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Berchio C, Piguet C, Michel CM, Cordera P, Rihs TA, Dayer AG, Aubry JM. Dysfunctional gaze processing in bipolar disorder. NEUROIMAGE-CLINICAL 2017; 16:545-556. [PMID: 28971006 PMCID: PMC5608173 DOI: 10.1016/j.nicl.2017.09.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2016] [Revised: 09/01/2017] [Accepted: 09/05/2017] [Indexed: 01/15/2023]
Abstract
Gaze conveys emotional information, and humans present sensitivity to its direction from the earliest days of life. Bipolar disorder is a disease characterized by fluctuating states of emotional and cognitive dysregulation. To explore the role of attentional control on face processing in bipolar patients (BP) we used gaze direction as an emotion modulation parameter in a two-back Working Memory (WM) task while high-density EEG data were acquired. Since gaze direction influences emotional attributions to faces with neutral expressions as well, we presented neutral faces with direct and averted gaze. Nineteen euthymic BP and a sample of age- and gender-matched controls were examined. In BP we observed diminished P200 and augmented P300 evoked responses, differentially modulated by non-repeated or repeated faces, as well as by gaze direction. BP showed a reduced P200 amplitude, significantly stronger for faces with direct gaze than averted gaze. Source localization of P200 indicated decreased activity in sensory-motor regions and frontal areas suggestive of abnormal affective processing of neutral faces. The present study provides neurophysiological evidence for abnormal gaze processing in BP and suggests dysfunctional processing of direct eye contact as a prominent characteristic of bipolar disorder. This ERP study identified abnormalities in gaze processing in bipolar patients. We observed functional anomalies in the P200 and P300 evoked responses. BP showed a strong suppression of the P200 for faces with direct gaze. Source localization indicated decreased activity in sensory-motor regions.
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Affiliation(s)
- Cristina Berchio
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland.,Department of Mental Health and Psychiatry, Service of Psychiatric Specialties, Mood Disorders Unit University Hospitals of Geneva, Switzerland
| | - Camille Piguet
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland.,Department of Mental Health and Psychiatry, Service of Psychiatric Specialties, Mood Disorders Unit University Hospitals of Geneva, Switzerland
| | - Christoph M Michel
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland.,Biomedical Imaging Center (CIBM) Lausanne, Geneva, Switzerland
| | - Paolo Cordera
- Department of Mental Health and Psychiatry, Service of Psychiatric Specialties, Mood Disorders Unit University Hospitals of Geneva, Switzerland
| | - Tonia A Rihs
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
| | - Alexandre G Dayer
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland.,Department of Mental Health and Psychiatry, Service of Psychiatric Specialties, Mood Disorders Unit University Hospitals of Geneva, Switzerland.,Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | - Jean-Michel Aubry
- Department of Mental Health and Psychiatry, Service of Psychiatric Specialties, Mood Disorders Unit University Hospitals of Geneva, Switzerland.,Department of Psychiatry, University of Geneva, Geneva, Switzerland
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Abdallah C, Maillard LG, Rikir E, Jonas J, Thiriaux A, Gavaret M, Bartolomei F, Colnat-Coulbois S, Vignal JP, Koessler L. Localizing value of electrical source imaging: Frontal lobe, malformations of cortical development and negative MRI related epilepsies are the best candidates. NEUROIMAGE-CLINICAL 2017; 16:319-329. [PMID: 28856095 PMCID: PMC5565782 DOI: 10.1016/j.nicl.2017.08.009] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 07/24/2017] [Accepted: 08/07/2017] [Indexed: 11/29/2022]
Abstract
OBJECTIVE We aimed to prospectively assess the anatomical concordance of electric source localizations of interictal discharges with the epileptogenic zone (EZ) estimated by stereo-electroencephalography (SEEG) according to different subgroups: the type of epilepsy, the presence of a structural MRI lesion, the aetiology and the depth of the EZ. METHODS In a prospective multicentric observational study, we enrolled 85 consecutive patients undergoing pre-surgical SEEG investigation for focal drug-resistant epilepsy. Electric source imaging (ESI) was performed before SEEG. Source localizations were obtained from dipolar and distributed source methods. Anatomical concordance between ESI and EZ was defined according to 36 predefined sublobar regions. ESI was interpreted blinded to- and subsequently compared with SEEG estimated EZ. RESULTS 74 patients were finally analyzed. 38 patients had temporal and 36 extra-temporal lobe epilepsy. MRI was positive in 52. 41 patients had malformation of cortical development (MCD), 33 had another or an unknown aetiology. EZ was medial in 27, lateral in 13, and medio-lateral in 34. In the overall cohort, ESI completely or partly localized the EZ in 85%: full concordance in 13 cases and partial concordance in 50 cases. The rate of ESI full concordance with EZ was significantly higher in (i) frontal lobe epilepsy (46%; p = 0.05), (ii) cases of negative MRI (36%; p = 0.01) and (iii) MCD (27%; p = 0.03). The rate of ESI full concordance with EZ was not statistically different according to the depth of the EZ. SIGNIFICANCE We prospectively demonstrated that ESI more accurately estimated the EZ in subgroups of patients who are often the most difficult cases in epilepsy surgery: frontal lobe epilepsy, negative MRI and the presence of MCD.
