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Lahtinen J, Moura F, Samavaki M, Siltanen S, Pursiainen S. In silicostudy of the effects of cerebral circulation on source localization using a dynamical anatomical atlas of the human head. J Neural Eng 2023; 20. [PMID: 36808911 DOI: 10.1088/1741-2552/acbdc1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 02/21/2023] [Indexed: 02/23/2023]
Abstract
Objective.This study focuses on the effects of dynamical vascular modeling on source localization errors in electroencephalography (EEG). Our aim of thisin silicostudy is to (a) find out the effects of cerebral circulation on the accuracy of EEG source localization estimates, and (b) evaluate its relevance with respect to measurement noise and interpatient variation.Approach.We employ a four-dimensional (3D + T) statistical atlas of the electrical properties of the human head with a cerebral circulation model to generate virtual patients with different cerebral circulatory conditions for EEG source localization analysis. As source reconstruction techniques, we use the linearly constraint minimum variance (LCMV) beamformer, standardized low-resolution brain electromagnetic tomography (sLORETA), and the dipole scan (DS).Main results.Results indicate that arterial blood flow affects source localization at different depths and with varying significance. The average flow rate plays an important role in source localization performance, while the pulsatility effects are very small. In cases where a personalized model of the head is available, blood circulation mismodeling causes localization errors, especially in the deep structures of the brain where the main cerebral arteries are located. When interpatient variations are considered, the results show differences up to 15 mm for sLORETA and LCMV beamformer and 10 mm for DS in the brainstem and entorhinal cortices regions. In regions far from the main arteries vessels, the discrepancies are smaller than 3 mm. When measurement noise is added and interpatient differences are considered in a deep dipolar source, the results indicate that the effects of conductivity mismatch are detectable even for moderate measurement noise. The signal-to-noise ratio limit for sLORETA and LCMV beamformer is 15 dB, while the limit is under 30 dB for DS.Significance.Localization of the brain activity via EEG constitutes an ill-posed inverse problem, where any modeling uncertainty, e.g. a slight amount of noise in the data or material parameter discrepancies, can lead to a significant deviation of the estimated activity, especially in the deep structures of the brain. Proper modeling of the conductivity distribution is necessary in order to obtain an appropriate source localization. In this study, we show that the conductivity of the deep brain structures is particularly impacted by blood flow-induced changes in conductivity because large arteries and veins access the brain through that region.
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Affiliation(s)
- Joonas Lahtinen
- Computing Sciences Unit, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland
| | - Fernando Moura
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.,Engineering, Modelling and Applied Social Sciences Center, Federal University of ABC, São Bernardo do Campo, São Paulo, Brazil
| | - Maryam Samavaki
- Computing Sciences Unit, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland
| | - Samuli Siltanen
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Sampsa Pursiainen
- Computing Sciences Unit, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland
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2
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Beamforming Seizures from the Temporal Lobe Using Magnetoencephalography. Can J Neurol Sci 2023; 50:201-213. [PMID: 35022091 DOI: 10.1017/cjn.2022.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Surgical treatment of drug-resistant temporal lobe epilepsy (TLE) depends on proper identification of the seizure onset zone (SOZ) and differentiation of mesial, temporolimbic seizure onsets from temporal neocortical seizure onsets. Noninvasive source imaging using electroencephalography (EEG) and magnetoencephalography (MEG) can provide accurate information on interictal spike localization; however, EEG and MEG have low sensitivity for epileptiform activity restricted to deep temporolimbic structures. Moreover, in mesial temporal lobe epilepsy (MTLE), interictal spikes frequently arise in neocortical foci distant from the SOZ, rendering interictal spike localization potentially misleading for presurgical planning. METHODS In this study, we used two different beamformer techniques applied to the MEG signal of ictal events acquired during EEG-MEG recordings in six patients with TLE (three neocortical, three MTLE) in whom the ictal source localization results could be compared to ground truth SOZ localizations determined from intracranial EEG and/or clinical, neuroimaging, and postsurgical outcome evidence. RESULTS Beamformer analysis proved to be highly accurate in all cases and was able to identify focal SOZs in mesial, temporolimbic structures. In three patients, interictal spikes were absent, too complex for dipole modeling, or localized to anterolateral temporal neocortex distant to a mesial temporal SOZ, and thus unhelpful in presurgical investigation. CONCLUSIONS MEG beamformer source reconstruction is suitable for analysis of ictal events in TLE and can complement or supersede the traditional analysis of interictal spikes. The method outlined is applicable to any type of epileptiform event, expanding the information value of MEG and broadening its utility for presurgical recording in epilepsy.
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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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Validating EEG, MEG and Combined MEG and EEG Beamforming for an Estimation of the Epileptogenic Zone in Focal Cortical Dysplasia. Brain Sci 2022; 12:brainsci12010114. [PMID: 35053857 PMCID: PMC8796031 DOI: 10.3390/brainsci12010114] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 01/04/2022] [Accepted: 01/06/2022] [Indexed: 02/04/2023] Open
Abstract
MEG and EEG source analysis is frequently used for the presurgical evaluation of pharmacoresistant epilepsy patients. The source localization of the epileptogenic zone depends, among other aspects, on the selected inverse and forward approaches and their respective parameter choices. In this validation study, we compare the standard dipole scanning method with two beamformer approaches for the inverse problem, and we investigate the influence of the covariance estimation method and the strength of regularization on the localization performance for EEG, MEG, and combined EEG and MEG. For forward modelling, we investigate the difference between calibrated six-compartment and standard three-compartment head modelling. In a retrospective study, two patients with focal epilepsy due to focal cortical dysplasia type IIb and seizure freedom following lesionectomy or radiofrequency-guided thermocoagulation (RFTC) used the distance of the localization of interictal epileptic spikes to the resection cavity resp. RFTC lesion as reference for good localization. We found that beamformer localization can be sensitive to the choice of the regularization parameter, which has to be individually optimized. Estimation of the covariance matrix with averaged spike data yielded more robust results across the modalities. MEG was the dominant modality and provided a good localization in one case, while it was EEG for the other. When combining the modalities, the good results of the dominant modality were mostly not spoiled by the weaker modality. For appropriate regularization parameter choices, the beamformer localized better than the standard dipole scan. Compared to the importance of an appropriate regularization, the sensitivity of the localization to the head modelling was smaller, due to similar skull conductivity modelling and the fixed source space without orientation constraint.
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Yu T, Liu X, Wu J, Wang Q. Electrophysiological Biomarkers of Epileptogenicity in Alzheimer's Disease. Front Hum Neurosci 2021; 15:747077. [PMID: 34916917 PMCID: PMC8669481 DOI: 10.3389/fnhum.2021.747077] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 11/01/2021] [Indexed: 11/13/2022] Open
Abstract
Cortical network hyperexcitability is an inextricable feature of Alzheimer’s disease (AD) that also might accelerate its progression. Seizures are reported in 10–22% of patients with AD, and subclinical epileptiform abnormalities have been identified in 21–42% of patients with AD without seizures. Accurate identification of hyperexcitability and appropriate intervention to slow the compromise of cognitive functions of AD might open up a new approach to treatment. Based on the results of several studies, epileptiform discharges, especially those with specific features (including high frequency, robust morphology, right temporal location, and occurrence during awake or rapid eye movement states), frequent small sharp spikes (SSSs), temporal intermittent rhythmic delta activities (TIRDAs), and paroxysmal slow wave events (PSWEs) recorded in long-term scalp electroencephalogram (EEG) provide sufficient sensitivity and specificity in detecting cortical network hyperexcitability and epileptogenicity of AD. In addition, magnetoencephalogram (MEG), foramen ovale (FO) electrodes, and computational approaches help to find subclinical seizures that are invisible on scalp EEGs. We performed a comprehensive analysis of the aforementioned electrophysiological biomarkers of AD-related seizures.
