51
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Toscano G, Carboni M, Rubega M, Spinelli L, Pittau F, Bartoli A, Momjian S, Manni R, Terzaghi M, Vulliemoz S, Seeck M. Visual analysis of high density EEG: As good as electrical source imaging? Clin Neurophysiol Pract 2019; 5:16-22. [PMID: 31909306 PMCID: PMC6939057 DOI: 10.1016/j.cnp.2019.09.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2019] [Revised: 09/19/2019] [Accepted: 09/29/2019] [Indexed: 11/29/2022] Open
Abstract
Visual analysis of HD-EEG is an excellent tool to explore the epileptogenic focus. ESI remains the gold standard for presurgical evaluation of the cortical source. ESI at 50% slope/ESI at peak discordance could predict worse surgical outcome.
Objective In this study, we sought to determine whether visual analysis of high density EEG (HD-EEG) would provide similar localizing information comparable to electrical source imaging (ESI). Methods HD-EEG (256 electrodes) recordings from 20 patients suffering from unifocal, drug-resistant epilepsy (13 women, mean age 29.1 ± 2.62 years, 11 with temporal lobe epilepsy) were examined. In the visual analysis condition, we identified the 5 contacts with maximal spike amplitude and determined their localization with respect to the underlying cortex. ESI was computed using the LAURA algorithm of the averaged spikes in the patient’s individual MRI. We considered the localization “correct” if all 5 contacts were concordant with the resection volume underneath or if ESI was located within the resection as determined by the postoperative MRI. Results Twelve patients were postoperatively seizure-free (Engel Class IA), while the remaining eight were in class IB to IV. Visual analysis and ESI showed sensitivity of 58% and 75%, specificity of 75% and 87%, and accuracy of 65% and 80%, respectively. In 70% of cases, visual analysis and ESI provided concordant results. Conclusions Localization of the electrodes with maximal spike amplitude provides very good estimation of the localization of the underlying source. However, ESI has a higher accuracy and adds 3D information; therefore, it should remain the tool of choice for presurgical evaluation. Significance The present study proposes the possibility to analyze HD-EEG visually, in tandem with ESI or alone, if ESI is not accessible.
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Affiliation(s)
- Gianpaolo Toscano
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland.,Unit of Sleep Medicine and Epilepsy, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioural Sciences, University of Pavia, Italy
| | - Margherita Carboni
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland.,Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Maria Rubega
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Laurent Spinelli
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - Francesca Pittau
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - Andrea Bartoli
- Department of Neurosurgery, University Hospital of Geneva, Geneva, Switzerland
| | - Shahan Momjian
- Department of Neurosurgery, University Hospital of Geneva, Geneva, Switzerland
| | - Raffaele Manni
- Unit of Sleep Medicine and Epilepsy, IRCCS Mondino Foundation, Pavia, Italy
| | - Michele Terzaghi
- Unit of Sleep Medicine and Epilepsy, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioural Sciences, University of Pavia, Italy
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
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Carboni M, Rubega M, Iannotti GR, De Stefano P, Toscano G, Tourbier S, Pittau F, Hagmann P, Momjian S, Schaller K, Seeck M, Michel CM, van Mierlo P, Vulliemoz S. The network integration of epileptic activity in relation to surgical outcome. Clin Neurophysiol 2019; 130:2193-2202. [PMID: 31669753 DOI: 10.1016/j.clinph.2019.09.006] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 08/21/2019] [Accepted: 09/12/2019] [Indexed: 11/24/2022]
Abstract
OBJECTIVE Epilepsy is a network disease with epileptic activity and cognitive impairment involving large-scale brain networks. A complex network is involved in the seizure and in the interictal epileptiform discharges (IEDs). Directed connectivity analysis, describing the information transfer between brain regions, and graph analysis are applied to high-density EEG to characterise networks. METHODS We analysed 19 patients with focal epilepsy who had high-density EEG containing IED and underwent surgery. We estimated cortical activity during IED using electric source analysis in 72 atlas-based cortical regions of the individual brain MRI. We applied directed connectivity analysis (information Partial Directed Coherence) and graph analysis on these sources and compared patients with good vs poor post-operative outcome at global, hemispheric and lobar level. RESULTS We found lower network integration reflected by global, hemispheric, lobar efficiency during the IED (p < 0.05) in patients with good post-surgical outcome, compared to patients with poor outcome. Prediction was better than using the IED field or the localisation obtained by electric source imaging. CONCLUSIONS Abnormal network patterns in epilepsy are related to seizure outcome after surgery. SIGNIFICANCE Our finding may help understand networks related to a more "isolated" epileptic activity, limiting the extent of the epileptic network in patients with subsequent good post-operative outcome.
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Affiliation(s)
- M Carboni
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland.
| | - M Rubega
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - G R Iannotti
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland; Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - P De Stefano
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - G Toscano
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Unit of Sleep Medicine and Epilepsy, C. Mondino National Neurological Institute, Pavia, Italy
| | - S Tourbier
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - F Pittau
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - P Hagmann
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - S Momjian
- Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - K Schaller
- Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - M Seeck
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - C M Michel
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - P van Mierlo
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - S Vulliemoz
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland.