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Affiliation(s)
- Chifaou Abdallah
- Neurology Department, University Hospital of Nancy, Nancy, France
| | - Louis G Maillard
- Neurology Department, University Hospital of Nancy, Nancy, France.,CRAN, UMR 7039, Lorraine University, Vandœuvre-les-Nancy Cedex, France.,CNRS, CRAN, UMR 7039, Vandœuvre-les-Nancy Cedex, France.,Medical Faculty, Lorraine University, Nancy, France
| | - Estelle Rikir
- Neurology Department, University Hospital of Sart-Tilman, Liege, Belgium.,Medical Faculty, Liege University, Liege, Belgium
| | - Jacques Jonas
- Neurology Department, University Hospital of Nancy, Nancy, France.,CRAN, UMR 7039, Lorraine University, Vandœuvre-les-Nancy Cedex, France.,CNRS, CRAN, UMR 7039, Vandœuvre-les-Nancy Cedex, France
| | - Anne Thiriaux
- Neurology department, University Hospital of Reims, Reims, France
| | - Martine Gavaret
- Clinical Neurophysiology Department, AP-HM, University Hospital la Timone, Marseille, France.,INSERM UMR 1106, Institut de Neurosciences des Systemes, Marseille, France.,Medical Faculty, Aix-Marseille University, Marseille, France
| | - Fabrice Bartolomei
- Clinical Neurophysiology Department, AP-HM, University Hospital la Timone, Marseille, France.,INSERM UMR 1106, Institut de Neurosciences des Systemes, Marseille, France.,Medical Faculty, Aix-Marseille University, Marseille, France
| | - Sophie Colnat-Coulbois
- Medical Faculty, Lorraine University, Nancy, France.,Neurosurgery Department, University Hospital of Nancy, Nancy, France
| | - Jean-Pierre Vignal
- Neurology Department, University Hospital of Nancy, Nancy, France.,CRAN, UMR 7039, Lorraine University, Vandœuvre-les-Nancy Cedex, France.,CNRS, CRAN, UMR 7039, Vandœuvre-les-Nancy Cedex, France
| | - Laurent Koessler
- Neurology Department, University Hospital of Nancy, Nancy, France.,CRAN, UMR 7039, Lorraine University, Vandœuvre-les-Nancy Cedex, France.,CNRS, CRAN, UMR 7039, Vandœuvre-les-Nancy Cedex, France
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53
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van Mierlo P, Strobbe G, Keereman V, Birot G, Gadeyne S, Gschwind M, Carrette E, Meurs A, Van Roost D, Vonck K, Seeck M, Vulliémoz S, Boon P. Automated long-term EEG analysis to localize the epileptogenic zone. Epilepsia Open 2017; 2:322-333. [PMID: 29588961 PMCID: PMC5862106 DOI: 10.1002/epi4.12066] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/22/2017] [Indexed: 11/10/2022] Open
Abstract
Objective We investigated the performance of automatic spike detection and subsequent electroencephalogram (EEG) source imaging to localize the epileptogenic zone (EZ) from long-term EEG recorded during video-EEG monitoring. Methods In 32 patients, spikes were automatically detected in the EEG and clustered according to their morphology. The two spike clusters with most single events in each patient were averaged and localized in the brain at the half-rising time and peak of the spike using EEG source imaging. On the basis of the distance from the sources to the resection and the known patient outcome after surgery, the performance of the automated EEG analysis to localize the EZ was quantified. Results In 28 out of the 32 patients, the automatically detected spike clusters corresponded with the reported interictal findings. The median distance to the resection in patients with Engel class I outcome was 6.5 and 15 mm for spike cluster 1 and 27 and 26 mm for cluster 2, at the peak and the half-rising time of the spike, respectively. Spike occurrence (cluster 1 vs. cluster 2) and spike timing (peak vs. half-rising) significantly influenced the distance to the resection (p < 0.05). For patients with Engel class II, III, and IV outcomes, the median distance increased to 36 and 36 mm for cluster 1. Localizing spike cluster 1 at the peak resulted in a sensitivity of 70% and specificity of 100%, positive prediction value (PPV) of 100%, and negative predictive value (NPV) of 53%. Including the results of spike cluster 2 led to an increased sensitivity of 79% NPV of 55% and diagnostic OR of 11.4, while the specificity dropped to 75% and the PPV to 90%. Significance We showed that automated analysis of long-term EEG recordings results in a high sensitivity and specificity to localize the epileptogenic focus.