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Affiliation(s)
- Tingting Yu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xiao Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jianping Wu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,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.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China
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6
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Duma GM, Danieli A, Vettorel A, Antoniazzi L, Mento G, Bonanni P. Investigation of dynamic functional connectivity of the source reconstructed epileptiform discharges in focal epilepsy: A graph theory approach. Epilepsy Res 2021; 176:106745. [PMID: 34428725 DOI: 10.1016/j.eplepsyres.2021.106745] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/26/2021] [Accepted: 08/17/2021] [Indexed: 11/18/2022]
Abstract
OBJECTIVE The aim of the present study is to investigate with noninvasive methods the modulation of dynamic functional connectivity during interictal epileptiform discharge (IED). METHOD We reconstructed the cortical source of the EEG recorded IED of 17 patients with focal epilepsy. We then computed dynamic connectivity using the time resolved phase locking value (PLV). We derived graph theory indices (i.e. degree, strength, local efficiency, clustering coefficient and global efficiency). Finally, we selected the atlas node with the maximum activation as the IED cortical source investigating the graph indices dynamics in theta, alpha, beta and gamma frequency bands. RESULTS We observed IED-locked modulations of the graph indexes depending on the frequency bands. We detected a modulation of the strength, clustering coefficient, local and global efficiency both in theta and in alpha bands, which also displayed modulations of the degree index. In the beta band only the global efficiency was modulated by the IED, while no effects were detected in the gamma band. Finally, we found a correlation between alpha and theta local efficiency, as well as alpha global efficiency, and the epilepsy duration. SIGNIFICANCE Our findings suggest that the neural synchronization is not limited to the IED cortical source, but implies a phase synchronization across multiple brain areas. We hypothesize that the aberrant electrical activity originating from the IED locus is spread amongst the other network nodes throughout the low frequency bands (i.e. theta and alpha). Moreover, IED-dependent increase in the global efficiency indicates that the IED interfere with the whole network functioning. We finally discussed possible application of this methodology for future investigation.
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Affiliation(s)
- Gian Marco Duma
- Department of General Psychology, University of Padova, Italy; Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS "E. Medea", Conegliano, TV, Italy.
| | - Alberto Danieli
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS "E. Medea", Conegliano, TV, Italy
| | - Airis Vettorel
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS "E. Medea", Conegliano, TV, Italy
| | - Lisa Antoniazzi
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS "E. Medea", Conegliano, TV, Italy
| | - Giovanni Mento
- Department of General Psychology, University of Padova, Italy; Padova Neuroscience Center (PNC), University of Padova, Italy
| | - Paolo Bonanni
- Epilepsy and Clinical Neurophysiology Unit, Scientific Institute, IRCCS "E. Medea", Conegliano, TV, Italy
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7
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Bagić AI, Funke ME, Kirsch HE, Tenney JR, Zillgitt AJ, Burgess RC. The 10 Common Evidence-Supported Indications for MEG in Epilepsy Surgery: An Illustrated Compendium. J Clin Neurophysiol 2021; 37:483-497. [PMID: 33165222 DOI: 10.1097/wnp.0000000000000726] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Unfamiliarity with the indications for and benefits of magnetoencephalography (MEG) persists, even in the epilepsy community, and hinders its acceptance to clinical practice, despite the evidence. The wide treatment gap for patients with drug-resistant epilepsy and immense underutilization of epilepsy surgery had similar effects. Thus, educating referring physicians (epileptologists, neurologists, and neurosurgeons) both about the value of epilepsy surgery and about the potential benefits of MEG can achieve synergy and greatly improve the process of selecting surgical candidates. As a practical step toward a comprehensive educational process to benefit potential MEG users, current MEG referrers, and newcomers to MEG, the authors have elected to provide an illustrated guide to 10 everyday situations where MEG can help in the evaluation of people with drug-resistant epilepsy. They are as follows: (1) lacking or imprecise hypothesis regarding a seizure onset; (2) negative MRI with a mesial temporal onset suspected; (3) multiple lesions on MRI; (4) large lesion on MRI; (5) diagnostic or therapeutic reoperation; (6) ambiguous EEG findings suggestive of "bilateral" or "generalized" pattern; (7) intrasylvian onset suspected; (8) interhemispheric onset suspected; (9) insular onset suspected; and (10) negative (i.e., spikeless) EEG. Only their practical implementation and furtherance of personal and collective education will lead to the potentially impactful synergy of the two-MEG and epilepsy surgery. Thus, while fulfilling our mission as physicians, we must not forget that ignoring the wealth of evidence about the vast underutilization of epilepsy surgery - and about the usefulness and value of MEG in selecting surgical candidates - is far from benign neglect.
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Affiliation(s)
- Anto I Bagić
- University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), Department of Neurology, University of Pittsburgh Medical Center (UPMC), Pittsburgh, Pennsylvania, U.S.A
| | - Michael E Funke
- MEG Center, McGovern Medical School, UT Houston, Houston, Texas, U.S.A
| | - Heidi E Kirsch
- UCSF Biomagnetic Imaging Laboratory, UCSF, San Francisco, California, U.S.A
| | - Jeffrey R Tenney
- MEG Center, Cincinnati Children's Hospital Medical Center , Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, U.S.A
| | - Andrew J Zillgitt
- Department of Neurology, Beaumont Health Adult Comprehensive Epilepsy Center, Neurosicence Center, Royal Oak, Michigan, U.S.A.; and
| | - Richard C Burgess
- Magnetoencephalography Laboratory, Cleveland Clinic Epilepsy Center, Cleveland, Ohio, U.S.A
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8
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Wennberg R, Tarazi A, Zumsteg D, Garcia Dominguez L. Electromagnetic evidence that benign epileptiform transients of sleep are traveling, rotating hippocampal spikes. Clin Neurophysiol 2020; 131:2915-2925. [DOI: 10.1016/j.clinph.2020.07.023] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 07/05/2020] [Accepted: 07/23/2020] [Indexed: 12/01/2022]
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9
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The Value of Source Localization for Clinical Magnetoencephalography: Beyond the Equivalent Current Dipole. J Clin Neurophysiol 2020; 37:537-544. [DOI: 10.1097/wnp.0000000000000487] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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10
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Pellegrino G, Xu M, Alkuwaiti A, Porras-Bettancourt M, Abbas G, Lina JM, Grova C, Kobayashi E. Effects of Independent Component Analysis on Magnetoencephalography Source Localization in Pre-surgical Frontal Lobe Epilepsy Patients. Front Neurol 2020; 11:479. [PMID: 32582009 PMCID: PMC7280485 DOI: 10.3389/fneur.2020.00479] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 05/01/2020] [Indexed: 01/18/2023] Open
Abstract
Objective: Magnetoencephalography source imaging (MSI) of interictal epileptiform discharges (IED) is a useful presurgical tool in the evaluation of drug-resistant frontal lobe epilepsy (FLE) patients. Yet, failures in MSI can arise related to artifacts and to interference of background activity. Independent component analysis (ICA) is a popular denoising procedure but its clinical application remains challenging, as the selection of multiple independent components (IC) is controversial, operator dependent, and time consuming. We evaluated whether selecting only one IC of interest based on its similarity with the average IED field improves MSI in FLE. Methods: MSI was performed with the equivalent current dipole (ECD) technique and two distributed magnetic source imaging (dMSI) approaches: minimum norm estimate (MNE) and coherent Maximum Entropy on the Mean (cMEM). MSI accuracy was evaluated under three conditions: (1) ICA of continuous data (Cont_ICA), (2) ICA at the time of IED (IED_ICA), and (3) without ICA (No_ICA). Localization performance was quantitatively measured as actual distance of the source maximum in relation to the focus (Dmin), and spatial dispersion (SD) for dMSI. Results: After ICA, ECD Dmin did not change significantly (p > 0.200). For both dMSI techniques, ICA application worsened the source localization accuracy. We observed a worsening of both MNE Dmin (p < 0.05, consistently) and MNE SD (p < 0.001, consistently) for both ICA approaches. A similar behaviour was observed for cMEM, for which, however, Cont_ICA seemed less detrimental. Conclusion: We demonstrated that a simplified ICA approach selecting one IC of interest in combination with distributed magnetic source imaging can be detrimental. More complex approaches may provide better results but would be rather difficult to apply in real-world clinical setting. In a broader perspective, caution should be taken in applying ICA for source localization of interictal activity. To ensure optimal and useful results, effort should focus on acquiring good quality data, minimizing artifacts, and determining optimal candidacy for MEG, rather than counting on data cleaning techniques.