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Mégevand P, Hamid L, Dümpelmann M, Heers M. New horizons in clinical electric source imaging. ZEITSCHRIFT FUR EPILEPTOLOGIE 2019. [DOI: 10.1007/s10309-019-0258-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Coito A, Biethahn S, Tepperberg J, Carboni M, Roelcke U, Seeck M, van Mierlo P, Gschwind M, Vulliemoz S. Interictal epileptogenic zone localization in patients with focal epilepsy using electric source imaging and directed functional connectivity from low-density EEG. Epilepsia Open 2019; 4:281-292. [PMID: 31168495 PMCID: PMC6546067 DOI: 10.1002/epi4.12318] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Revised: 02/25/2019] [Accepted: 03/15/2019] [Indexed: 01/23/2023] Open
Abstract
OBJECTIVE Electrical source imaging (ESI) is used increasingly to estimate the epileptogenic zone (EZ) in patients with epilepsy. Directed functional connectivity (DFC) coupled to ESI helps to better characterize epileptic networks, but studies on interictal activity have relied on high-density recordings. We investigated the accuracy of ESI and DFC for localizing the EZ, based on low-density clinical electroencephalography (EEG). METHODS We selected patients with the following: (a) focal epilepsy, (b) interictal spikes on standard EEG, (c) either a focal structural lesion concordant with the electroclinical semiology or good postoperative outcome. In 34 patients (20 temporal lobe epilepsy [TLE], 14 extra-TLE [ETLE]), we marked interictal spikes and estimated the cortical activity during each spike in 82 cortical regions using a patient-specific head model and distributed linear inverse solution. DFC between brain regions was computed using Granger-causal modeling followed by network topologic measures. The concordance with the presumed EZ at the sublobar level was computed using the epileptogenic lesion or the resected area in postoperative seizure-free patients. RESULTS ESI, summed outflow, and efficiency were concordant with the presumed EZ in 76% of the patients, whereas the clustering coefficient and betweenness centrality were concordant in 70% of patients. There was no significant difference between ESI and connectivity measures. In all measures, patients with TLE had a significantly higher (P < 0.05) concordance with the presumed EZ than patients with with ETLE. The brain volume accepted for concordance was significantly larger in TLE. SIGNIFICANCE ESI and DFC derived from low-density EEG can reliably estimate the EZ from interictal spikes. Connectivity measures were not superior to ESI for EZ localization during interictal spikes, but the current validation of the localization of connectivity measure is promising for other applications.
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Affiliation(s)
- Ana Coito
- Department of NeurologyCantonal Hospital AarauAarauSwitzerland
| | - Silke Biethahn
- Department of NeurologyCantonal Hospital AarauAarauSwitzerland
| | | | | | - Ulrich Roelcke
- Department of Neurology and Brain Tumor CenterCantonal Hospital AarauAarauSwitzerland
| | - Margitta Seeck
- Department of NeurologyUniversity Hospital GenevaGenevaSwitzerland
| | - Pieter van Mierlo
- Department of Electronics and Information SystemsGhent UniversityGhentBelgium
| | - Markus Gschwind
- Department of NeurologyCantonal Hospital AarauAarauSwitzerland
| | - Serge Vulliemoz
- Department of NeurologyUniversity Hospital GenevaGenevaSwitzerland
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He B, Astolfi L, Valdés-Sosa PA, Marinazzo D, Palva SO, Bénar CG, Michel CM, Koenig T. Electrophysiological Brain Connectivity: Theory and Implementation. IEEE Trans Biomed Eng 2019; 66:10.1109/TBME.2019.2913928. [PMID: 31071012 PMCID: PMC6834897 DOI: 10.1109/tbme.2019.2913928] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
We review the theory and algorithms of electrophysiological brain connectivity analysis. This tutorial is aimed at providing an introduction to brain functional connectivity from electrophysiological signals, including electroencephalography (EEG), magnetoencephalography (MEG), electrocorticography (ECoG), stereoelectroencephalography (SEEG). Various connectivity estimators are discussed, and algorithms introduced. Important issues for estimating and mapping brain functional connectivity with electrophysiology are discussed.
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Affiliation(s)
- Bin He
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, USA
| | - Laura Astolfi
- Department of Computer, Control and Management Engineering, University of Rome Sapienza, and with IRCCS Fondazione Santa Lucia, Rome, Italy
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Michel CM, Brunet D. EEG Source Imaging: A Practical Review of the Analysis Steps. Front Neurol 2019; 10:325. [PMID: 31019487 PMCID: PMC6458265 DOI: 10.3389/fneur.2019.00325] [Citation(s) in RCA: 282] [Impact Index Per Article: 56.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Accepted: 03/15/2019] [Indexed: 11/13/2022] Open
Abstract
The electroencephalogram (EEG) is one of the oldest technologies to measure neuronal activity of the human brain. It has its undisputed value in clinical diagnosis, particularly (but not exclusively) in the identification of epilepsy and sleep disorders and in the evaluation of dysfunctions in sensory transmission pathways. With the advancement of digital technologies, the analysis of EEG has moved from pure visual inspection of amplitude and frequency modulations over time to a comprehensive exploration of the temporal and spatial characteristics of the recorded signals. Today, EEG is accepted as a powerful tool to capture brain function with the unique advantage of measuring neuronal processes in the time frame in which these processes occur, namely in the sub-second range. However, it is generally stated that EEG suffers from a poor spatial resolution that makes it difficult to infer to the location of the brain areas generating the neuronal activity measured on the scalp. This statement has challenged a whole community of biomedical engineers to offer solutions to localize more precisely and more reliably the generators of the EEG activity. High-density EEG systems combined with precise information of the head anatomy and sophisticated source localization algorithms now exist that convert the EEG to a true neuroimaging modality. With these tools in hand and with the fact that EEG still remains versatile, inexpensive and portable, electrical neuroimaging has become a widely used technology to study the functions of the pathological and healthy human brain. However, several steps are needed to pass from the recording of the EEG to 3-dimensional images of neuronal activity. This review explains these different steps and illustrates them in a comprehensive analysis pipeline integrated in a stand-alone freely available academic software: Cartool. The information about how the different steps are performed in Cartool is only meant as a suggestion. Other EEG source imaging software may apply similar or different approaches to the different steps.
