hills We Have Climbed and the Hills Ahead". Day 1 was dedicated to highlighting and honoring the work of Dr. Jean Gotman, a pioneer in EEG, intracranial EEG, simultaneous EEG/ functional magnetic resonance imaging, and signal analysis of epilepsy. The program focused on two main research directions of Dr. Gotman, and was dedicated to "High-frequency oscillations, a new biomarker of epilepsy" and "Probing the epileptic focus from inside and outside". All talks were presented by colleagues and former trainees of Dr. Gotman. The extended summaries provide an overview of historical and current work in the neurophysiology of epilepsy with emphasis on novel EEG biomarkers of epilepsy and source imaging and concluded with an outlook on the future of epilepsy research, and what is needed to bring the field to the next level.
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Affiliation(s)
- B Frauscher
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
| | - C G Bénar
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - J Jr Engel
- David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - C Grova
- Multimodal Functional Imaging Lab, PERFORM Centre, Department of Physics, Concordia University, Montreal, QC, Canada; Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, QC, Canada; Montreal Neurological Institute and Hospital, Neurology and Neurosurgery Department, McGill University, Montreal, QC, Canada
| | - J Jacobs
- Department of Pediatric and Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - P Kahane
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institute Neurosciences, Department of Neurology, 38000 Grenoble, France
| | - S Wiebe
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - M Zjilmans
- Stichting Epilepsie Instellingen Nederland, The Netherlands; Brain Center, University Medical Center Utrecht, The Netherlands
| | - F Dubeau
- Montreal Neurological Institute and Hospital, Neurology and Neurosurgery Department, McGill University, Montreal, QC, Canada
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Coelli S, Medina Villalon S, Bonini F, Velmurugan J, López-Madrona VJ, Carron R, Bartolomei F, Badier JM, Bénar CG. Comparison of beamformer and ICA for dynamic connectivity analysis: A simultaneous MEG-SEEG study. Neuroimage 2023; 265:119806. [PMID: 36513288 DOI: 10.1016/j.neuroimage.2022.119806] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/25/2022] [Accepted: 12/09/2022] [Indexed: 12/14/2022] Open
Abstract
Magnetoencephalography (MEG) is a powerful tool for estimating brain connectivity with both good spatial and temporal resolution. It is particularly helpful in epilepsy to characterize non-invasively the epileptic networks. However, using MEG to map brain networks requires solving a difficult inverse problem that introduces uncertainty in the activity localization and connectivity measures. Our goal here was to compare independent component analysis (ICA) followed by dipole source localization and the linearly constrained minimum-variance beamformer (LCMV-BF) for characterizing regions with interictal epileptic activity and their dynamic connectivity. After a simulation study, we compared ICA and LCMV-BF results with intracerebral EEG (stereotaxic EEG, SEEG) recorded simultaneously in 8 epileptic patients, which provide a unique 'ground truth' to which non-invasive results can be confronted. We compared the signal time courses extracted applying ICA and LCMV-BF on MEG data to that of SEEG, both for the actual signals and the dynamic connectivity computed using cross-correlation (evolution of links in time). With our simulations, we illustrated the different effect of the temporal and spatial correlation among sources on the two methods. While ICA was more affected by the temporal correlation but robust against spatial configurations, LCMV-BF showed opposite behavior. Moreover, ICA seems more suited to retrieve the simulated networks. In case of real patient data, good MEG/SEEG correlation and good localization were obtained in 6 out of 8 patients. In 4 of them ICA had the best performance (higher correlation, lower localization distance). In terms of dynamic connectivity, the evolution in time of the cross-correlation links could be retrieved in 5 patients out of 6, however, with more variable results in terms of correlation and distance. In two patients LCMV-BF had better results than ICA. In one patient the two methods showed equally good outcomes, and in the remaining two patients ICA performed best. In conclusion, our results obtained by exploiting simultaneous MEG/SEEG recordings suggest that ICA and LCMV-BF have complementary qualities for retrieving the dynamics of interictal sources and their network interactions.
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Affiliation(s)
- Stefania Coelli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy
| | - Samuel Medina Villalon
- Aix Marseille University, INSERM, INS, Inst Neurosci Syst, Marseille, France; APHM, Timone Hospital, Epileptology and Cerebral Rythmology, Marseille, France
| | - Francesca Bonini
- Aix Marseille University, INSERM, INS, Inst Neurosci Syst, Marseille, France; APHM, Timone Hospital, Epileptology and Cerebral Rythmology, Marseille, France
| | - Jayabal Velmurugan
- Aix Marseille University, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | | | - Romain Carron
- Aix Marseille University, INSERM, INS, Inst Neurosci Syst, Marseille, France; APHM, Timone Hospital, Functional and Stereotactic Neurosurgery, Marseille, France
| | - Fabrice Bartolomei
- Aix Marseille University, INSERM, INS, Inst Neurosci Syst, Marseille, France; APHM, Timone Hospital, Epileptology and Cerebral Rythmology, Marseille, France
| | - Jean-Michel Badier
- Aix Marseille University, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Christian-G Bénar
- Aix Marseille University, INSERM, INS, Inst Neurosci Syst, Marseille, France.