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Affiliation(s)
- Giovanni Pellegrino
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Min Xu
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.,Department of Geriatrics, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Abdulla Alkuwaiti
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Manuel Porras-Bettancourt
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Ghada Abbas
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Jean-Marc Lina
- Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Montreal, QC, Canada.,Département de Génie Électrique, École de Technologie Supérieure, Montreal, QC, Canada.,Centre de Recherches Mathematiques, Univeristé de Montréal, Montreal, QC, Canada
| | - Christophe Grova
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.,Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Montreal, QC, Canada.,Département de Génie Électrique, École de Technologie Supérieure, Montreal, QC, Canada.,Physics Department and PERFORM Centre, Concordia University, Montreal, QC, Canada
| | - Eliane Kobayashi
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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Abstract
Magnetoencephalography is the noninvasive measurement of miniscule magnetic fields produced by brain electrical currents, and is used most fruitfully to evaluate epilepsy patients. While other modalities infer brain function indirectly by measuring changes in blood flow, metabolism, and oxygenation, magnetoencephalography measures neuronal and synaptic function directly with submillisecond temporal resolution. The brain's magnetic field is recorded by neuromagnetometers surrounding the head in a helmet-shaped sensor array. Because magnetic signals are not distorted by anatomy, magnetoencephalography allows for a more accurate measurement and localization of brain activities than electroencephalography. Magnetoencephalography has become an indispensable part of the armamentarium at epilepsy centers.
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Affiliation(s)
- Richard C Burgess
- Epilepsy Center, Neurological Institute, The Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
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12
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Lam AD, Cole AJ, Cash SS. New Approaches to Studying Silent Mesial Temporal Lobe Seizures in Alzheimer's Disease. Front Neurol 2019; 10:959. [PMID: 31551916 PMCID: PMC6737997 DOI: 10.3389/fneur.2019.00959] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Accepted: 08/20/2019] [Indexed: 12/13/2022] Open
Abstract
Silent seizures were discovered in mouse models of Alzheimer's disease over 10 years ago, yet it remains unclear whether these seizures are a salient feature of Alzheimer's disease in humans. Seizures that arise early in the course of Alzheimer's disease most likely originate from the mesial temporal lobe, one of the first structures affected by Alzheimer's disease pathology and one of the most epileptogenic regions of the brain. Several factors greatly limit our ability to identify mesial temporal lobe seizures in patients with Alzheimer's disease, however. First, mesial temporal lobe seizures can be difficult to recognize clinically, as their accompanying symptoms are often subtle or even non-existent. Second, electrical activity arising from the mesial temporal lobe is largely invisible on the scalp electroencephalogram (EEG), the mainstay of diagnosis for epilepsy in this population. In this review, we will describe two new approaches being used to study silent mesial temporal lobe seizures in Alzheimer's disease. We will first describe the methodology and application of foramen ovale electrodes, which captured the first recordings of silent mesial temporal lobe seizures in humans with Alzheimer's disease. We will then describe machine learning approaches being developed to non-invasively identify silent mesial temporal lobe seizures on scalp EEG. Both of these tools have the potential to elucidate the role of silent seizures in humans with Alzheimer's disease, which could have important implications for early diagnosis, prognostication, and development of targeted therapies for this population.
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Affiliation(s)
- Alice D. Lam
- Massachusetts General Hospital, Department of Neurology, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Andrew J. Cole
- Massachusetts General Hospital, Department of Neurology, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Sydney S. Cash
- Massachusetts General Hospital, Department of Neurology, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
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13
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Burgess RC. Magnetoencephalography for localizing and characterizing the epileptic focus. HANDBOOK OF CLINICAL NEUROLOGY 2019; 160:203-214. [PMID: 31277848 DOI: 10.1016/b978-0-444-64032-1.00013-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
Magnetoencephalography (MEG) is the noninvasive measurement of the miniscule magnetic fields produced by electrical currents flowing in the brain-the same neuroelectric activity that produces the EEG. MEG is one of several diagnostic tests employed in the evaluation of patients with epilepsy, but without the need to expose the patient to any potentially harmful agents. MEG is especially important in those being considered for epilepsy surgery, in whom accurate localization of the epileptic focus is paramount. While other modalities infer brain function indirectly by measuring changes in blood flow, metabolism, oxygenation, etc., MEG, as well as EEG, measures neuronal and synaptic function directly and, like EEG, MEG enjoys submillisecond temporal resolution. The measurement of magnetic fields provides information not only about the amplitude of the current but also its orientation. MEG picks up the magnetic field from neuromagnetometers surrounding the head in a helmet-shaped array of sensors. Clinical whole-head systems currently have 200-300 magnetic sensors, thereby offering very high resolution. The magnetic signals are not distorted by anatomy, because magnetic susceptibility is the same for all tissues, including the skull. Hence, MEG allows for a more accurate measurement and localization of brain activities than does EEG. Because one of its primary strengths is the ability to precisely localize electromagnetic activity within brain areas, MEG results are always coregistered to the patient's MRI. When combined in this way with structural imaging, it has been called magnetic source imaging (MSI), but MEG is properly understood as a clinical neurophysiologic diagnostic test. Signal processing and clinical interpretation in magnetoencephalography require sophisticated noise reduction and computerized mathematical modeling. Technological advances in these areas have brought MEG to the point where it is now part of routine clinical practice. MEG has become an indispensable part of the armamentarium at epilepsy centers where MEG laboratories are located, especially when patients are MRI-negative or where results of other structural and functional tests are not entirely concordant.