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Affiliation(s)
- Pieter van Mierlo
- Medical Image and Signal Processing Group Department of Electronics and Information Systems Ghent University-iMinds Medical IT Department Ghent Belgium.,Functional Brain Mapping Laboratory Department of Fundamental Neurosciences University of Geneva Geneva Switzerland
| | - Gregor Strobbe
- Medical Image and Signal Processing Group Department of Electronics and Information Systems Ghent University-iMinds Medical IT Department Ghent Belgium
| | - Vincent Keereman
- Medical Image and Signal Processing Group Department of Electronics and Information Systems Ghent University-iMinds Medical IT Department Ghent Belgium.,Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology Department of Neurology Ghent University Hospital Ghent Belgium
| | - Gwénael Birot
- Functional Brain Mapping Laboratory Department of Fundamental Neurosciences University of Geneva Geneva Switzerland
| | - Stefanie Gadeyne
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology Department of Neurology Ghent University Hospital Ghent Belgium
| | - Markus Gschwind
- Functional Brain Mapping Laboratory Department of Fundamental Neurosciences University of Geneva Geneva Switzerland.,Epilepsy and EEG Unit University Hospital of Geneva Geneva Switzerland
| | - Evelien Carrette
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology Department of Neurology Ghent University Hospital Ghent Belgium
| | - Alfred Meurs
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology Department of Neurology Ghent University Hospital Ghent Belgium
| | - Dirk Van Roost
- Department of Neurosurgery Ghent University Hospital Ghent Belgium
| | - Kristl Vonck
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology Department of Neurology Ghent University Hospital Ghent Belgium
| | - Margitta Seeck
- Epilepsy and EEG Unit University Hospital of Geneva Geneva Switzerland
| | - Serge Vulliémoz
- Functional Brain Mapping Laboratory Department of Fundamental Neurosciences University of Geneva Geneva Switzerland.,Epilepsy and EEG Unit University Hospital of Geneva Geneva Switzerland
| | - Paul Boon
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology Department of Neurology Ghent University Hospital Ghent Belgium
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Nemtsas P, Birot G, Pittau F, Michel CM, Schaller K, Vulliemoz S, Kimiskidis VK, Seeck M. Source localization of ictal epileptic activity based on high-density scalp EEG data. Epilepsia 2017; 58:1027-1036. [DOI: 10.1111/epi.13749] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/11/2017] [Indexed: 02/05/2023]
Affiliation(s)
- Petros Nemtsas
- Laboratory of Clinical Neurophysiology; AHEPA Hospital; Aristotle University of Thessaloniki; Thessaloniki Greece
| | - Gwenael Birot
- Department of Fundamental Neurosciences; Functional Brain Mapping Lab; University of Geneva; Geneva Switzerland
| | - Francesca Pittau
- EEG & Epilepsy Unit; Department of Clinical Neurosciences; University Hospital of Geneva; Geneva Switzerland
| | - Christoph M. Michel
- Department of Fundamental Neurosciences; Functional Brain Mapping Lab; University of Geneva; Geneva Switzerland
- Center for Biomedical Imaging (CIBM) Lausanne; Geneva Switzerland
| | - Karl Schaller
- Department of Clinical Neurosciences; Neurosurgery Clinic; University Hospital of Geneva; Geneva Switzerland
| | - Serge Vulliemoz
- EEG & Epilepsy Unit; Department of Clinical Neurosciences; University Hospital of Geneva; Geneva Switzerland
| | - Vasilios K. Kimiskidis
- Laboratory of Clinical Neurophysiology; AHEPA Hospital; Aristotle University of Thessaloniki; Thessaloniki Greece
| | - Margitta Seeck
- EEG & Epilepsy Unit; Department of Clinical Neurosciences; University Hospital of Geneva; Geneva Switzerland
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55
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Cam SL, Ranta R, Caune V, Korats G, Koessler L, Maillard L, Louis-Dorr V. SEEG dipole source localization based on an empirical Bayesian approach taking into account forward model uncertainties. Neuroimage 2017; 153:1-15. [PMID: 28323161 DOI: 10.1016/j.neuroimage.2017.03.030] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Revised: 01/18/2017] [Accepted: 03/14/2017] [Indexed: 11/24/2022] Open
Abstract
Electromagnetic brain source localization consists in the inversion of a forward model based on a limited number of potential measurements. A wide range of methods has been developed to regularize this severely ill-posed problem and to reduce the solution space, imposing spatial smoothness, anatomical constraint or sparsity of the activated source map. This last criteria, based on physiological assumptions stating that in some particular events (e.g., epileptic spikes, evoked potential) few focal area of the brain are simultaneously actives, has gained more and more interest. Bayesian approaches have the ability to provide sparse solutions under adequate parametrization, and bring a convenient framework for the introduction of priors in the form of probabilistic density functions. However the quality of the forward model is rarely questioned while this parameter has undoubtedly a great influence on the solution. Its construction suffers from numerous approximation and uncertainties, even when using realistic numerical models. In addition, it often encodes a coarse sampling of the continuous solution space due to the computational burden its inversion implies. In this work we propose an empirical Bayesian approach to take into account the uncertainties of the forward model by allowing constrained variations around a prior physical model, in the particular context of SEEG measurements. We demonstrate on simulations that the method enhance the accuracy of the source time-course estimation as well as the sparsity of the resulting source map. Results on real signals prove the applicability of the method in real contexts.