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7
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Velmurugan J, Badier JM, Pizzo F, Medina Villalon S, Papageorgakis C, López-Madrona V, Jegou A, Carron R, Bartolomei F, Bénar CG. Virtual MEG sensors based on beamformer and independent component analysis can reconstruct epileptic activity as measured on simultaneous intracerebral recordings. Neuroimage 2022; 264:119681. [PMID: 36270623 DOI: 10.1016/j.neuroimage.2022.119681] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 09/30/2022] [Accepted: 10/10/2022] [Indexed: 11/09/2022] Open
Abstract
The prevailing gold standard for presurgical determination of epileptogenic brain networks is intracerebral EEG, a potent yet invasive approach. Magnetoencephalography (MEG) is a state-of-the art non-invasive method for investigating epileptiform discharges. However, it is not clear at what level the precision offered by MEG can reach that of SEEG. Here, we present a strategy for non-invasively retrieving the constituents of the interictal network, with high spatial and temporal precision. Our method is based on MEG and a combination of spatial filtering and independent component analysis (ICA). We validated this approach in twelve patients with drug-resistant focal epilepsy, thanks to the unprecedented ground truth provided by simultaneous recordings of MEG and SEEG. A minimum variance adaptive beamformer estimated the source time series and ICA was used to further decompose these time series into network constituents (MEG-ICs), each having a time series (virtual electrode) and a topography (spatial distribution of amplitudes in the brain). We show that MEG has a considerable sensitivity of 0.80 and 0.84 and a specificity of 0.93 and 0.91 for reconstructing deep and superficial sources, respectively, when compared to the ground truth (SEEG). For each epileptic MEG-IC (n = 131), we found at least one significantly correlating SEEG contact close to zero lag after correcting for multiple comparisons. All the patients except one had at least one epileptic component that was highly correlated (Spearman rho>0.3) with that of SEEG traces. MEG-ICs correlated well with SEEG traces. The strength of correlation coefficients did not depend on the depth of the SEEG contacts or the clinical outcome of the patient. A significant proportion of the MEG-ICs (n = 83/131) were localized in proximity with their maximally correlating SEEG, within a mean distance of 20±12.18mm. Our research is the first to validate the MEG-retrieved beamformer IC sources against SEEG-derived ground truth in a simultaneous MEG-SEEG framework. Observations from the present study suggest that non-invasive MEG source components may potentially provide additional information, comparable to SEEG in a number of instances.
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Affiliation(s)
- Jayabal Velmurugan
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France
| | - Jean-Michel Badier
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France
| | - Francesca Pizzo
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, F-13005, France
| | - Samuel Medina Villalon
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, F-13005, France
| | | | | | - Aude Jegou
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France
| | - Romain Carron
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Functional and Stereotactic Neurosurgery, Marseille, F-13005, France
| | - Fabrice Bartolomei
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, F-13005, France
| | - Christian-G Bénar
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France.
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8
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López-Madrona VJ, Medina Villalon S, Badier JM, Trébuchon A, Jayabal V, Bartolomei F, Carron R, Barborica A, Vulliémoz S, Alario FX, Bénar CG. Magnetoencephalography can reveal deep brain network activities linked to memory processes. Hum Brain Mapp 2022; 43:4733-4749. [PMID: 35766240 PMCID: PMC9491290 DOI: 10.1002/hbm.25987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 05/04/2022] [Accepted: 05/18/2022] [Indexed: 11/14/2022] Open
Abstract
Recording from deep neural structures such as hippocampus noninvasively and yet with high temporal resolution remains a major challenge for human neuroscience. Although it has been proposed that deep neuronal activity might be recordable during cognitive tasks using magnetoencephalography (MEG), this remains to be demonstrated as the contribution of deep structures to MEG recordings may be too small to be detected or might be eclipsed by the activity of large‐scale neocortical networks. In the present study, we disentangled mesial activity and large‐scale networks from the MEG signals thanks to blind source separation (BSS). We then validated the MEG BSS components using intracerebral EEG signals recorded simultaneously in patients during their presurgical evaluation of epilepsy. In the MEG signals obtained during a memory task involving the recognition of old and new images, we identified with BSS a putative mesial component, which was present in all patients and all control subjects. The time course of the component selectively correlated with stereo‐electroencephalography signals recorded from hippocampus and rhinal cortex, thus confirming its mesial origin. This finding complements previous studies with epileptic activity and opens new possibilities for using MEG to study deep brain structures in cognition and in brain disorders.