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Affiliation(s)
- Christoph M. Michel
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
- Center for Biomedical Imaging Lausanne-Geneva (CIBM), Geneva, Switzerland
| | - Denis Brunet
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
- Center for Biomedical Imaging Lausanne-Geneva (CIBM), Geneva, Switzerland
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Coll SY, Vuichoud N, Grandjean D, James CE. Electrical Neuroimaging of Music Processing in Pianists With and Without True Absolute Pitch. Front Neurosci 2019; 13:142. [PMID: 30967751 PMCID: PMC6424903 DOI: 10.3389/fnins.2019.00142] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 02/07/2019] [Indexed: 11/24/2022] Open
Abstract
True absolute pitch (AP), labeling of pitches with semitone precision without a reference, is classically studied using isolated tones. However, AP is acquired and has its function within complex dynamic musical contexts. Here we examined event-related brain responses and underlying cerebral sources to endings of short expressive string quartets, investigating a homogeneous population of young highly trained pianists with half of them possessing true-AP. The pieces ended regularly or contained harmonic transgressions at closure that participants appraised. Given the millisecond precision of ERP analyses, this experimental plan allowed examining whether AP alters music processing at an early perceptual, or later cognitive level, or both, and which cerebral sources underlie differences with non-AP musicians. We also investigated the impact of AP on general auditory cognition. Remarkably, harmonic transgression sensitivity did not differ between AP and non-AP participants, and differences for auditory cognition were only marginal. The key finding of this study is the involvement of a microstate peaking around 60 ms after musical closure, characterizing AP participants. Concurring sources were estimated in secondary auditory areas, comprising the planum temporale, all transgression conditions collapsed. These results suggest that AP is not a panacea to become a proficient musician, but a rare perceptual feature.
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Affiliation(s)
- Sélim Yahia Coll
- Neuroscience of Emotion and Affective Dynamics Laboratory Faculty of Psychology and Educational Sciences and Swiss Centre for Affective Sciences, University of Geneva, Geneva, Switzerland
| | - Noémi Vuichoud
- Neuroscience of Emotion and Affective Dynamics Laboratory Faculty of Psychology and Educational Sciences and Swiss Centre for Affective Sciences, University of Geneva, Geneva, Switzerland
| | - Didier Grandjean
- Neuroscience of Emotion and Affective Dynamics Laboratory Faculty of Psychology and Educational Sciences and Swiss Centre for Affective Sciences, University of Geneva, Geneva, Switzerland
| | - Clara Eline James
- Neuroscience of Emotion and Affective Dynamics Laboratory Faculty of Psychology and Educational Sciences and Swiss Centre for Affective Sciences, University of Geneva, Geneva, Switzerland.,School of Health Sciences Geneva HES-SO University of Applied Sciences and Arts Western Switzerland, Geneva, Switzerland.,Geneva Neuroscience Center University of Geneva, Geneva, Switzerland
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Electroencephalography, magnetoencephalography and source localization: their value in epilepsy. Curr Opin Neurol 2019; 31:176-183. [PMID: 29432218 DOI: 10.1097/wco.0000000000000545] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
PURPOSE OF REVIEW Source localization of cerebral activity using electroencephalography (EEG) or magnetoencephalography (MEG) can reveal noninvasively the generators of the abnormal signals recorded in epilepsy, such as interictal epileptic discharges (IEDs) and seizures. Here, we review recent progress showcasing the usefulness of these techniques in treating patients with drug-resistant epilepsy. RECENT FINDINGS The source localization of IEDs by high-density EEG and MEG has now been proved in large patient cohorts to be accurate and clinically relevant, with positive and negative predictive values rivaling those of structural MRI. Localizing seizure onsets is an emerging technique that seems to perform similarly well to the localization of interictal spikes, although there remain questions regarding the processing of signals for reliable results. The localization of somatosensory cortex using EEG/MEG is well established. The localization of language cortex is less reliable, although progress has been made regarding hemispheric lateralization. Source localization is also able to reveal how epilepsy alters the dynamics of neuronal activity in the large-scale networks that underlie cerebral function. SUMMARY Given the high performance of EEG/MEG source localization, these tools should find a place similar to that of established techniques like MRI in the assessment of patients for epilepsy surgery.