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Affiliation(s)
- S Le Cam
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France.
| | - R Ranta
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France
| | - V Caune
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France
| | - G Korats
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France; Ventspils University College, 101 Inzenieruiela, LV-3601 Ventspils, Latvia
| | - L Koessler
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France
| | - L Maillard
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France; CHU Nancy, Neurology Department, 54000 Nancy, France
| | - V Louis-Dorr
- Université de Lorraine, CRAN, UMR 7039, 54500 Vandœuvre-lès-Nancy, France; CNRS, CRAN, UMR, 7039, France
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56
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Coordinative task difficulty and behavioural errors are associated with increased long-range beta band synchronization. Neuroimage 2017; 146:883-893. [DOI: 10.1016/j.neuroimage.2016.10.030] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2016] [Revised: 10/10/2016] [Accepted: 10/18/2016] [Indexed: 11/17/2022] Open
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57
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Complex patterns of spatially extended generators of epileptic activity: Comparison of source localization methods cMEM and 4-ExSo-MUSIC on high resolution EEG and MEG data. Neuroimage 2016; 143:175-195. [DOI: 10.1016/j.neuroimage.2016.08.044] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Revised: 08/18/2016] [Accepted: 08/20/2016] [Indexed: 11/23/2022] Open
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Coito A, Michel CM, van Mierlo P, Vulliemoz S, Plomp G. Directed Functional Brain Connectivity Based on EEG Source Imaging: Methodology and Application to Temporal Lobe Epilepsy. IEEE Trans Biomed Eng 2016; 63:2619-2628. [PMID: 27775899 DOI: 10.1109/tbme.2016.2619665] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
OBJECTIVE The importance of functional brain connectivity to study physiological and pathological brain activity has been widely recognized. Here, we aimed to 1) review a methodological pipeline to investigate directed functional connectivity between brain regions using source signals derived from high-density EEG; 2) elaborate on some methodological challenges; and 3) apply this pipeline to temporal lobe epilepsy (TLE) patients and healthy controls to investigate directed functional connectivity differences in the theta and beta frequency bands during EEG epochs without visible pathological activity. METHODS The methodological pipeline includes: EEG acquisition and preprocessing, electrical-source imaging (ESI) using individual head models and distributed inverse solutions, parcellation of the gray matter in regions of interest, fixation of the dipole orientation for each region, computation of the spectral power in the source space, and directed functional connectivity estimation using Granger-causal modeling. We specifically analyzed how the signal-to-noise ratio (SNR) changes using different approaches for the dipole orientation fixation. We applied this pipeline to 20 left TLE patients, 20 right TLE patients, and 20 healthy controls. RESULTS Projecting each dipole to the predominant dipole orientation leads to a threefold SNR increase as compared to the norm of the dipoles. By comparing connectivity in TLE versus controls, we found significant frequency-specific outflow differences in physiologically plausible regions. CONCLUSION The results suggest that directed functional connectivity derived from ESI can help better understand frequency-specific resting-state network alterations underlying focal epilepsy. SIGNIFICANCE EEG-based directed functional connectivity could contribute to the search of new biomarkers of this disorder.
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59
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Koessler L, Colnat-Coulbois S, Cecchin T, Hofmanis J, Dmochowski JP, Norcia AM, Maillard LG. In-vivo measurements of human brain tissue conductivity using focal electrical current injection through intracerebral multicontact electrodes. Hum Brain Mapp 2016; 38:974-986. [PMID: 27726249 DOI: 10.1002/hbm.23431] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2016] [Revised: 09/23/2016] [Accepted: 09/30/2016] [Indexed: 11/08/2022] Open
Abstract
In-vivo measurements of human brain tissue conductivity at body temperature were conducted using focal electrical currents injected through intracerebral multicontact electrodes. A total of 1,421 measurements in 15 epileptic patients (age: 28 ± 10) using a radiofrequency generator (50 kHz current injection) were analyzed. Each contact pair was classified as being from healthy (gray matter, n = 696; white matter, n = 530) or pathological (epileptogenic zone, n = 195) tissue using neuroimaging analysis of the local tissue environment and intracerebral EEG recordings. Brain tissue conductivities were obtained using numerical simulations based on conductivity estimates that accounted for the current flow in the local brain volume around the contact pairs (a cube with a side length of 13 mm). Conductivity values were 0.26 S/m for gray matter and 0.17 S/m for white matter. Healthy gray and white matter had statistically different median impedances (P < 0.0001). White matter conductivity was found to be homogeneous as normality tests did not find evidence of multiple subgroups. Gray matter had lower conductivity in healthy tissue than in the epileptogenic zone (0.26 vs. 0.29 S/m; P = 0.012), even when the epileptogenic zone was not visible in the magnetic resonance image (MRI) (P = 0.005). The present in-vivo conductivity values could serve to create more accurate volume conduction models and could help to refine the identification of relevant intracerebral contacts, especially when located within the epileptogenic zone of an MRI-invisible lesion. Hum Brain Mapp 38:974-986, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Laurent Koessler
- CNRS, CRAN, UMR 7039, Vandœuvre-lès-Nancy, France.,Université de Lorraine, CRAN, UMR 7039, Vandœuvre-lès-Nancy, 54516, France.,Service de Neurologie, Centre Hospitalier Universitaire de Nancy, Nancy, 54000, France
| | - Sophie Colnat-Coulbois
- Service de Neurochirurgie, Centre Hospitalier Universitaire de Nancy, Nancy, 54000, France
| | - Thierry Cecchin
- CNRS, CRAN, UMR 7039, Vandœuvre-lès-Nancy, France.,Université de Lorraine, CRAN, UMR 7039, Vandœuvre-lès-Nancy, 54516, France
| | - Janis Hofmanis
- Ventspils Engineering Research Institute, Ventspils University, Ventspils, LV3601, Latvia
| | - Jacek P Dmochowski
- Department of Biomedical Engineering, City College of New York, New York, New York
| | - Anthony M Norcia