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Affiliation(s)
| | - Samuel Medina Villalon
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France.,APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
| | | | - Agnès Trébuchon
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France.,APHM, Timone Hospital, Functional and Stereotactic Neurosurgery, Marseille, France
| | | | - Fabrice Bartolomei
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France.,APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
| | - Romain Carron
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France.,APHM, Timone Hospital, Functional and Stereotactic Neurosurgery, Marseille, France
| | | | - Serge Vulliémoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine Geneva, Geneva, Switzerland
| | | | - Christian G Bénar
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
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9
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Parmigiani S, Mikulan EP, Russo S, Sarasso S, Zauli FM, Rubino A, Cattani A, Fecchio M, Giampiccolo D, Lanzone J, D'Orio P, Del Vecchio M, Avanzini P, Nobili L, Sartori I, Massimini M, Pigorini A. Simultaneous stereo-EEG and high-density scalp EEG recordings to study the effects of intracerebral stimulation parameters. Brain Stimul 2022; 15:664-675. [PMID: 35421585 DOI: 10.1016/j.brs.2022.04.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 04/06/2022] [Accepted: 04/06/2022] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Cortico-cortical evoked potentials (CCEPs) recorded by stereo-electroencephalography (SEEG) are a valuable tool to investigate brain reactivity and effective connectivity. However, invasive recordings are spatially sparse since they depend on clinical needs. This sparsity hampers systematic comparisons across-subjects, the detection of the whole-brain effects of intracortical stimulation, as well as their relationships to the EEG responses evoked by non-invasive stimuli. OBJECTIVE To demonstrate that CCEPs recorded by high-density electroencephalography (hd-EEG) provide additional information with respect SEEG alone and to provide an open, curated dataset to allow for further exploration of their potential. METHODS The dataset encompasses SEEG and hd-EEG recordings simultaneously acquired during Single Pulse Electrical Stimulation (SPES) in drug-resistant epileptic patients (N = 36) in whom stimulations were delivered with different physical, geometrical, and topological parameters. Differences in CCEPs were assessed by amplitude, latency, and spectral measures. RESULTS While invasively and non-invasively recorded CCEPs were generally correlated, differences in pulse duration, angle and stimulated cortical area were better captured by hd-EEG. Further, intracranial stimulation evoked site-specific hd-EEG responses that reproduced the spectral features of EEG responses to transcranial magnetic stimulation (TMS). Notably, SPES, albeit unperceived by subjects, elicited scalp responses that were up to one order of magnitude larger than the responses typically evoked by sensory stimulation in awake humans. CONCLUSIONS CCEPs can be simultaneously recorded with SEEG and hd-EEG and the latter provides a reliable descriptor of the effects of SPES as well as a common reference to compare the whole-brain effects of intracortical stimulation to those of non-invasive transcranial or sensory stimulations in humans.
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Affiliation(s)
- S Parmigiani
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy
| | - E P Mikulan
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy
| | - S Russo
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy; Department of Philosophy "Piero Martinetti", Università degli Studi di Milano, Milan, Italy
| | - S Sarasso
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy
| | - F M Zauli
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy; Department of Philosophy "Piero Martinetti", Università degli Studi di Milano, Milan, Italy
| | - A Rubino
- "C. Munari" Epilepsy Surgery Centre, Department of Neuroscience, Niguarda Hospital, Milan, Italy
| | - A Cattani
- Department of Mathematics & Statistics, Boston University, Boston, MA, USA
| | - M Fecchio
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - D Giampiccolo
- Department of Neurosurgery, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK; Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, UK; Institute of Neurosciences, Cleveland Clinic London, London, UK
| | - J Lanzone
- Department of Systems Medicine, Neuroscience, University of Rome Tor Vergata, Rome, Italy; Istituti Clinici Scientifici Maugeri, IRCCS, Neurorehabilitation Department of Milano Institute, Milan, Italy
| | - P D'Orio
- "C. Munari" Epilepsy Surgery Centre, Department of Neuroscience, Niguarda Hospital, Milan, Italy; Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, Parma, Italy
| | - M Del Vecchio
- Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, Parma, Italy
| | - P Avanzini
- Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche, Parma, Italy
| | - L Nobili
- Child Neuropsychiatry, IRCCS Istituto G. Gaslini, Genova, Italy
| | - I Sartori
- "C. Munari" Epilepsy Surgery Centre, Department of Neuroscience, Niguarda Hospital, Milan, Italy
| | - M Massimini
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy; Istituto Di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan, Italy; Azrieli Program in Brain, Mind and Consciousness, Canadian Institute for Advanced Research, Toronto, Canada
| | - A Pigorini
- Department of Biomedical and Clinical Sciences "L. Sacco" Università degli Studi di Milano, Milan, Italy; Department of Biomedical, V, Università degli Studi di Milano, Milan, Italy.