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Affiliation(s)
- Richard C Burgess
- Department of Neurology, Cleveland Clinic Foundation, Cleveland, OH, United States.
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14
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Hu Y, Yin C, Zhang J, Wang Y. Partial Least Square Aided Beamforming Algorithm in Magnetoencephalography Source Imaging. Front Neurosci 2018; 12:616. [PMID: 30233299 PMCID: PMC6134212 DOI: 10.3389/fnins.2018.00616] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Accepted: 08/14/2018] [Indexed: 01/17/2023] Open
Abstract
Beamforming techniques have played a prominent role in source imaging in neuroimaging and in locating epileptogenic zones. However, existing vector-beamformers are sensitive to noise on localization of epileptogenic zones. In this study, partial least square (PLS) was used to aid the minimum variance beamforming approach for source imaging with magnetoencephalography (MEG) arrays, and verified its effectiveness in simulated data and epilepsy data. First, PLS was employed to extract the components of the MEG arrays by maximizing the covariance between a linear combination of the predictors and the class variable. Noise was then removed by reconstructing the MEG arrays based on those components. The minimum variance beamforming method was used to estimate a source model. Simulations with a realistic head model and varying noise levels indicated that the proposed approach can provide higher spatial accuracy than other well-known beamforming methods. For real MEG recordings in 10 patients with temporal lobe epilepsy, the ratios of the number of spikes localized in the surgical excised region to the total number of spikes using the proposed method were higher than that of the dipole fitting method. These localization results using the proposed method are more consistent with the clinical evaluation. The proposed method may provide a new imaging marker for localization of epileptogenic zones.
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Affiliation(s)
- Yegang Hu
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Big Data-Based Precision Medicine, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China.,Hefei Innovation Research Institute, Beihang University, Hefei, China
| | - Chunli Yin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Brain Functional Disease and Neuromodulation, Beijing, China
| | - Jicong Zhang
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Big Data-Based Precision Medicine, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China.,Hefei Innovation Research Institute, Beihang University, Hefei, China
| | - Yuping Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Brain Functional Disease and Neuromodulation, Beijing, China
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15
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Hari R, Baillet S, Barnes G, Burgess R, Forss N, Gross J, Hämäläinen M, Jensen O, Kakigi R, Mauguière F, Nakasato N, Puce A, Romani GL, Schnitzler A, Taulu S. IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG). Clin Neurophysiol 2018; 129:1720-1747. [PMID: 29724661 PMCID: PMC6045462 DOI: 10.1016/j.clinph.2018.03.042] [Citation(s) in RCA: 89] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Revised: 03/18/2018] [Accepted: 03/24/2018] [Indexed: 12/22/2022]
Abstract
Magnetoencephalography (MEG) records weak magnetic fields outside the human head and thereby provides millisecond-accurate information about neuronal currents supporting human brain function. MEG and electroencephalography (EEG) are closely related complementary methods and should be interpreted together whenever possible. This manuscript covers the basic physical and physiological principles of MEG and discusses the main aspects of state-of-the-art MEG data analysis. We provide guidelines for best practices of patient preparation, stimulus presentation, MEG data collection and analysis, as well as for MEG interpretation in routine clinical examinations. In 2017, about 200 whole-scalp MEG devices were in operation worldwide, many of them located in clinical environments. Yet, the established clinical indications for MEG examinations remain few, mainly restricted to the diagnostics of epilepsy and to preoperative functional evaluation of neurosurgical patients. We are confident that the extensive ongoing basic MEG research indicates potential for the evaluation of neurological and psychiatric syndromes, developmental disorders, and the integrity of cortical brain networks after stroke. Basic and clinical research is, thus, paving way for new clinical applications to be identified by an increasing number of practitioners of MEG.
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Affiliation(s)
- Riitta Hari
- Department of Art, Aalto University, Helsinki, Finland.
| | - Sylvain Baillet
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Gareth Barnes
- Wellcome Centre for Human Neuroimaging, University College of London, London, UK
| | - Richard Burgess
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Nina Forss
- Clinical Neuroscience, Neurology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Joachim Gross
- Centre for Cognitive Neuroimaging, University of Glasgow, Glasgow, UK; Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Germany
| | - Matti Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Ole Jensen
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Ryusuke Kakigi
- Department of Integrative Physiology, National Institute of Physiological Sciences, Okazaki, Japan
| | - François Mauguière
- Department of Functional Neurology and Epileptology, Neurological Hospital & University of Lyon, Lyon, France
| | | | - Aina Puce
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Gian-Luca Romani
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. D'Annunzio, Chieti, Italy
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, and Department of Neurology, Heinrich-Heine-University, Düsseldorf, Germany
| | - Samu Taulu
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA, USA; Department of Physics, University of Washington, Seattle, WA, USA
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16
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Pu Y, Cheyne DO, Cornwell BR, Johnson BW. Non-invasive Investigation of Human Hippocampal Rhythms Using Magnetoencephalography: A Review. Front Neurosci 2018; 12:273. [PMID: 29755314 PMCID: PMC5932174 DOI: 10.3389/fnins.2018.00273] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Accepted: 04/09/2018] [Indexed: 02/06/2023] Open
Abstract
Hippocampal rhythms are believed to support crucial cognitive processes including memory, navigation, and language. Due to the location of the hippocampus deep in the brain, studying hippocampal rhythms using non-invasive magnetoencephalography (MEG) recordings has generally been assumed to be methodologically challenging. However, with the advent of whole-head MEG systems in the 1990s and development of advanced source localization techniques, simulation and empirical studies have provided evidence that human hippocampal signals can be sensed by MEG and reliably reconstructed by source localization algorithms. This paper systematically reviews simulation studies and empirical evidence of the current capacities and limitations of MEG “deep source imaging” of the human hippocampus. Overall, these studies confirm that MEG provides a unique avenue to investigate human hippocampal rhythms in cognition, and can bridge the gap between animal studies and human hippocampal research, as well as elucidate the functional role and the behavioral correlates of human hippocampal oscillations.