- Department of Psychology, Stanford University, Stanford, California
| | - Louis G Maillard
- CNRS, CRAN, UMR 7039, Vandœuvre-lès-Nancy, France.,Université de Lorraine, CRAN, UMR 7039, Vandœuvre-lès-Nancy, 54516, France.,Service de Neurologie, Centre Hospitalier Universitaire de Nancy, Nancy, 54000, France
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60
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Berchio C, Rihs TA, Piguet C, Dayer AG, Aubry JM, Michel CM. Early averted gaze processing in the right Fusiform Gyrus: An EEG source imaging study. Biol Psychol 2016; 119:156-70. [DOI: 10.1016/j.biopsycho.2016.06.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2015] [Revised: 06/21/2016] [Accepted: 06/22/2016] [Indexed: 11/29/2022]
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61
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Gschwind M, Seeck M. Transcranial direct-current stimulation as treatment in epilepsy. Expert Rev Neurother 2016; 16:1427-1441. [DOI: 10.1080/14737175.2016.1209410] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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62
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Advances in EEG: home video telemetry, high frequency oscillations and electrical source imaging. J Neurol 2016; 263:2139-44. [DOI: 10.1007/s00415-016-8159-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Revised: 05/02/2016] [Accepted: 05/02/2016] [Indexed: 10/21/2022]
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63
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Montes-Restrepo V, Carrette E, Strobbe G, Gadeyne S, Vandenberghe S, Boon P, Vonck K, Mierlo PV. The Role of Skull Modeling in EEG Source Imaging for Patients with Refractory Temporal Lobe Epilepsy. Brain Topogr 2016; 29:572-89. [PMID: 26936594 DOI: 10.1007/s10548-016-0482-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2015] [Accepted: 02/19/2016] [Indexed: 11/26/2022]
Abstract
We investigated the influence of different skull modeling approaches on EEG source imaging (ESI), using data of six patients with refractory temporal lobe epilepsy who later underwent successful epilepsy surgery. Four realistic head models with different skull compartments, based on finite difference methods, were constructed for each patient: (i) Three models had skulls with compact and spongy bone compartments as well as air-filled cavities, segmented from either computed tomography (CT), magnetic resonance imaging (MRI) or a CT-template and (ii) one model included a MRI-based skull with a single compact bone compartment. In all patients we performed ESI of single and averaged spikes marked in the clinical 27-channel EEG by the epileptologist. To analyze at which time point the dipole estimations were closer to the resected zone, ESI was performed at two time instants: the half-rising phase and peak of the spike. The estimated sources for each model were validated against the resected area, as indicated by the postoperative MRI. Our results showed that single spike analysis was highly influenced by the signal-to-noise ratio (SNR), yielding estimations with smaller distances to the resected volume at the peak of the spike. Although averaging reduced the SNR effects, it did not always result in dipole estimations lying closer to the resection. The proposed skull modeling approaches did not lead to significant differences in the localization of the irritative zone from clinical EEG data with low spatial sampling density. Furthermore, we showed that a simple skull model (MRI-based) resulted in similar accuracy in dipole estimation compared to more complex head models (based on CT- or CT-template). Therefore, all the considered head models can be used in the presurgical evaluation of patients with temporal lobe epilepsy to localize the irritative zone from low-density clinical EEG recordings.
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Affiliation(s)
- Victoria Montes-Restrepo
- Medical Image and Signal Processing (MEDISIP), Ghent University-iMinds Medical IT Department, De Pintelaan 185, 9000, Ghent, Belgium.
| | - Evelien Carrette
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology, Ghent University Hospital, De Pintelaan 185, 9000, Ghent, Belgium
| | - Gregor Strobbe
- Medical Image and Signal Processing (MEDISIP), Ghent University-iMinds Medical IT Department, De Pintelaan 185, 9000, Ghent, Belgium
| | - Stefanie Gadeyne
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology, Ghent University Hospital, De Pintelaan 185, 9000, Ghent, Belgium
| | - Stefaan Vandenberghe
- Medical Image and Signal Processing (MEDISIP), Ghent University-iMinds Medical IT Department, De Pintelaan 185, 9000, Ghent, Belgium
| | - Paul Boon
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology, Ghent University Hospital, De Pintelaan 185, 9000, Ghent, Belgium
| | - Kristl Vonck
- Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology, Ghent University Hospital, De Pintelaan 185, 9000, Ghent, Belgium
| | - Pieter van Mierlo
- Medical Image and Signal Processing (MEDISIP), Ghent University-iMinds Medical IT Department, De Pintelaan 185, 9000, Ghent, Belgium
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64
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Duncan JS, Winston GP, Koepp MJ, Ourselin S. Brain imaging in the assessment for epilepsy surgery. Lancet Neurol 2016; 15:420-33. [PMID: 26925532 DOI: 10.1016/s1474-4422(15)00383-x] [Citation(s) in RCA: 184] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Revised: 11/22/2015] [Accepted: 12/02/2015] [Indexed: 01/14/2023]
Abstract
Brain imaging has a crucial role in the presurgical assessment of patients with epilepsy. Structural imaging reveals most cerebral lesions underlying focal epilepsy. Advances in MRI acquisitions including diffusion-weighted imaging, post-acquisition image processing techniques, and quantification of imaging data are increasing the accuracy of lesion detection. Functional MRI can be used to identify areas of the cortex that are essential for language, motor function, and memory, and tractography can reveal white matter tracts that are vital for these functions, thus reducing the risk of epilepsy surgery causing new morbidities. PET, SPECT, simultaneous EEG and functional MRI, and electrical and magnetic source imaging can be used to infer the localisation of epileptic foci and assist in the design of intracranial EEG recording strategies. Progress in semi-automated methods to register imaging data into a common space is enabling the creation of multimodal three-dimensional patient-specific datasets. These techniques show promise for the demonstration of the complex relations between normal and abnormal structural and functional data and could be used to direct precise intracranial navigation and surgery for individual patients.