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10
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Xu N, Shan W, Qi J, Wu J, Wang Q. Presurgical Evaluation of Epilepsy Using Resting-State MEG Functional Connectivity. Front Hum Neurosci 2021; 15:649074. [PMID: 34276321 PMCID: PMC8283278 DOI: 10.3389/fnhum.2021.649074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Accepted: 06/07/2021] [Indexed: 11/21/2022] Open
Abstract
Epilepsy is caused by abnormal electrical discharges (clinically identified by electrophysiological recording) in a specific part of the brain [originating in only one part of the brain, namely, the epileptogenic zone (EZ)]. Epilepsy is now defined as an archetypical hyperexcited neural network disorder. It can be investigated through the network analysis of interictal discharges, ictal discharges, and resting-state functional connectivity. Currently, there is an increasing interest in embedding resting-state connectivity analysis into the preoperative evaluation of epilepsy. Among the various neuroimaging technologies employed to achieve brain functional networks, magnetoencephalography (MEG) with the excellent temporal resolution is an ideal tool for estimating the resting-state connectivity between brain regions, which can reveal network abnormalities in epilepsy. What value does MEG resting-state functional connectivity offer for epileptic presurgical evaluation? Regarding this topic, this paper introduced the origin of MEG and the workflow of constructing source-space functional connectivity based on MEG signals. Resting-state functional connectivity abnormalities correlate with epileptogenic networks, which are defined by the brain regions involved in the production and propagation of epileptic activities. This paper reviewed the evidence of altered epileptic connectivity based on low- or high-frequency oscillations (HFOs) and the evidence of the advantage of using simultaneous MEG and intracranial electroencephalography (iEEG) recordings. More importantly, this review highlighted that MEG-based resting-state functional connectivity has the potential to predict postsurgical outcomes. In conclusion, resting-state MEG functional connectivity has made a substantial progress toward serving as a candidate biomarker included in epileptic presurgical evaluations.
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Affiliation(s)
- Na Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wei Shan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jing Qi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianping Wu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
- Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neuromodulation, Beijing, China
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11
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Zhang S, Cao C, Quinn A, Vivekananda U, Zhan S, Liu W, Sun B, Woolrich M, Lu Q, Litvak V. Dynamic analysis on simultaneous iEEG-MEG data via hidden Markov model. Neuroimage 2021; 233:117923. [PMID: 33662572 PMCID: PMC8204269 DOI: 10.1016/j.neuroimage.2021.117923] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 02/17/2021] [Accepted: 02/24/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Intracranial electroencephalography (iEEG) recordings are used for clinical evaluation prior to surgical resection of the focus of epileptic seizures and also provide a window into normal brain function. A major difficulty with interpreting iEEG results at the group level is inconsistent placement of electrodes between subjects making it difficult to select contacts that correspond to the same functional areas. Recent work using time delay embedded hidden Markov model (HMM) applied to magnetoencephalography (MEG) resting data revealed a distinct set of brain states with each state engaging a specific set of cortical regions. Here we use a rare group dataset with simultaneously acquired resting iEEG and MEG to test whether there is correspondence between HMM states and iEEG power changes that would allow classifying iEEG contacts into functional clusters. METHODS Simultaneous MEG-iEEG recordings were performed at rest on 11 patients with epilepsy whose intracranial electrodes were implanted for pre-surgical evaluation. Pre-processed MEG sensor data was projected to source space. Time delay embedded HMM was then applied to MEG time series. At the same time, iEEG time series were analyzed with time-frequency decomposition to obtain spectral power changes with time. To relate MEG and iEEG results, correlations were computed between HMM probability time courses of state activation and iEEG power time course from the mid contact pair for each electrode in equally spaced frequency bins and presented as correlation spectra for the respective states and iEEG channels. Association of iEEG electrodes with HMM states based on significant correlations was compared to that based on the distance to peaks in subject-specific state topographies. RESULTS Five HMM states were inferred from MEG. Two of them corresponded to the left and the right temporal activations and had a spectral signature primarily in the theta/alpha frequency band. All the electrodes had significant correlations with at least one of the states (p < 0.05 uncorrected) and for 27/50 electrodes these survived within-subject FDR correction (q < 0.05). These correlations peaked in the theta/alpha band. There was a highly significant dependence between the association of states and electrodes based on functional correlations and that based on spatial proximity (p = 5.6e-6,χ2 test for independence). Despite the potentially atypical functional anatomy and physiological abnormalities related to epilepsy, HMM model estimated from the patient group was very similar to that estimated from healthy subjects. CONCLUSION Epilepsy does not preclude HMM analysis of interictal data. The resulting group functional states are highly similar to those reported for healthy controls. Power changes recorded with iEEG correlate with HMM state time courses in the alpha-theta band and the presence of this correlation can be related to the spatial location of electrode contacts close to the individual peaks of the corresponding state topographies. Thus, the hypothesized relation between iEEG contacts and HMM states exists and HMM could be further explored as a method for identifying comparable iEEG channels across subjects for the purposes of group analysis.