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Affiliation(s)
- Yi Pu
- ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, Sydney, NSW, Australia.,Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia
| | - Douglas O Cheyne
- Program in Neurosciences and Mental Health, Hospital for Sick Children Research Institute, Toronto, ON, Canada.,Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Brian R Cornwell
- Brain and Psychological Sciences Research Centre, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Blake W Johnson
- ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, Sydney, NSW, Australia.,Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia
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17
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Abd El-Samie FE, Alotaiby TN, Khalid MI, Alshebeili SA, Aldosari SA. A Review of EEG and MEG Epileptic Spike Detection Algorithms. IEEE ACCESS 2018; 6:60673-60688. [DOI: 10.1109/access.2018.2875487] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
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18
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Chowdhury RA, Pellegrino G, Aydin Ü, Lina JM, Dubeau F, Kobayashi E, Grova C. Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy. Hum Brain Mapp 2017; 39:880-901. [PMID: 29164737 DOI: 10.1002/hbm.23889] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 11/03/2017] [Accepted: 11/07/2017] [Indexed: 11/06/2022] Open
Abstract
Fusion of electroencephalography (EEG) and magnetoencephalography (MEG) data using maximum entropy on the mean method (MEM-fusion) takes advantage of the complementarities between EEG and MEG to improve localization accuracy. Simulation studies demonstrated MEM-fusion to be robust especially in noisy conditions such as single spike source localizations (SSSL). Our objective was to assess the reliability of SSSL using MEM-fusion on clinical data. We proposed to cluster SSSL results to find the most reliable and consistent source map from the reconstructed sources, the so-called consensus map. Thirty-four types of interictal epileptic discharges (IEDs) were analyzed from 26 patients with well-defined epileptogenic focus. SSSLs were performed on EEG, MEG, and fusion data and consensus maps were estimated using hierarchical clustering. Qualitative (spike-to-spike reproducibility rate, SSR) and quantitative (localization error and spatial dispersion) assessments were performed using the epileptogenic focus as clinical reference. Fusion SSSL provided significantly better results than EEG or MEG alone. Fusion found at least one cluster concordant with the clinical reference in all cases. This concordant cluster was always the one involving the highest number of spikes. Fusion yielded highest reproducibility (SSR EEG = 55%, MEG = 71%, fusion = 90%) and lowest localization error. Also, using only few channels from either modality (21EEG + 272MEG or 54EEG + 25MEG) was sufficient to reach accurate fusion. MEM-fusion with consensus map approach provides an objective way of finding the most reliable and concordant generators of IEDs. We, therefore, suggest the pertinence of SSSL using MEM-fusion as a valuable clinical tool for presurgical evaluation of epilepsy.
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Affiliation(s)
- Rasheda Arman Chowdhury
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Québec, Canada
| | | | - Ümit Aydin
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Québec, Canada
| | - Jean-Marc Lina
- Ecole de Technologie Supérieure, Montréal, Québec, Canada.,Centre de Recherches Mathématiques, Université de Montréal, Montréal, Québec, Canada
| | - François Dubeau
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Eliane Kobayashi
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Christophe Grova
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Québec, Canada.,Centre de Recherches Mathématiques, Université de Montréal, Montréal, Québec, Canada.,Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada.,Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Québec, Canada
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19
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Epileptic MEG Spike Detection Using Statistical Features and Genetic Programming with KNN. JOURNAL OF HEALTHCARE ENGINEERING 2017; 2017:3035606. [PMID: 29118962 PMCID: PMC5651155 DOI: 10.1155/2017/3035606] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Revised: 08/06/2017] [Accepted: 09/13/2017] [Indexed: 11/18/2022]
Abstract
Epilepsy is a neurological disorder that affects millions of people worldwide. Monitoring the brain activities and identifying the seizure source which starts with spike detection are important steps for epilepsy treatment. Magnetoencephalography (MEG) is an emerging epileptic diagnostic tool with high-density sensors; this makes manual analysis a challenging task due to the vast amount of MEG data. This paper explores the use of eight statistical features and genetic programing (GP) with the K-nearest neighbor (KNN) for interictal spike detection. The proposed method is comprised of three stages: preprocessing, genetic programming-based feature generation, and classification. The effectiveness of the proposed approach has been evaluated using real MEG data obtained from 28 epileptic patients. It has achieved a 91.75% average sensitivity and 92.99% average specificity.
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20
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Deep Source Localization with Magnetoencephalography Based on Sensor Array Decomposition and Beamforming. SENSORS 2017; 17:s17081860. [PMID: 28800118 PMCID: PMC5579488 DOI: 10.3390/s17081860] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Revised: 07/31/2017] [Accepted: 08/02/2017] [Indexed: 11/17/2022]
Abstract
In recent years, the source localization technique of magnetoencephalography (MEG) has played a prominent role in cognitive neuroscience and in the diagnosis and treatment of neurological and psychological disorders. However, locating deep brain activities such as in the mesial temporal structures, especially in preoperative evaluation of epilepsy patients, may be more challenging. In this work we have proposed a modified beamforming approach for finding deep sources. First, an iterative spatiotemporal signal decomposition was employed for reconstructing the sensor arrays, which could characterize the intrinsic discriminant features for interpreting sensor signals. Next, a sensor covariance matrix was estimated under the new reconstructed space. Then, a well-known vector beamforming approach, which was a linearly constraint minimum variance (LCMV) approach, was applied to compute the solution for the inverse problem. It can be shown that the proposed source localization approach can give better localization accuracy than two other commonly-used beamforming methods (LCMV, MUSIC) in simulated MEG measurements generated with deep sources. Further, we applied the proposed approach to real MEG data recorded from ten patients with medically-refractory mesial temporal lobe epilepsy (mTLE) for finding epileptogenic zone(s), and there was a good agreement between those findings by the proposed approach and the clinical comprehensive results.
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21
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Engels MMA, Yu M, Stam CJ, Gouw AA, van der Flier WM, Scheltens P, van Straaten ECW, Hillebrand A. Directional information flow in patients with Alzheimer's disease. A source-space resting-state MEG study. Neuroimage Clin 2017; 15:673-681. [PMID: 28702344 PMCID: PMC5486371 DOI: 10.1016/j.nicl.2017.06.025] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Revised: 05/10/2017] [Accepted: 06/16/2017] [Indexed: 01/24/2023]
Abstract
In a recent magnetoencephalography (MEG) study, we found posterior-to-anterior information flow over the cortex in higher frequency bands in healthy subjects, with a reversed pattern in the theta band. A disruption of information flow may underlie clinical symptoms in Alzheimer's disease (AD). In AD, highly connected regions (hubs) in posterior areas are mostly disrupted. We therefore hypothesized that in AD the information flow from these hub regions would be disturbed. We used resting-state MEG recordings from 27 early-onset AD patients and 26 healthy controls. Using beamformer-based virtual electrodes, we estimated neuronal oscillatory activity for 78 cortical regions of interest (ROIs) and 12 subcortical ROIs of the AAL atlas, and calculated the directed phase transfer entropy (dPTE) as a measure of information flow between these ROIs. Group differences were evaluated using permutation tests and, for the AD group, associations between dPTE and general cognition or CSF biomarkers were determined using Spearman correlation coefficients. We confirmed the previously reported posterior-to-anterior information flow in the higher frequency bands in the healthy controls, and found it to be disturbed in the beta band in AD. Most prominently, the information flow from the precuneus and the visual cortex, towards frontal and subcortical structures, was decreased in AD. These disruptions did not correlate with cognitive impairment or CSF biomarkers. We conclude that AD pathology may affect the flow of information between brain regions, particularly from posterior hub regions, and that changes in the information flow in the beta band indicate an aspect of the pathophysiological process in AD.