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Affiliation(s)
- John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, University College London, London, UK; National Hospital for Neurology and Neurosurgery, London, UK; Chalfont Centre for Epilepsy, Chalfont St Peter, Gerrards Cross, UK.
| | - Gavin P Winston
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, University College London, London, UK; National Hospital for Neurology and Neurosurgery, London, UK; Chalfont Centre for Epilepsy, Chalfont St Peter, Gerrards Cross, UK
| | - Matthias J Koepp
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, University College London, London, UK; National Hospital for Neurology and Neurosurgery, London, UK; Chalfont Centre for Epilepsy, Chalfont St Peter, Gerrards Cross, UK
| | - Sebastien Ourselin
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, University College London, London, UK; Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK; National Hospital for Neurology and Neurosurgery, London, UK
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Janssen T, Geladé K, van Mourik R, Maras A, Oosterlaan J. An ERP source imaging study of the oddball task in children with Attention Deficit/Hyperactivity Disorder. Clin Neurophysiol 2016; 127:1351-1357. [DOI: 10.1016/j.clinph.2015.10.051] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2015] [Revised: 08/27/2015] [Accepted: 10/27/2015] [Indexed: 11/25/2022]
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Strobbe G, Carrette E, López JD, Montes Restrepo V, Van Roost D, Meurs A, Vonck K, Boon P, Vandenberghe S, van Mierlo P. Electrical source imaging of interictal spikes using multiple sparse volumetric priors for presurgical epileptogenic focus localization. NEUROIMAGE-CLINICAL 2016; 11:252-263. [PMID: 26958464 PMCID: PMC4773507 DOI: 10.1016/j.nicl.2016.01.017] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2015] [Revised: 10/09/2015] [Accepted: 01/17/2016] [Indexed: 11/07/2022]
Abstract
Electrical source imaging of interictal spikes observed in EEG recordings of patients with refractory epilepsy provides useful information to localize the epileptogenic focus during the presurgical evaluation. However, the selection of the time points or time epochs of the spikes in order to estimate the origin of the activity remains a challenge. In this study, we consider a Bayesian EEG source imaging technique for distributed sources, i.e. the multiple volumetric sparse priors (MSVP) approach. The approach allows to estimate the time courses of the intensity of the sources corresponding with a specific time epoch of the spike. Based on presurgical averaged interictal spikes in six patients who were successfully treated with surgery, we estimated the time courses of the source intensities for three different time epochs: (i) an epoch starting 50 ms before the spike peak and ending at 50% of the spike peak during the rising phase of the spike, (ii) an epoch starting 50 ms before the spike peak and ending at the spike peak and (iii) an epoch containing the full spike time period starting 50 ms before the spike peak and ending 230 ms after the spike peak. To identify the primary source of the spike activity, the source with the maximum energy from 50 ms before the spike peak till 50% of the spike peak was subsequently selected for each of the time windows. For comparison, the activity at the spike peaks and at 50% of the peaks was localized using the LORETA inversion technique and an ECD approach. Both patient-specific spherical forward models and patient-specific 5-layered finite difference models were considered to evaluate the influence of the forward model. Based on the resected zones in each of the patients, extracted from post-operative MR images, we compared the distances to the resection border of the estimated activity. Using the spherical models, the distances to the resection border for the MSVP approach and each of the different time epochs were in the same range as the LORETA and ECD techniques. We found distances smaller than 23 mm, with robust results for all the patients. For the finite difference models, we found that the distances to the resection border for the MSVP inversions of the full spike time epochs were generally smaller compared to the MSVP inversions of the time epochs before the spike peak. The results also suggest that the inversions using the finite difference models resulted in slightly smaller distances to the resection border compared to the spherical models. The results we obtained are promising because the MSVP approach allows to study the network of the estimated source-intensities and allows to characterize the spatial extent of the underlying sources. A Bayesian ESI technique is evaluated to localize interictal spike activity. Averaged spikes in six patients were used that were seizure free after surgery. We compared the technique with the LORETA an ECD technique. We evaluated both spherical and 5-layered finite difference forward models. Our approach is potentially useful to delineate the irritative zone.