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Affiliation(s)
- Siqi Zhang
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, China; Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, 12 Queen Square, London WC1N 3BG, UK
| | - Chunyan Cao
- Department of Neurosurgery, affiliated Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Andrew Quinn
- Oxford Centre for Human Brain Activity, University of Oxford, Warneford Hospital, Oxford, UK
| | - Umesh Vivekananda
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, 12 Queen Square, London WC1N 3BG, UK; National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - Shikun Zhan
- Department of Neurosurgery, affiliated Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wei Liu
- Department of Neurosurgery, affiliated Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bomin Sun
- Department of Neurosurgery, affiliated Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mark Woolrich
- Oxford Centre for Human Brain Activity, University of Oxford, Warneford Hospital, Oxford, UK
| | - Qing Lu
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, China.
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, 12 Queen Square, London WC1N 3BG, UK.
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12
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Bénar CG, Velmurugan J, López-Madrona VJ, Pizzo F, Badier JM. Detection and localization of deep sources in magnetoencephalography: A review. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2021. [DOI: 10.1016/j.cobme.2021.100285] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
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13
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Vivekananda U, Cao C, Liu W, Zhang J, Rugg-Gunn F, Walker MC, Litvak V, Sun B, Zhan S. The use of simultaneous stereo-electroencephalography and magnetoencephalography in localizing the epileptogenic focus in refractory focal epilepsy. Brain Commun 2021; 3:fcab072. [PMID: 33977268 PMCID: PMC8099997 DOI: 10.1093/braincomms/fcab072] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/27/2021] [Indexed: 11/12/2022] Open
Abstract
Both magnetoencephalography and stereo-electroencephalography are used in presurgical epilepsy assessment, with contrasting advantages and limitations. It is not known whether simultaneous stereo-electroencephalography-magnetoencephalography recording confers an advantage over both individual modalities, in particular whether magnetoencephalography can provide spatial context to epileptiform activity seen on stereo-electroencephalography. Twenty-four adult and paediatric patients who underwent stereo-electroencephalography study for pre-surgical evaluation of drug-resistant focal epilepsy, were recorded using simultaneous stereo-electroencephalography-magnetoencephalography, of which 14 had abnormal interictal activity during recording. The 14 patients were divided into two groups; those with detected superficial (n = 7) and deep (n = 7) brain interictal activity. Interictal spikes were independently identified in stereo-electroencephalography and magnetoencephalography. Magnetoencephalography dipoles were derived using a distributed inverse method. There was no significant difference between stereo-electroencephalography and magnetoencephalography in detecting superficial spikes (P = 0.135) and stereo-electroencephalography was significantly better at detecting deep spikes (P = 0.002). Mean distance across patients between stereo-electroencephalography channel with highest average spike amplitude and magnetoencephalography dipole was 20.7 ± 4.4 mm. for superficial sources, and 17.8 ± 3.7 mm. for deep sources, even though for some of the latter (n = 4) no magnetoencephalography spikes were detected and magnetoencephalography dipole was fitted to a stereo-electroencephalography interictal activity triggered average. Removal of magnetoencephalography dipole was associated with 1 year seizure freedom in 6/7 patients with superficial source, and 5/6 patients with deep source. Although stereo-electroencephalography has greater sensitivity in identifying interictal activity from deeper sources, a magnetoencephalography source can be localized using stereo-electroencephalography information, thereby providing useful whole brain context to stereo-electroencephalography and potential role in epilepsy surgery planning.