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Affiliation(s)
- M M A Engels
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | - M Yu
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands
| | - C J Stam
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands
| | - A A Gouw
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands
| | - W M van der Flier
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands; Department of Epidemiology and Biostatistics, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Ph Scheltens
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - E C W van Straaten
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands
| | - A Hillebrand
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands
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22
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Magnetoencephalography with temporal spread imaging to visualize propagation of epileptic activity. Clin Neurophysiol 2017; 128:734-743. [DOI: 10.1016/j.clinph.2017.01.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2016] [Revised: 12/11/2016] [Accepted: 01/04/2017] [Indexed: 11/18/2022]
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23
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Wennberg R, Del Campo JM, Shampur N, Rowland NC, Valiante T, Lozano AM, Garcia Dominguez L. Feasibility of magnetoencephalographic source imaging in patients with thalamic deep brain stimulation for epilepsy. Epilepsia Open 2016; 2:101-106. [PMID: 29750219 PMCID: PMC5939388 DOI: 10.1002/epi4.12027] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/10/2016] [Indexed: 11/17/2022] Open
Abstract
Source localization of interictal spikes in patients with medically refractory epilepsy is the most common clinical application of magnetoencephalography (MEG). In recent decades, many patients with intractable epilepsy have been treated with various forms of neurostimulation, including thalamic deep brain stimulation (DBS). Patients with suboptimal seizure control after DBS might in some cases benefit from further investigations for resective epilepsy surgery, including MEG source imaging (MSI). We sought to determine the feasibility and accuracy of MSI in the setting of active thalamic DBS. Simultaneous EEG/MEG was obtained in a patient using an Elekta 306‐channel MEG system, with high‐frequency (100 Hz) DBS of the thalamic anterior nuclei cycling between on and off states. Magnetic artifacts associated with the DBS apparatus were successfully suppressed using the spatiotemporal signal space separation (tSSS) method. Electrical stimulation artifact was removed by standard digital low‐pass filtering. Dipole source modeling results for spike foci in frontal and posterior temporal regions were comparable between stimulation on and stimulation off states, and the source solutions corresponded well to the localization of spikes documented by intracranial EEG. MSI is thus feasible and source solutions can be accurate when performed in patients with active thalamic DBS for epilepsy.
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Affiliation(s)
- Richard Wennberg
- Mitchell Goldhar MEG Unit Division of Neurology Department of Medicine Krembil Neuroscience Centre University Health Network Toronto Western Hospital University of Toronto Toronto Ontario Canada
| | - J Martin Del Campo
- Mitchell Goldhar MEG Unit Division of Neurology Department of Medicine Krembil Neuroscience Centre University Health Network Toronto Western Hospital University of Toronto Toronto Ontario Canada
| | - Nat Shampur
- Mitchell Goldhar MEG Unit Division of Neurology Department of Medicine Krembil Neuroscience Centre University Health Network Toronto Western Hospital University of Toronto Toronto Ontario Canada
| | - Nathan C Rowland
- Division of Neurosurgery Department of Surgery Krembil Neuroscience Centre University Health Network Toronto Western Hospital University of Toronto Toronto Ontario Canada
| | - Taufik Valiante
- Division of Neurosurgery Department of Surgery Krembil Neuroscience Centre University Health Network Toronto Western Hospital University of Toronto Toronto Ontario Canada
| | - Andres M Lozano
- Division of Neurosurgery Department of Surgery Krembil Neuroscience Centre University Health Network Toronto Western Hospital University of Toronto Toronto Ontario Canada
| | - Luis Garcia Dominguez
- Mitchell Goldhar MEG Unit Division of Neurology Department of Medicine Krembil Neuroscience Centre University Health Network Toronto Western Hospital University of Toronto Toronto Ontario Canada
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24
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Hillebrand A, Nissen IA, Ris-Hilgersom I, Sijsma NCG, Ronner HE, van Dijk BW, Stam CJ. Detecting epileptiform activity from deeper brain regions in spatially filtered MEG data. Clin Neurophysiol 2016; 127:2766-2769. [PMID: 27417050 DOI: 10.1016/j.clinph.2016.05.272] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2014] [Revised: 05/19/2016] [Accepted: 05/19/2016] [Indexed: 10/21/2022]
Affiliation(s)
- A Hillebrand
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands.
| | - I A Nissen
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands
| | - I Ris-Hilgersom
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands
| | - N C G Sijsma
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands
| | - H E Ronner
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands
| | - B W van Dijk
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands; Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands
| | - C J Stam
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands
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25
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Nissen IA, Stam CJ, Citroen J, Reijneveld JC, Hillebrand A. Preoperative evaluation using magnetoencephalography: Experience in 382 epilepsy patients. Epilepsy Res 2016; 124:23-33. [PMID: 27232766 DOI: 10.1016/j.eplepsyres.2016.05.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2015] [Revised: 10/03/2015] [Accepted: 05/09/2016] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Identifying epilepsy patients for whom clinical MEG is likely to be beneficial avoids or optimizes burdensome ancillary investigations. We determined whether it could be predicted upfront if MEG would be able to generate a hypothesis about the location of the epileptogenic zone (EZ), and in which patients MEG fails to do so. METHODS MEG recordings of 382 epilepsy patients with inconclusive findings regarding EZ localization prior to MEG were acquired for preoperative evaluation. MEG reports were categorized for several demographic, clinical and MEG variables. First, demographic and clinical variables were associated with MEG localization ability for upfront prediction. Second, all variables were compared between patients with and without MEG location in order to characterize patients without MEG location. RESULTS Our patient group had often complex etiology and did not contain the (by other means) straightforward and well-localized cases, such as those with concordant tumor and EEG location. For our highly-selected patient group, MEG localization ability cannot be predicted upfront, although the odds of a recording with MEG location were significantly higher in the absence of a tumor and in the presence of widespread MRI abnormalities. Compared to the patients with MEG location, patients without MEG location more often had a tumor, widespread EEG abnormalities, non-lateralizing MEG abnormalities, non-concordant MEG/EEG abnormalities and less often widespread MRI abnormalities or epileptiform MEG activity. In a subgroup of 48 patients with known surgery outcome, more patients with concordant MEG and resection area were seizure-free than patients with discordant results. CONCLUSIONS MEG potentially adds information about the location of the EZ even in patients with a complex etiology, and the clinical advice is to not withhold MEG in epilepsy surgery candidates. Providing a hypothesis about the location of the EZ using MEG is difficult in patients with inconclusive EEG and MRI findings, and in the absence of specific epileptiform activity. More refined methods are needed for patients where MEG currently does not contribute to the hypothesis about the location of the EZ.
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Affiliation(s)
- I A Nissen
- Department of Clinical Neurophysiology and MEG Center, Neuroscience Campus Amsterdam, VU University Medical Center, Postbus 7057, 1007 MB, Amsterdam, The Netherlands.
| | - C J Stam
- Department of Clinical Neurophysiology and MEG Center, Neuroscience Campus Amsterdam, VU University Medical Center, Postbus 7057, 1007 MB, Amsterdam, The Netherlands.
| | - J Citroen
- Department of Clinical Neurophysiology and MEG Center, Neuroscience Campus Amsterdam, VU University Medical Center, Postbus 7057, 1007 MB, Amsterdam, The Netherlands.
| | - J C Reijneveld
- Brain Tumor Center Amsterdam & Department of Neurology, VU University Medical Center, Postbus 7057, 1007 MB, Amsterdam, The Netherlands.
| | - A Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Neuroscience Campus Amsterdam, VU University Medical Center, Postbus 7057, 1007 MB, Amsterdam, The Netherlands.