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Seeber M, Cantonas LM, Hoevels M, Sesia T, Visser-Vandewalle V, Michel CM. Subcortical electrophysiological activity is detectable with high-density EEG source imaging. Nat Commun 2019; 10:753. [PMID: 30765707 PMCID: PMC6376013 DOI: 10.1038/s41467-019-08725-w] [Citation(s) in RCA: 153] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 01/28/2019] [Indexed: 11/09/2022] Open
Abstract
Subcortical neuronal activity is highly relevant for mediating communication in large-scale brain networks. While electroencephalographic (EEG) recordings provide appropriate temporal resolution and coverage to study whole brain dynamics, the feasibility to detect subcortical signals is a matter of debate. Here, we investigate if scalp EEG can detect and correctly localize signals recorded with intracranial electrodes placed in the centromedial thalamus, and in the nucleus accumbens. Externalization of deep brain stimulation (DBS) electrodes, placed in these regions, provides the unique opportunity to record subcortical activity simultaneously with high-density (256 channel) scalp EEG. In three patients during rest with eyes closed, we found significant correlation between alpha envelopes derived from intracranial and EEG source reconstructed signals. Highest correlation was found for source signals in close proximity to the actual recording sites, given by the DBS electrode locations. Therefore, we present direct evidence that scalp EEG indeed can sense subcortical signals. Electroencephalography (EEG) allows the measurement of electrical signals associated with brain activity, but it is unclear if EEG can accurately measure subcortical activity. Here, the authors show that source dynamics, reconstructed from scalp EEG, correlate with activity recorded from human thalamus and nucleus accumbens.
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Affiliation(s)
- Martin Seeber
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, Campus Biotech, University of Geneva, 1201, Geneva, Switzerland
| | - Lucia-Manuela Cantonas
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, Campus Biotech, University of Geneva, 1201, Geneva, Switzerland
| | - Mauritius Hoevels
- Department of Stereotactic and Functional Neurosurgery, University of Cologne, 50937, Cologne, Germany
| | - Thibaut Sesia
- Department of Stereotactic and Functional Neurosurgery, University of Cologne, 50937, Cologne, Germany
| | - Veerle Visser-Vandewalle
- Department of Stereotactic and Functional Neurosurgery, University of Cologne, 50937, Cologne, Germany
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, Campus Biotech, University of Geneva, 1201, Geneva, Switzerland. .,Center for Biomedical Imaging (CIBM), Lausanne and Geneva, 1015 Lausanne, Switzerland.
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60
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Large-Scale 3-5 Hz Oscillation Constrains the Expression of Neocortical Fast Ripples in a Mouse Model of Mesial Temporal Lobe Epilepsy. eNeuro 2019; 6:eN-CFN-0494-18. [PMID: 30783615 PMCID: PMC6378326 DOI: 10.1523/eneuro.0494-18.2019] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Revised: 01/21/2019] [Accepted: 01/24/2019] [Indexed: 01/12/2023] Open
Abstract
Large-scale slow oscillations allow the integration of neuronal activity across brain regions during sensory or cognitive processing. However, evidence that this form of coding also holds for pathological networks, such as for distributed networks in epileptic disorders, does not yet exist. Here, we show in a mouse model of unilateral hippocampal epilepsy that epileptic fast ripples generated in the neocortex distant from the primary focus occur during transient trains of interictal epileptic discharges. During these epileptic paroxysms, local phase-locking of neuronal firing and a phase-amplitude coupling of the epileptic discharges over a slow oscillation at 3-5 Hz are detected. Furthermore, the buildup of the slow oscillation begins in the bihippocampal network that includes the focus, which synchronizes and drives the activity across the large-scale epileptic network into the frontal cortex. This study provides the first functional description of the emergence of neocortical fast ripples in hippocampal epilepsy and shows that cross-frequency coupling might be a fundamental mechanism underlying the spreading of epileptic activity.
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Mouthaan BE, Rados M, Boon P, Carrette E, Diehl B, Jung J, Kimiskidis V, Kobulashvili T, Kuchukhidze G, Larsson PG, Leitinger M, Ryvlin P, Rugg-Gunn F, Seeck M, Vulliémoz S, Huiskamp G, Leijten FSS, Van Eijsden P, Trinka E, Braun KPJ. Diagnostic accuracy of interictal source imaging in presurgical epilepsy evaluation: A systematic review from the E-PILEPSY consortium. Clin Neurophysiol 2019; 130:845-855. [PMID: 30824202 DOI: 10.1016/j.clinph.2018.12.016] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2018] [Revised: 11/16/2018] [Accepted: 12/20/2018] [Indexed: 10/27/2022]
Abstract
OBJECTIVE Interictal high resolution (HR-) electric source imaging (ESI) and magnetic source imaging (MSI) are non-invasive tools to aid epileptogenic zone localization in epilepsy surgery candidates. We carried out a systematic review on the diagnostic accuracy and quality of evidence of these modalities. METHODS Embase, Pubmed and the Cochrane database were searched on 13 February 2017. Diagnostic accuracy studies taking post-surgical seizure outcome as reference standard were selected. Quality appraisal was based on the QUADAS-2 framework. RESULTS Eleven studies were included: eight MSI (n = 267), three HR-ESI (n = 127) studies. None was free from bias. This mostly involved: selection of operated patients only, interference of source imaging with surgical decision, and exclusion of indeterminate results. Summary sensitivity and specificity estimates were 82% (95% CI: 75-88%) and 53% (95% CI: 37-68%) for overall source imaging, with no statistical difference between MSI and HR-ESI. Specificity is higher when partially concordant results were included as non-concordant (p < 0.05). Inclusion of indeterminate test results as non-concordant lowered sensitivity (p < 0.05). CONCLUSIONS Source imaging has a relatively high sensitivity but low specificity for identification of the epileptogenic zone. SIGNIFICANCE We need higher quality studies allowing unbiased test evaluation to determine the added value and diagnostic accuracy of source imaging in the presurgical workup of refractory focal epilepsy.