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Affiliation(s)
- Gregor Strobbe
- Ghent University, Department of Electronics and Information Systems, MEDISIP, De Pintelaan 185, Building BB Floor 5, 9000 Ghent, Belgium; iMinds Medical IT Department, Belgium.
| | - Evelien Carrette
- Laboratory for Clinical and Experimental Neurophysiology, Ghent University Hospital, Ghent, Belgium.
| | - José David López
- SISTEMIC, Department of Electronic Engineering, Universidad de Antioquia UDEA, Calle 70 No. 52-21,Medellín, Colombia.
| | - Victoria Montes Restrepo
- Ghent University, Department of Electronics and Information Systems, MEDISIP, De Pintelaan 185, Building BB Floor 5, 9000 Ghent, Belgium; iMinds Medical IT Department, Belgium
| | - Dirk Van Roost
- Department of Neurosurgery, Ghent University Hospital, Ghent, Belgium.
| | - Alfred Meurs
- Laboratory for Clinical and Experimental Neurophysiology, Ghent University Hospital, Ghent, Belgium.
| | - Kristl Vonck
- Laboratory for Clinical and Experimental Neurophysiology, Ghent University Hospital, Ghent, Belgium.
| | - Paul Boon
- Laboratory for Clinical and Experimental Neurophysiology, Ghent University Hospital, Ghent, Belgium.
| | - Stefaan Vandenberghe
- Ghent University, Department of Electronics and Information Systems, MEDISIP, De Pintelaan 185, Building BB Floor 5, 9000 Ghent, Belgium; iMinds Medical IT Department, Belgium.
| | - Pieter van Mierlo
- Ghent University, Department of Electronics and Information Systems, MEDISIP, De Pintelaan 185, Building BB Floor 5, 9000 Ghent, Belgium; iMinds Medical IT Department, Belgium.
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Early recurrence and ongoing parietal driving during elementary visual processing. Sci Rep 2015; 5:18733. [PMID: 26692466 PMCID: PMC4686934 DOI: 10.1038/srep18733] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2015] [Accepted: 11/25/2015] [Indexed: 11/29/2022] Open
Abstract
Visual stimuli quickly activate a broad network of brain areas that often show reciprocal structural connections between them. Activity at short latencies (<100 ms) is thought to represent a feed-forward activation of widespread cortical areas, but fast activation combined with reciprocal connectivity between areas in principle allows for two-way, recurrent interactions to occur at short latencies after stimulus onset. Here we combined EEG source-imaging and Granger-causal modeling with high temporal resolution to investigate whether recurrent and top-down interactions between visual and attentional brain areas can be identified and distinguished at short latencies in humans. We investigated the directed interactions between widespread occipital, parietal and frontal areas that we localized within participants using fMRI. The connectivity results showed two-way interactions between area MT and V1 already at short latencies. In addition, the results suggested a large role for lateral parietal cortex in coordinating visual activity that may be understood as an ongoing top-down allocation of attentional resources. Our results support the notion that indirect pathways allow early, evoked driving from MT to V1 to highlight spatial locations of motion transients, while influence from parietal areas is continuously exerted around stimulus onset, presumably reflecting task-related attentional processes.
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Mehrkanoon S, Breakspear M, Britz J, Boonstra TW. Intrinsic coupling modes in source-reconstructed electroencephalography. Brain Connect 2015; 4:812-25. [PMID: 25230358 DOI: 10.1089/brain.2014.0280] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
Intrinsic coupling of neuronal assemblies constitutes a key feature of ongoing brain activity, yielding the rich spatiotemporal patterns observed in neuroimaging data and putatively supporting cognitive processes. Intrinsic coupling has been investigated in electrophysiological recordings using two types of functional connectivity measures: amplitude and phase coupling. These two coupling modes differ in their likely causes and functions, and have been proposed to provide complementary insights into intrinsic neuronal interactions. Here, we investigate the relationship between amplitude and phase coupling in source-reconstructed electroencephalography (EEG). Volume conduction is a key obstacle for connectivity analysis in EEG-we therefore also test the envelope correlation of orthogonalized signals and the phase lag index. Functional connectivity between six seed source regions (bilateral visual, sensorimotor, and auditory cortices) and all other cortical voxels was computed. For all four measures, coupling between homologous sensory areas in both hemispheres was significantly higher than with other voxels at the same physical distance. The frequency of significant coupling differed between sensory areas: 10 Hz for visual, 30 Hz for auditory, and 40 Hz for sensorimotor cortices. By contrasting envelope correlations and phase locking values, we observed two distinct clusters of voxels showing a different relationship between amplitude and phase coupling. Large clusters contiguous to the seed regions showed an identity (1:1) relationship between amplitude and phase coupling, whereas a cluster located around the contralateral homologous regions showed higher phase than amplitude coupling. These results show a relationship between intrinsic coupling modes that is distinct from the effect of volume conduction.