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26
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Grova C, Aiguabella M, Zelmann R, Lina JM, Hall JA, Kobayashi E. Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy. Hum Brain Mapp 2016; 37:1661-83. [PMID: 26931511 DOI: 10.1002/hbm.23127] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Revised: 12/18/2015] [Accepted: 01/17/2016] [Indexed: 01/19/2023] Open
Abstract
Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Christophe Grova
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada.,Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Québec, Canada.,Physics Department and PERFORM Centre, Concordia University, Montreal, Québec, Canada.,Centre De Recherches En Mathématiques, Montreal, Québec, Canada
| | - Maria Aiguabella
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada
| | - Rina Zelmann
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada
| | - Jean-Marc Lina
- Centre De Recherches En Mathématiques, Montreal, Québec, Canada.,Electrical Engineering Department, Ecole De Technologie Supérieure, Montreal, Québec, Canada.,Centre D'etudes Avancées En Médecine Du Sommeil, Centre De Recherche De L'hôpital Sacré-Coeur De Montréal, Montreal, Québec, Canada
| | - Jeffery A Hall
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada
| | - Eliane Kobayashi
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada
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van Klink N, Hillebrand A, Zijlmans M. Identification of epileptic high frequency oscillations in the time domain by using MEG beamformer-based virtual sensors. Clin Neurophysiol 2016; 127:197-208. [DOI: 10.1016/j.clinph.2015.06.008] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2014] [Revised: 05/22/2015] [Accepted: 06/08/2015] [Indexed: 10/23/2022]
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Beniczky S, Duez L, Scherg M, Hansen PO, Tankisi H, Sidenius P, Sabers A, Pinborg LH, Uldall P, Fuglsang-Frederiksen A. Visualizing spikes in source-space: Rapid and efficient evaluation of magnetoencephalography. Clin Neurophysiol 2015; 127:1067-1072. [PMID: 26238854 DOI: 10.1016/j.clinph.2015.07.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2015] [Revised: 07/14/2015] [Accepted: 07/16/2015] [Indexed: 10/23/2022]
Abstract
OBJECTIVE Reviewing magnetoencephalography (MEG) recordings is time-consuming: signals from the 306 MEG-sensors are typically reviewed divided into six arrays of 51 sensors each, thus browsing each recording six times in order to evaluate all signals. A novel method of reconstructing the MEG signals in source-space was developed using a source-montage of 29 brain-regions and two spatial components to remove magnetocardiographic (MKG) artefacts. Our objective was to evaluate the accuracy of reviewing MEG in source-space. METHODS In 60 consecutive patients with epilepsy, we prospectively evaluated the accuracy of reviewing the MEG signals in source-space as compared to the classical method of reviewing them in sensor-space. RESULTS All 46 spike-clusters identified in sensor-space were also identified in source-space. Two additional spike-clusters were identified in source-space. As 29 source-channels can be easily displayed simultaneously, MEG recordings had to be browsed only once. Yet, this yielded a global coverage of the recorded signals and enhanced detectability of epileptiform discharges because MKG-artefacts were suppressed and did not impede evaluation in source-space. CONCLUSIONS Our results show that reviewing MEG recordings in source-space is accurate and much more rapid than the classical method of reviewing in sensor-space. SIGNIFICANCE This novel method facilitates the clinical use of MEG.
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Affiliation(s)
- Sándor Beniczky
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Neurophysiology, Danish Epilepsy Centre, Dianalund, Denmark.
| | - Lene Duez
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | | | - Peter Orm Hansen
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | - Hatice Tankisi
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | - Per Sidenius
- Department of Neurology, Aarhus University Hospital, Aarhus, Denmark
| | - Anne Sabers
- Department of Neurology and Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Lars Hageman Pinborg
- Department of Neurology and Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Peter Uldall
- Department of Paediatrics, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
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Aydin Ü, Vorwerk J, Dümpelmann M, Küpper P, Kugel H, Heers M, Wellmer J, Kellinghaus C, Haueisen J, Rampp S, Stefan H, Wolters CH. Combined EEG/MEG can outperform single modality EEG or MEG source reconstruction in presurgical epilepsy diagnosis. PLoS One 2015; 10:e0118753. [PMID: 25761059 PMCID: PMC4356563 DOI: 10.1371/journal.pone.0118753] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2014] [Accepted: 01/06/2015] [Indexed: 11/25/2022] Open
Abstract
We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1) sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2) still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes) or MEG (275-gradiometers) and especially on the benefits of combined EEG/MEG (EMEG) source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG) (167-contacts) and low-density EEG (ldEEG) (21-electrodes). To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset), i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply.
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Affiliation(s)
- Ümit Aydin
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
- Institute for Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
- * E-mail:
| | - Johannes Vorwerk
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Matthias Dümpelmann
- Epilepsy Center, Universitätsklinikum Freiburg, Freiburg im Breisgau, Germany
| | - Philipp Küpper
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
- Department of Neurology, Klinikum Osnabrück, Osnabrück, Germany
| | - Harald Kugel
- Department of Clinical Radiology, Universitätsklinikum Münster, Münster, Germany
| | - Marcel Heers
- Epilepsy Center, Universitätsklinikum Freiburg, Freiburg im Breisgau, Germany
- Ruhr-Epileptology Department of Neurology, Universitätsklinikum Knappschaftskrankenhaus Bochum, Bochum, Germany
| | - Jörg Wellmer
- Ruhr-Epileptology Department of Neurology, Universitätsklinikum Knappschaftskrankenhaus Bochum, Bochum, Germany
| | | | - Jens Haueisen
- Institute for Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
| | - Stefan Rampp
- Ruhr-Epileptology Department of Neurology, Universitätsklinikum Knappschaftskrankenhaus Bochum, Bochum, Germany
- Epilepsy Center, Department of Neurology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Hermann Stefan
- Epilepsy Center, Department of Neurology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Carsten H. Wolters
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
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Yoshimura M, Zhang S, Ueda Y, Matsuda K, Imai K, Takahashi Y, Inoue Y. An analysis of epileptic negative myoclonus by magnetoencephalography. Epilepsy Res 2015; 110:139-45. [PMID: 25616466 DOI: 10.1016/j.eplepsyres.2014.12.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2014] [Revised: 11/26/2014] [Accepted: 12/03/2014] [Indexed: 10/24/2022]
Abstract
PURPOSE To clarify the neurophysiologic mechanism of epileptic negative myoclonus (ENM), we analyzed the magnetoencephalography (MEG) of a patient with ENM. METHODS The 52-year-old right-handed male had frequent ENM in the right upper limb during awake and monthly seizures with sudden tonic stiffening of the right forearm during sleep. MRI demonstrated a focal cortical dysplasia in the cortex of the posterior portion of the left superior frontal sulcus. Whole-head type MEG, electroencephalography and electromyography were simultaneously recorded during ENM. Single equivalent currents dipoles (ECDs) were calculated for each spike component followed by silent period (SP) in the right deltoid muscle. These MEG spike components were averaged with respect to their peaks, and single ECD was also calculated for the averaged spike component. Furthermore, we analyzed the MEG with the silent-period-locked-averaging (SPLA) method. Twenty MEG signal data were averaged with respect to the onset of SP. Twenty epochs in each of five separate periods of recording were repeatedly averaged. ECDs were calculated for spike components observed in each averaged epoch. RESULTS ECDs of each spike followed by SP were clustered near the cortex of the left central sulcus. In MEG spike averaging and SPLA method, ECDs at the peak of spike components were located near the right shoulder division of the primary sensorimotor cortex reproducibly. ECDs on the ascending phase before the peak were located lateral to the above ECD location in MEG spike averaging method. CONCLUSIONS ENM was produced by an inhibitory action on the primary sensorimotor cortex corresponding to the body segment in which ENM occurs.