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Affiliation(s)
- Brian E Mouthaan
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, PO Box 85090, 3508 AB Utrecht, The Netherlands
| | - Matea Rados
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, PO Box 85090, 3508 AB Utrecht, The Netherlands
| | - Paul Boon
- Reference Center for Refractory Epilepsy, Department of Neurology, Ghent University Hospital, Belgium
| | - Evelien Carrette
- Reference Center for Refractory Epilepsy, Department of Neurology, Ghent University Hospital, Belgium
| | - Beate Diehl
- National Hospital for Neurology and Neurosurgery, University College London Hospitals, London, United Kingdom; Department of Clinical and Experimental Epilepsy, University College, London, UK
| | - Julien Jung
- Department of Functional Neurology and Epileptology, Institute of Epilepsies (IDEE), Hospices Civils de Lyon, Lyon, France
| | - Vasilios Kimiskidis
- Laboratory of Clinical Neurophysiology, Medical School, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece
| | - Teia Kobulashvili
- Department of Neurology, Christian-Doppler University Hospital, Paracelsus Medical University, and Centre for Cognitive Neuroscience, Salzburg, Austria
| | - Giorgi Kuchukhidze
- Department of Neurology, Christian-Doppler University Hospital, Paracelsus Medical University, and Centre for Cognitive Neuroscience, Salzburg, Austria
| | - Pål G Larsson
- Department of Neurosurgery, Clinic of Surgery and Neuroscience, Oslo University Hospital, Norway
| | - Markus Leitinger
- Department of Neurology, Christian-Doppler University Hospital, Paracelsus Medical University, and Centre for Cognitive Neuroscience, Salzburg, Austria
| | - Philippe Ryvlin
- Department of Clinical Neurosciences, Lausanne University Hospital, Lausanne, Switzerland
| | - Fergus Rugg-Gunn
- National Hospital for Neurology and Neurosurgery, University College London Hospitals, London, United Kingdom; Department of Clinical and Experimental Epilepsy, University College, London, UK
| | - Margitta Seeck
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, University Hospital of Geneva, Switzerland
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, University Hospital of Geneva, Switzerland
| | - Geertjan Huiskamp
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, PO Box 85090, 3508 AB Utrecht, The Netherlands
| | - Frans S S Leijten
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, PO Box 85090, 3508 AB Utrecht, The Netherlands
| | - Pieter Van Eijsden
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, PO Box 85090, 3508 AB Utrecht, The Netherlands
| | - Eugen Trinka
- Department of Neurology, Christian-Doppler University Hospital, Paracelsus Medical University, and Centre for Cognitive Neuroscience, Salzburg, Austria; Institute of Public Health, Medical Decision Making and HTA, UMIT, Private University for Health Sciences, Medical Informatics and Technology, Hall in Tyrol, Austria
| | - Kees P J Braun
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, PO Box 85090, 3508 AB Utrecht, The Netherlands.
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Tamilia E, AlHilani M, Tanaka N, Tsuboyama M, Peters JM, Grant PE, Madsen JR, Stufflebeam SM, Pearl PL, Papadelis C. Assessing the localization accuracy and clinical utility of electric and magnetic source imaging in children with epilepsy. Clin Neurophysiol 2019; 130:491-504. [PMID: 30771726 DOI: 10.1016/j.clinph.2019.01.009] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 12/07/2018] [Accepted: 01/08/2019] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To evaluate the accuracy and clinical utility of conventional 21-channel EEG (conv-EEG), 72-channel high-density EEG (HD-EEG) and 306-channel MEG in localizing interictal epileptiform discharges (IEDs). METHODS Twenty-four children who underwent epilepsy surgery were studied. IEDs on conv-EEG, HD-EEG, MEG and intracranial EEG (iEEG) were localized using equivalent current dipoles and dynamical statistical parametric mapping (dSPM). We compared the localization error (ELoc) with respect to the ground-truth Irritative Zone (IZ), defined by iEEG sources, between non-invasive modalities and the distance from resection (Dres) between good- (Engel 1) and poor-outcomes. For each patient, we estimated the resection percentage of IED sources and tested whether it predicted outcome. RESULTS MEG presented lower ELoc than HD-EEG and conv-EEG. For all modalities, Dres was shorter in good-outcome than poor-outcome patients, but only the resection percentage of the ground-truth IZ and MEG-IZ predicted surgical outcome. CONCLUSIONS MEG localizes the IZ more accurately than conv-EEG and HD-EEG. MSI may help the presurgical evaluation in terms of patient's outcome prediction. The promising clinical value of ESI for both conv-EEG and HD-EEG prompts the use of higher-density EEG-systems to possibly achieve MEG performance. SIGNIFICANCE Localizing the IZ non-invasively with MSI/ESI facilitates presurgical evaluation and surgical prognosis assessment.