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Affiliation(s)
- Umesh Vivekananda
- Department of Clinical and Experimental Epilepsy, UCL, Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Chunyan Cao
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China.,Wellcome Centre for Human Neuroimaging, UCL, Queen Square, London WC1N 3AR, UK
| | - Wei Liu
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Jing Zhang
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Fergus Rugg-Gunn
- Department of Clinical and Experimental Epilepsy, UCL, Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Matthew C Walker
- Department of Clinical and Experimental Epilepsy, UCL, Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, UCL, Queen Square, London WC1N 3AR, UK
| | - Bomin Sun
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Shikun Zhan
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
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14
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Neal EG, Schoenberg MR, Maciver S, Bezchlibnyk YB, Vale FL. Seizure Freedom After Epilepsy Surgery and Higher Baseline Cognition May Be Associated With a Negatively Correlated Epilepsy Network in Temporal Lobe Epilepsy. Front Neurosci 2021; 14:629667. [PMID: 33584184 PMCID: PMC7874020 DOI: 10.3389/fnins.2020.629667] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Accepted: 12/28/2020] [Indexed: 11/13/2022] Open
Abstract
Background: Brain regions positively correlated with the epileptogenic zone in patients with temporal lobe epilepsy vary in spread across the brain and in the degree of correlation to the temporal lobes, thalamus, and limbic structures, and these parameters have been associated with pre-operative cognitive impairment and seizure freedom after epilepsy surgery, but negatively correlated regions have not been as well studied. We hypothesize that connectivity within a negatively correlated epilepsy network may predict which patients with temporal lobe epilepsy will respond best to surgery. Methods: Scalp EEG and resting state functional MRI (rsfMRI) were collected from 19 patients with temporal lobe epilepsy and used to estimate the irritative zone. Using patients' rsfMRI, the negatively correlated epilepsy network was mapped by determining all the brain voxels that were negatively correlated with the voxels in the epileptogenic zone and the spread and average connectivity within the network was determined. Results: Pre-operatively, connectivity within the negatively correlated network was inversely related to the spread (diffuseness) of that network and positively associated with higher baseline verbal and logical memory. Pre-operative connectivity within the negatively correlated network was also significantly higher in patients who would go on to be seizure free. Conclusion: Patients with higher connectivity within brain regions negatively correlated with the epilepsy network had higher baseline memory function, narrower network spread, and were more likely to be seizure free after surgery.
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Affiliation(s)
- Elliot G Neal
- Department of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL, United States
| | - Mike R Schoenberg
- Department of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL, United States.,Department of Neurology, University of South Florida, Tampa, FL, United States
| | - Stephanie Maciver
- Department of Neurology, University of South Florida, Tampa, FL, United States
| | - Yarema B Bezchlibnyk
- Department of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL, United States
| | - Fernando L Vale
- Department of Neurosurgery, Medical College of Georgia, Augusta University, Augusta, GA, United States
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15
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Abstract
Concise history of fascinating magnetoencephalography (MEG) technology and catalog of very selected milestone preclinical and clinical MEG studies are provided as the background. The focus is the societal context defining a journey of MEG to and through clinical practice and formation of the American Clinical MEG Society (ACMEGS). We aspired to provide an objective historic perspective and document contributions of many professionals while focusing on the role of ACMEGS in the growth and maturation of clinical MEG field. The ACMEGS was born (2006) out of inevitability to address two vital issues-fair reimbursement and proper clinical acceptance. A beacon of accountable MEG practice and utilization is now an expanding professional organization with the highest level of competence in practice of clinical MEG and clinical credibility. The ACMEGS facilitated a favorable disposition of insurances toward MEG in the United States by combining the national replication of the grassroots efforts and teaming up with the strategic partners-particularly the American Academy of Neurology (AAN), published two Position Statements (2009 and 2017), the world's only set of MEG Clinical Practice Guidelines (CPGs; 2011) and surveys of clinical MEG practice (2011 and 2020) and use (2020). In addition to the annual ACMEGS Course (2012), we directly engaged MEG practitioners through an Invitational Summit (2019). The Society remains focused on the improvements and expansion of clinical practice, education, clinical training, and constructive engagement of vendors in these issues and pivotal studies toward additional MEG indications. The ACMEGS not only had the critical role in the progress of Clinical MEG in the United States and beyond since 2006 but positioned itself as the field leader in the future.
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16
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Redefining the role of Magnetoencephalography in refractory epilepsy. Seizure 2020; 83:70-75. [PMID: 33096459 DOI: 10.1016/j.seizure.2020.10.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 10/10/2020] [Indexed: 11/23/2022] Open
Abstract
Magnetoencephalography (MEG) possesses a number of features, including excellent spatiotemporal resolution, that lend itself to the functional imaging of epileptic activity. However its current use is restricted to specific scenarios, namely in the diagnosis refractory focal epilepsies where electroencephalography (EEG) has been inconclusive. This review highlights the recent progress of MEG within epilepsy, including advances in the technique itself such as simultaneous EEG/MEG and intracranial EEG/MEG recording and room temperature MEG recording using optically pumped magnetometers, as well as improved post processing of the data during interictal and ictal activity for accurate source localisation of the epileptogenic focus. These advances should broaden the scope of MEG as an important part of epilepsy diagnostics in the future.