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Affiliation(s)
- Masaki Yoshimura
- National Epilepsy Center, Shizuoka Institute of Epilepsy and Neurological Disorders, Urushiyama 886, Aoi-ku 420-8688, Shizuoka, Japan.
| | - Shouwen Zhang
- National Epilepsy Center, Shizuoka Institute of Epilepsy and Neurological Disorders, Urushiyama 886, Aoi-ku 420-8688, Shizuoka, Japan.
| | - Yuki Ueda
- National Epilepsy Center, Shizuoka Institute of Epilepsy and Neurological Disorders, Urushiyama 886, Aoi-ku 420-8688, Shizuoka, Japan.
| | - Kazumi Matsuda
- National Epilepsy Center, Shizuoka Institute of Epilepsy and Neurological Disorders, Urushiyama 886, Aoi-ku 420-8688, Shizuoka, Japan.
| | - Katsumi Imai
- National Epilepsy Center, Shizuoka Institute of Epilepsy and Neurological Disorders, Urushiyama 886, Aoi-ku 420-8688, Shizuoka, Japan.
| | - Yukitoshi Takahashi
- National Epilepsy Center, Shizuoka Institute of Epilepsy and Neurological Disorders, Urushiyama 886, Aoi-ku 420-8688, Shizuoka, Japan.
| | - Yushi Inoue
- National Epilepsy Center, Shizuoka Institute of Epilepsy and Neurological Disorders, Urushiyama 886, Aoi-ku 420-8688, Shizuoka, Japan.
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Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy. Brain Topogr 2015; 29:162-81. [DOI: 10.1007/s10548-014-0423-1] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2014] [Accepted: 12/24/2014] [Indexed: 10/24/2022]
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Bagić A, Ebersole JS. Does MEG/MSI dipole variability mean unreliability? Clin Neurophysiol 2015; 126:209-11. [DOI: 10.1016/j.clinph.2014.01.037] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2013] [Revised: 01/20/2014] [Accepted: 01/23/2014] [Indexed: 11/28/2022]
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Elucidating the meaning of dipole variability in MEG/MSI. Clin Neurophysiol 2015; 126:211-5. [DOI: 10.1016/j.clinph.2014.03.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2014] [Revised: 03/07/2014] [Accepted: 03/11/2014] [Indexed: 11/21/2022]
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Contribution of research on 'Epilepsy & behavior' to the refinement of functional brain atlas in four dimensions. Epilepsy Behav 2014; 40:86-8. [PMID: 25262069 PMCID: PMC4254342 DOI: 10.1016/j.yebeh.2014.08.030] [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: 08/16/2014] [Accepted: 08/18/2014] [Indexed: 11/22/2022]
Abstract
Intracranial stimulation mapping by Penfield et al. largely contributed to our current knowledge of the functional organization of motor, sensory, and language systems. The functional maps were generated and printed in two dimensions, based on the summary results of direct cortical stimulation of which locations varied across patients. Intracranial measurement of electrocorticographic changes elicited by a task can localize the regions involved in or participating to the given task. Augmentation of high-gamma activity at >80 Hz is considered to reflect in situ cortical activation at each moment. In the late 2000s, the spatial-temporal profiles of event-related high-gamma activity began to be published as a video material in journals. We have referred to our animation movie as ‘in-vivo animation of event-related high-gamma activity’, that demonstrates ‘when’ and ‘where’ cortical regions are activated in a self-explanatory fashion. Summation of event-related high-gamma measures derived from a large cohort of patients, as previously performed by Penfield et al, is expected to generate unique four-dimensional functional brain atlas covering the whole cerebral cortex.
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Wennberg R, Cheyne D. EEG source imaging of anterior temporal lobe spikes: Validity and reliability. Clin Neurophysiol 2014; 125:886-902. [DOI: 10.1016/j.clinph.2013.09.042] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2013] [Revised: 08/29/2013] [Accepted: 09/15/2013] [Indexed: 11/26/2022]
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Aydin Ü, Vorwerk J, Küpper P, Heers M, Kugel H, Galka A, Hamid L, Wellmer J, Kellinghaus C, Rampp S, Wolters CH. Combining EEG and MEG for the reconstruction of epileptic activity using a calibrated realistic volume conductor model. PLoS One 2014; 9:e93154. [PMID: 24671208 PMCID: PMC3966892 DOI: 10.1371/journal.pone.0093154] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2014] [Accepted: 02/28/2014] [Indexed: 11/18/2022] Open
Abstract
To increase the reliability for the non-invasive determination of the irritative zone in presurgical epilepsy diagnosis, we introduce here a new experimental and methodological source analysis pipeline that combines the complementary information in EEG and MEG, and apply it to data from a patient, suffering from refractory focal epilepsy. Skull conductivity parameters in a six compartment finite element head model with brain anisotropy, constructed from individual MRI data, are estimated in a calibration procedure using somatosensory evoked potential (SEP) and field (SEF) data. These data are measured in a single run before acquisition of further runs of spontaneous epileptic activity. Our results show that even for single interictal spikes, volume conduction effects dominate over noise and need to be taken into account for accurate source analysis. While cerebrospinal fluid and brain anisotropy influence both modalities, only EEG is sensitive to skull conductivity and conductivity calibration significantly reduces the difference in especially depth localization of both modalities, emphasizing its importance for combining EEG and MEG source analysis. On the other hand, localization differences which are due to the distinct sensitivity profiles of EEG and MEG persist. In case of a moderate error in skull conductivity, combined source analysis results can still profit from the different sensitivity profiles of EEG and MEG to accurately determine location, orientation and strength of the underlying sources. On the other side, significant errors in skull modeling are reflected in EEG reconstruction errors and could reduce the goodness of fit to combined datasets. For combined EEG and MEG source analysis, we therefore recommend calibrating skull conductivity using additionally acquired SEP/SEF data.
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Affiliation(s)
- Ümit Aydin
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Johannes Vorwerk
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Philipp Küpper
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
- Department of Neurology, Klinikum Osnabrück, Osnabrück, Germany
| | - Marcel Heers
- Ruhr-Epileptology Department of Neurology, Universitätsklinikum Knappschaftskrankenhaus Bochum, Bochum, Germany
| | - Harald Kugel
- Department of Clinical Radiology, Universitätsklinikum Münster, Münster, Germany
| | - Andreas Galka
- Department of Neuropediatrics, Universitätsklinikum Schleswig-Holstein, Kiel, Germany
| | - Laith Hamid
- Department of Neuropediatrics, Universitätsklinikum Schleswig-Holstein, Kiel, Germany
| | - Jörg Wellmer
- Ruhr-Epileptology Department of Neurology, Universitätsklinikum Knappschaftskrankenhaus Bochum, Bochum, Germany
| | | | - Stefan Rampp
- Epilepsy Center, Department of Neurology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Carsten Hermann Wolters
- Institute for Biomagnetism and Biosignalanalysis, Westfälische Wilhelms-Universität Münster, Münster, Germany
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