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Affiliation(s)
- Eleonora Tamilia
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michel AlHilani
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Naoaki Tanaka
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Sapporo Neuroimaging Research Group, Sapporo, Japan
| | - Melissa Tsuboyama
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jurriaan M Peters
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, USA
| | - Steven M Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christos Papadelis
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
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Maharathi B, Wlodarski R, Bagla S, Asano E, Hua J, Patton J, Loeb JA. Interictal spike connectivity in human epileptic neocortex. Clin Neurophysiol 2018; 130:270-279. [PMID: 30605889 DOI: 10.1016/j.clinph.2018.11.025] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Revised: 11/09/2018] [Accepted: 11/22/2018] [Indexed: 12/20/2022]
Abstract
OBJECTIVE Interictal spikes are a biomarker of epilepsy, yet their precise roles are poorly understood. Using long-term neocortical recordings from epileptic patients, we investigated the spatial-temporal propagation patterns of interictal spiking. METHODS Interictal spikes were detected in 10 epileptic patients. Short time direct directed transfer function was used to map the spatial-temporal patterns of interictal spike onset and propagation across different cortical topographies. RESULTS Each patient had unique interictal spike propagation pattern that was highly consistent across times, regardless of the frequency band. High spiking brain regions were often not spike onset regions. We observed frequent spike propagations to shorter distances and that the central sulcus forms a strong barrier to spike propagation. Spike onset and seizure onset seemed to be distinct networks in most cases. CONCLUSIONS Patients in epilepsy have distinct and unique network of causal propagation pattern which are very consistent revealing the underlying epileptic network. Although spike are epileptic biomarkers, spike origin and seizure onset seems to be distinct in most cases. SIGNIFICANCE Understanding patterns of interictal spike propagation could lead to the identification patient-specific epileptic networks amenable to surgical or other treatments.
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Affiliation(s)
- Biswajit Maharathi
- Department of Neurology and Rehabilitation, University of Illinois, Chicago, IL, United States; Department of Bioengineering, University of Illinois, Chicago, IL, United States
| | - Richard Wlodarski
- Department of Neurology and Rehabilitation, University of Illinois, Chicago, IL, United States
| | - Shruti Bagla
- Department of and Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, United States
| | - Eishi Asano
- Department of Pediatrics, Wayne State University, Detroit, MI, United States; Department of Neurology, Wayne State University, Detroit, MI, United States
| | - Jing Hua
- Department of Computer Science, Wayne State University, Detroit, MI, United States
| | - James Patton
- Department of Bioengineering, University of Illinois, Chicago, IL, United States
| | - Jeffrey A Loeb
- Department of Neurology and Rehabilitation, University of Illinois, Chicago, IL, United States.
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Rubega M, Carboni M, Seeber M, Pascucci D, Tourbier S, Toscano G, Van Mierlo P, Hagmann P, Plomp G, Vulliemoz S, Michel CM. Estimating EEG Source Dipole Orientation Based on Singular-value Decomposition for Connectivity Analysis. Brain Topogr 2018; 32:704-719. [PMID: 30511174 DOI: 10.1007/s10548-018-0691-2] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Accepted: 11/29/2018] [Indexed: 12/14/2022]
Abstract
In the last decade, the use of high-density electrode arrays for EEG recordings combined with the improvements of source reconstruction algorithms has allowed the investigation of brain networks dynamics at a sub-second scale. One powerful tool for investigating large-scale functional brain networks with EEG is time-varying effective connectivity applied to source signals obtained from electric source imaging. Due to computational and interpretation limitations, the brain is usually parcelled into a limited number of regions of interests (ROIs) before computing EEG connectivity. One specific need and still open problem is how to represent the time- and frequency-content carried by hundreds of dipoles with diverging orientation in each ROI with one unique representative time-series. The main aim of this paper is to provide a method to compute a signal that explains most of the variability of the data contained in each ROI before computing, for instance, time-varying connectivity. As the representative time-series for a ROI, we propose to use the first singular vector computed by a singular-value decomposition of all dipoles belonging to the same ROI. We applied this method to two real datasets (visual evoked potentials and epileptic spikes) and evaluated the time-course and the frequency content of the obtained signals. For each ROI, both the time-course and the frequency content of the proposed method reflected the expected time-course and the scalp-EEG frequency content, representing most of the variability of the sources (~ 80%) and improving connectivity results in comparison to other procedures used so far. We also confirm these results in a simulated dataset with a known ground truth.
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Affiliation(s)
- M Rubega
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland.