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17
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Bartolomei F, Lagarde S, Scavarda D, Carron R, Bénar C, Picard F. The role of the dorsal anterior insula in ecstatic sensation revealed by direct electrical brain stimulation. Brain Stimul 2019; 12:1121-1126. [DOI: 10.1016/j.brs.2019.06.005] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2019] [Revised: 05/13/2019] [Accepted: 06/03/2019] [Indexed: 12/12/2022] Open
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18
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Liu W, Tian S, Zhang J, Huang P, Wang T, Deng Y, Liu X, Miao F, Sun B, Zhan S. Utility of stereo-electroencephalography recording guided by magnetoencephalography in the surgical treatment of epilepsy patients with negative magnetic resonance imaging results. Int J Neurosci 2019; 129:1045-1052. [PMID: 31215295 DOI: 10.1080/00207454.2019.1634066] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Objective: It is challenging for neurosurgeons to perform surgeries on patients without detectable structural lesions. Therefore, this retrospective study aimed to explore the outcome of stereo-electroencephalography (SEEG) in suspicious areas guided by magnetoencephalography (MEG)-magnetic resonance imaging (MRI) reconstruction in MRI-negative epilepsy patients. Methods: This study included 47 patients with negative-MRI epilepsy. Seizure outcome at 24 months was assessed using a modified Engel's classification. Accordingly, class I and II were considered favorable outcomes, whereas classes III and IV were unfavorable. Furthermore, patients were classified into a consistent group if the results of MEG and SEEG indicated the same area of the brain. The relationship between surgical outcome and the concordance of MEG and SEEG was analyzed. Results: A complete seizure-free condition was achieved in 22 (47%) patients. Sex, handedness, age and duration of illness were not significantly associated with seizure-free outcome (p = .187 [Pearson chi-squared test]). The number of patients with favorable outcome (Engle I and II) was as high as 68% at the time of follow-up. Furthermore, more seizure-free patients were found in the SEEG and MEG consistent group. Conclusions: SEEG is a valuable tool in the pre-evaluation for resective epilepsy surgery, particularly in negative-MRI epilepsy patients; MEG greatly facilitates localization for SEEG electrode implantation. However, none of these tools are absolutely sensitive and reliable; therefore, collecting as much information as possible is necessary to achieve satisfactory results in epilepsy surgery.
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Affiliation(s)
- Wei Liu
- Department of Stereotactic and Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
| | - Shuaiwei Tian
- Department of Neurosurgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
| | - Jing Zhang
- Department of Stereotactic and Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
| | - Peng Huang
- Department of Stereotactic and Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
| | - Tao Wang
- Department of Stereotactic and Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
| | - Yulei Deng
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
| | - Xiaoying Liu
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
| | - Fei Miao
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
| | - Bomin Sun
- Department of Stereotactic and Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
| | - Shikun Zhan
- Department of Stereotactic and Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , China
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19
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Abstract
[Box: see text].
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20
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Intracerebral Sources Reconstructed on the Basis of High-Resolution Scalp EEG and MEG. Brain Topogr 2019; 32:523-526. [PMID: 31129753 DOI: 10.1007/s10548-019-00717-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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21
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He B, Astolfi L, Valdés-Sosa PA, Marinazzo D, Palva SO, Bénar CG, Michel CM, Koenig T. Electrophysiological Brain Connectivity: Theory and Implementation. IEEE Trans Biomed Eng 2019; 66:10.1109/TBME.2019.2913928. [PMID: 31071012 PMCID: PMC6834897 DOI: 10.1109/tbme.2019.2913928] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
We review the theory and algorithms of electrophysiological brain connectivity analysis. This tutorial is aimed at providing an introduction to brain functional connectivity from electrophysiological signals, including electroencephalography (EEG), magnetoencephalography (MEG), electrocorticography (ECoG), stereoelectroencephalography (SEEG). Various connectivity estimators are discussed, and algorithms introduced. Important issues for estimating and mapping brain functional connectivity with electrophysiology are discussed.
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Affiliation(s)
- Bin He
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, USA
| | - Laura Astolfi
- Department of Computer, Control and Management Engineering, University of Rome Sapienza, and with IRCCS Fondazione Santa Lucia, Rome, Italy
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22
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Pizzo F, Roehri N, Medina Villalon S, Trébuchon A, Chen S, Lagarde S, Carron R, Gavaret M, Giusiano B, McGonigal A, Bartolomei F, Badier JM, Bénar CG. Deep brain activities can be detected with magnetoencephalography. Nat Commun 2019; 10:971. [PMID: 30814498 PMCID: PMC6393515 DOI: 10.1038/s41467-019-08665-5] [Citation(s) in RCA: 103] [Impact Index Per Article: 20.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Accepted: 01/12/2019] [Indexed: 12/22/2022] Open
Abstract
The hippocampus and amygdala are key brain structures of the medial temporal lobe, involved in cognitive and emotional processes as well as pathological states such as epilepsy. Despite their importance, it is still unclear whether their neural activity can be recorded non-invasively. Here, using simultaneous intracerebral and magnetoencephalography (MEG) recordings in patients with focal drug-resistant epilepsy, we demonstrate a direct contribution of amygdala and hippocampal activity to surface MEG recordings. In particular, a method of blind source separation, independent component analysis, enabled activity arising from large neocortical networks to be disentangled from that of deeper structures, whose amplitude at the surface was small but significant. This finding is highly relevant for our understanding of hippocampal and amygdala brain activity as it implies that their activity could potentially be measured non-invasively.