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Affiliation(s)
- Saeid Mehrkanoon
- 1 School of Psychiatry, University of New South Wales , Sydney, Australia
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Bae J, Deshmukh A, Song Y, Riera J. Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings. J Vis Exp 2015:e52700. [PMID: 26131755 PMCID: PMC4545023 DOI: 10.3791/52700] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Electroencephalogram (EEG) has been traditionally used to determine which brain regions are the most likely candidates for resection in patients with focal epilepsy. This methodology relies on the assumption that seizures originate from the same regions of the brain from which interictal epileptiform discharges (IEDs) emerge. Preclinical models are very useful to find correlates between IED locations and the actual regions underlying seizure initiation in focal epilepsy. Rats have been commonly used in preclinical studies of epilepsy; hence, there exist a large variety of models for focal epilepsy in this particular species. However, it is challenging to record multichannel EEG and to perform brain source imaging in such a small animal. To overcome this issue, we combine a patented-technology to obtain 32-channel EEG recordings from rodents and an MRI probabilistic atlas for brain anatomical structures in Wistar rats to perform brain source imaging. In this video, we introduce the procedures to acquire multichannel EEG from Wistar rats with focal cortical dysplasia, and describe the steps both to define the volume conductor model from the MRI atlas and to uniquely determine the IEDs. Finally, we validate the whole methodology by obtaining brain source images of IEDs and compare them with those obtained at different time frames during the seizure onset.
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Affiliation(s)
- Jihye Bae
- Biomedical Engineering, Florida International University
| | - Abhay Deshmukh
- Biomedical Engineering, Florida International University
| | - Yinchen Song
- Biomedical Engineering, Florida International University
| | - Jorge Riera
- Biomedical Engineering, Florida International University;
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Coito A, Plomp G, Genetti M, Abela E, Wiest R, Seeck M, Michel CM, Vulliemoz S. Dynamic directed interictal connectivity in left and right temporal lobe epilepsy. Epilepsia 2015; 56:207-17. [PMID: 25599821 DOI: 10.1111/epi.12904] [Citation(s) in RCA: 98] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/25/2014] [Indexed: 11/27/2022]
Abstract
OBJECTIVE There is increasing evidence that epileptic activity involves widespread brain networks rather than single sources and that these networks contribute to interictal brain dysfunction. We investigated the fast-varying behavior of epileptic networks during interictal spikes in right and left temporal lobe epilepsy (RTLE and LTLE) at a whole-brain scale using directed connectivity. METHODS In 16 patients, 8 with LTLE and 8 with RTLE, we estimated the electrical source activity in 82 cortical regions of interest (ROIs) using high-density electroencephalography (EEG), individual head models, and a distributed linear inverse solution. A multivariate, time-varying, and frequency-resolved Granger-causal modeling (weighted Partial Directed Coherence) was applied to the source signal of all ROIs. A nonparametric statistical test assessed differences between spike and baseline epochs. Connectivity results between RTLE and LTLE were compared between RTLE and LTLE and with neuropsychological impairments. RESULTS Ipsilateral anterior temporal structures were identified as key drivers for both groups, concordant with the epileptogenic zone estimated invasively. We observed an increase in outflow from the key driver already before the spike. There were also important temporal and extratemporal ipsilateral drivers in both conditions, and contralateral only in RTLE. A different network pattern between LTLE and RTLE was found: in RTLE there was a much more prominent ipsilateral to contralateral pattern than in LTLE. Half of the RTLE patients but none of the LTLE patients had neuropsychological deficits consistent with contralateral temporal lobe dysfunction, suggesting a relationship between connectivity changes and cognitive deficits. SIGNIFICANCE The different patterns of time-varying connectivity in LTLE and RTLE suggest that they are not symmetrical entities, in line with our neuropsychological results. The highest outflow region was concordant with invasive validation of the epileptogenic zone. This enhanced characterization of dynamic connectivity patterns could better explain cognitive deficits and help the management of epilepsy surgery candidates.
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Affiliation(s)
- Ana Coito
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
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Pittau F, Mégevand P, Sheybani L, Abela E, Grouiller F, Spinelli L, Michel CM, Seeck M, Vulliemoz S. Mapping epileptic activity: sources or networks for the clinicians? Front Neurol 2014; 5:218. [PMID: 25414692 PMCID: PMC4220689 DOI: 10.3389/fneur.2014.00218] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2014] [Accepted: 10/08/2014] [Indexed: 01/03/2023] Open
Abstract
Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity.
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Affiliation(s)
- Francesca Pittau
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
| | - Pierre Mégevand
- Laboratory for Multimodal Human Brain Mapping, Hofstra North Shore LIJ School of Medicine , Manhasset, NY , USA
| | - Laurent Sheybani
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva , Geneva , Switzerland
| | - Eugenio Abela
- Support Center of Advanced Neuroimaging (SCAN), Institute for Diagnostic and Interventional Neuroradiology, University Hospital Inselspital , Bern , Switzerland
| | - Frédéric Grouiller
- Radiology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
| | - Laurent Spinelli
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva , Geneva , Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva , Geneva , Switzerland
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Differences Between MEG and High-Density EEG Source Localizations Using a Distributed Source Model in Comparison to fMRI. Brain Topogr 2014; 28:87-94. [DOI: 10.1007/s10548-014-0405-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2014] [Accepted: 09/22/2014] [Indexed: 10/24/2022]
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