| | - M Carboni
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland.,EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - M Seeber
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland
| | - D Pascucci
- Perceptual Networks Group, Department of Psychology, University of Fribourg, Fribourg, Switzerland
| | - S Tourbier
- Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - G Toscano
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland.,Unit of Sleep Medicine and Epilepsy, C. Mondino National Neurological Institute, Pavia, Italy
| | - P Van Mierlo
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland.,Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - P Hagmann
- Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - G Plomp
- Perceptual Networks Group, Department of Psychology, University of Fribourg, Fribourg, Switzerland
| | - S Vulliemoz
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - C M Michel
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202, Geneva, Switzerland.,Lemanic Biomedical Imaging Centre (CIBM), Lausanne, Geneva, Switzerland
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Compressibility of High-Density EEG Signals in Stroke Patients. SENSORS 2018; 18:s18124107. [PMID: 30477168 PMCID: PMC6308673 DOI: 10.3390/s18124107] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 11/15/2018] [Accepted: 11/18/2018] [Indexed: 02/05/2023]
Abstract
Stroke is a critical event that causes the disruption of neural connections. There is increasing evidence that the brain tries to reorganize itself and to replace the damaged circuits, by establishing compensatory pathways. Intra- and extra-cellular currents are involved in the communication between neurons and the macroscopic effects of such currents can be detected at the scalp through electroencephalographic (EEG) sensors. EEG can be used to study the lesions in the brain indirectly, by studying their effects on the brain electrical activity. The primary goal of the present work was to investigate possible asymmetries in the activity of the two hemispheres, in the case one of them is affected by a lesion due to stroke. In particular, the compressibility of High-Density-EEG (HD-EEG) recorded at the two hemispheres was investigated since the presence of the lesion is expected to impact on the regularity of EEG signals. The secondary objective was to evaluate if standard low density EEG is able to provide such information. Eighteen patients with unilateral stroke were recruited and underwent HD-EEG recording. Each EEG signal was compressively sensed, using Block Sparse Bayesian Learning, at increasing compression rate. The two hemispheres showed significant differences in the compressibility of EEG. Signals acquired at the electrode locations of the affected hemisphere showed a better reconstruction quality, quantified by the Structural SIMilarity index (SSIM), than the EEG signals recorded at the healthy hemisphere (p < 0.05), for each compression rate value. The presence of the lesion seems to induce an increased regularity in the electrical activity of the brain, thus an increased compressibility.
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68
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Baroumand AG, van Mierlo P, Strobbe G, Pinborg LH, Fabricius M, Rubboli G, Leffers AM, Uldall P, Jespersen B, Brennum J, Henriksen OM, Beniczky S. Automated EEG source imaging: A retrospective, blinded clinical validation study. Clin Neurophysiol 2018; 129:2403-2410. [DOI: 10.1016/j.clinph.2018.09.015] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 08/21/2018] [Accepted: 09/15/2018] [Indexed: 11/16/2022]
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69
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Coito A, Michel CM, Vulliemoz S, Plomp G. Directed functional connections underlying spontaneous brain activity. Hum Brain Mapp 2018; 40:879-888. [PMID: 30367722 DOI: 10.1002/hbm.24418] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Revised: 09/13/2018] [Accepted: 10/02/2018] [Indexed: 11/06/2022] Open
Abstract
Neuroimaging studies have shown that spontaneous brain activity is characterized as changing networks of coherent activity across multiple brain areas. However, the directionality of functional interactions between the most active regions in our brain at rest remains poorly understood. Here, we examined, at the whole-brain scale, the main drivers and directionality of interactions that underlie spontaneous human brain activity by applying directed functional connectivity analysis to electroencephalography (EEG) source signals. We found that the main drivers of electrophysiological activity were the posterior cingulate cortex (PCC), the medial temporal lobes (MTL), and the anterior cingulate cortex (ACC). Among those regions, the PCC was the strongest driver and had both the highest integration and segregation importance, followed by the MTL regions. The driving role of the PCC and MTL resulted in an effective directed interaction directed from posterior toward anterior brain regions. Our results strongly suggest that the PCC and MTL structures are the main drivers of electrophysiological spontaneous activity throughout the brain and suggest that EEG-based directed functional connectivity analysis is a promising tool to better understand the dynamics of spontaneous brain activity in healthy subjects and in various brain disorders.
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Affiliation(s)
- Ana Coito
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - Gijs Plomp
- Perceptual Networks Group, Department of Psychology, University of Fribourg, Fribourg, Switzerland
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70
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Kuo CC, Tucker DM, Luu P, Jenson K, Tsai JJ, Ojemann JG, Holmes MD. EEG source imaging of epileptic activity at seizure onset. Epilepsy Res 2018; 146:160-171. [DOI: 10.1016/j.eplepsyres.2018.07.006] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 07/06/2018] [Accepted: 07/16/2018] [Indexed: 01/16/2023]
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71
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Sharma P, Scherg M, Pinborg LH, Fabricius M, Rubboli G, Pedersen B, Leffers AM, Uldall P, Jespersen B, Brennum J, Henriksen OM, Beniczky S. Ictal and interictal electric source imaging in pre-surgical evaluation: a prospective study. Eur J Neurol 2018; 25:1154-1160. [DOI: 10.1111/ene.13676] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Accepted: 05/03/2018] [Indexed: 12/01/2022]
Affiliation(s)
- P. Sharma
- Department of Clinical Neurophysiology; Danish Epilepsy Centre; Dianalund Denmark