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Affiliation(s)
- F Pizzo
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France.
- APHM, Timone Hospital, Epileptology and cerebral rhythmology, Marseille, 13005, France.
| | - N Roehri
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France
| | - S Medina Villalon
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France
- APHM, Timone Hospital, Epileptology and cerebral rhythmology, Marseille, 13005, France
| | - A Trébuchon
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France
- APHM, Timone Hospital, Epileptology and cerebral rhythmology, Marseille, 13005, France
| | - S Chen
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France
| | - S Lagarde
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France
- APHM, Timone Hospital, Epileptology and cerebral rhythmology, Marseille, 13005, France
| | - R Carron
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France
- APHM, Timone Hospital, Functional and Stereotactic Neurosurgery, Marseille, 13005, France
| | - M Gavaret
- INSERM UMR894, Paris Descartes university, GHU Paris Psychiatrie Neurosciences, 75013, Paris, France
| | - B Giusiano
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France
| | - A McGonigal
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France
- APHM, Timone Hospital, Epileptology and cerebral rhythmology, Marseille, 13005, France
| | - F Bartolomei
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France
- APHM, Timone Hospital, Epileptology and cerebral rhythmology, Marseille, 13005, France
| | - J M Badier
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France
| | - C G Bénar
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, 13005, France.
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Auditory Functional Mapping. Validation by simultaneous depth and MEG recordings. Neurophysiol Clin 2018. [DOI: 10.1016/j.neucli.2018.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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24
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Juárez-Martinez EL, Nissen IA, Idema S, Velis DN, Hillebrand A, Stam CJ, van Straaten ECW. Virtual localization of the seizure onset zone: Using non-invasive MEG virtual electrodes at stereo-EEG electrode locations in refractory epilepsy patients. Neuroimage Clin 2018; 19:758-766. [PMID: 30009129 PMCID: PMC6041424 DOI: 10.1016/j.nicl.2018.06.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Revised: 05/22/2018] [Accepted: 06/01/2018] [Indexed: 12/11/2022]
Abstract
In some patients with medically refractory epilepsy, EEG with intracerebrally placed electrodes (stereo-electroencephalography, SEEG) is needed to locate the seizure onset zone (SOZ) for successful epilepsy surgery. SEEG has limitations and entails risk of complications because of its invasive character. Non-invasive magnetoencephalography virtual electrodes (MEG-VEs) may overcome SEEG limitations and optimize electrode placement making SOZ localization safer. Our purpose was to assess whether interictal activity measured by MEG-VEs and SEEG at identical anatomical locations were comparable, and whether MEG-VEs activity properties could determine the location of a later resected brain area (RA) as an approximation of the SOZ. We analyzed data from nine patients who underwent MEG and SEEG evaluation, and surgery for medically refractory epilepsy. MEG activity was retrospectively reconstructed using beamforming to obtain VEs at the anatomical locations corresponding to those of SEEG electrodes. Spectral, functional connectivity and functional network properties were obtained for both, MEG-VEs and SEEG time series, and their correlation and reliability were established. Based on these properties, the approximation of the SOZ was characterized by the differences between RA and non-RA (NRA). We found significant positive correlation and reliability between MEG-VEs and SEEG spectral measures (particularly in delta [0.5-4 Hz], alpha2 [10-13 Hz], and beta [13-30 Hz] bands) and broadband functional connectivity. Both modalities showed significantly slower activity and a tendency towards increased broadband functional connectivity in the RA compared to the NRA. Our findings show that spectral and functional connectivity properties of non-invasively obtained MEG-VEs match those of invasive SEEG recordings, and can characterize the SOZ. This suggests that MEG-VEs might be used for optimal SEEG planning and fewer depth electrode implantations, making the localization of the SOZ safer and more successful.
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Affiliation(s)
| | - Ida A Nissen
- Department of Neurology and Clinical Neurophysiology, Amsterdam, the Netherlands
| | - Sander Idema
- Department of Neurosurgery, VU University Medical Center, Amsterdam, the Netherlands
| | - Demetrios N Velis
- Department of Neurology and Clinical Neurophysiology, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Department of Neurology and Clinical Neurophysiology, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Department of Neurology and Clinical Neurophysiology, Amsterdam, the Netherlands
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