- Department of Neurology; King George's Medical University; Lucknow India
| | - M. Scherg
- Research Department; BESA GmbH; Gräfelfing Germany
| | - L. H. Pinborg
- Department of Neurology; Copenhagen University Hospital Rigshospitalet; Copenhagen
- Neurobiology Research Unit; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - M. Fabricius
- Department of Clinical Neurophysiology; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - G. Rubboli
- Department of Neurology; Danish Epilepsy Centre; Dianalund
| | - B. Pedersen
- Department of Neurology; Danish Epilepsy Centre; Dianalund
| | - A.-M. Leffers
- Department of Diagnostic Radiology; Hvidovre Hospital; Hvidovre
| | - P. Uldall
- Department of Paediatrics, Child Neurology; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - B. Jespersen
- Department of Neurosurgery; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - J. Brennum
- Department of Neurosurgery; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - O. M. Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - S. Beniczky
- Department of Clinical Neurophysiology; Danish Epilepsy Centre; Dianalund Denmark
- Department of Clinical Neurophysiology; Aarhus University Hospital; Aarhus Denmark
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Tatum W, Rubboli G, Kaplan P, Mirsatari S, Radhakrishnan K, Gloss D, Caboclo L, Drislane F, Koutroumanidis M, Schomer D, Kasteleijn-Nolst Trenite D, Cook M, Beniczky S. Clinical utility of EEG in diagnosing and monitoring epilepsy in adults. Clin Neurophysiol 2018; 129:1056-1082. [DOI: 10.1016/j.clinph.2018.01.019] [Citation(s) in RCA: 76] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2017] [Revised: 12/28/2017] [Accepted: 01/09/2018] [Indexed: 12/20/2022]
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Koren J, Gritsch G, Pirker S, Herta J, Perko H, Kluge T, Baumgartner C. Automatic ictal onset source localization in presurgical epilepsy evaluation. Clin Neurophysiol 2018; 129:1291-1299. [PMID: 29680731 DOI: 10.1016/j.clinph.2018.03.020] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 03/07/2018] [Accepted: 03/24/2018] [Indexed: 10/17/2022]
Abstract
OBJECTIVE To test the diagnostic accuracy of a new automatic algorithm for ictal onset source localization (IOSL) during routine presurgical epilepsy evaluation following STARD (Standards for Reporting of Diagnostic Accuracy) criteria. METHODS We included 28 consecutive patients with refractory focal epilepsy (25 patients with temporal lobe epilepsy (TLE) and 3 with extratemporal epilepsy) who underwent resective epilepsy surgery. Ictal EEG patterns were analyzed with a novel automatic IOSL algorithm. IOSL source localizations on a sublobar level were validated by comparison with actual resection sites and seizure free outcome 2 years after surgery. RESULTS Sensitivity of IOSL was 92.3% (TLE: 92.3%); specificity 60% (TLE: 50%); positive predictive value 66.7% (TLE: 66.7%); and negative predictive value 90% (TLE: 85.7%). The likelihood ratio was more than ten times higher for concordant IOSL results as compared to discordant results (p = 0.013). CONCLUSIONS We demonstrated the clinical feasibility of our IOSL approach yielding reasonable high performance measures on a sublobar level. SIGNIFICANCE Our IOSL method may contribute to a correct localization of the seizure onset zone in temporal lobe epilepsy and can readily be used in standard epilepsy monitoring settings. Further studies are needed for validation in extratemporal epilepsy.
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Affiliation(s)
- Johannes Koren
- Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Neurological Department, General Hospital Hietzing with Neurological Center Rosenhügel, Vienna, Austria
| | - Gerhard Gritsch
- Austrian Institute of Technology GmbH (AIT), Safety & Security Department, Vienna, Austria
| | - Susanne Pirker
- Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Neurological Department, General Hospital Hietzing with Neurological Center Rosenhügel, Vienna, Austria
| | - Johannes Herta
- Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Hannes Perko
- Austrian Institute of Technology GmbH (AIT), Safety & Security Department, Vienna, Austria
| | - Tilmann Kluge
- Austrian Institute of Technology GmbH (AIT), Safety & Security Department, Vienna, Austria
| | - Christoph Baumgartner
- Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Neurological Department, General Hospital Hietzing with Neurological Center Rosenhügel, Vienna, Austria; Department of Epileptology and Clinical Neurophysiology, Sigmund Freud University, Vienna, Austria.
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Khachatryan E, Brouwer H, Staljanssens W, Carrette E, Meurs A, Boon P, Van Roost D, Van Hulle MM. A new insight into sentence comprehension: The impact of word associations in sentence processing as shown by invasive EEG recording. Neuropsychologia 2018; 108:103-116. [PMID: 29203203 DOI: 10.1016/j.neuropsychologia.2017.12.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2017] [Revised: 11/20/2017] [Accepted: 12/01/2017] [Indexed: 11/26/2022]
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75
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James CE, Oechslin MS, Michel CM, De Pretto M. Electrical Neuroimaging of Music Processing Reveals Mid-Latency Changes with Level of Musical Expertise. Front Neurosci 2017; 11:613. [PMID: 29163017 PMCID: PMC5682036 DOI: 10.3389/fnins.2017.00613] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 10/20/2017] [Indexed: 11/28/2022] Open
Abstract
This original research focused on the effect of musical training intensity on cerebral and behavioral processing of complex music using high-density event-related potential (ERP) approaches. Recently we have been able to show progressive changes with training in gray and white matter, and higher order brain functioning using (f)MRI [(functional) Magnetic Resonance Imaging], as well as changes in musical and general cognitive functioning. The current study investigated the same population of non-musicians, amateur pianists and expert pianists using spatio-temporal ERP analysis, by means of microstate analysis, and ERP source imaging. The stimuli consisted of complex musical compositions containing three levels of transgression of musical syntax at closure that participants appraised. ERP waveforms, microstates and underlying brain sources revealed gradual differences according to musical expertise in a 300–500 ms window after the onset of the terminal chords of the pieces. Within this time-window, processing seemed to concern context-based memory updating, indicated by a P3b-like component or microstate for which underlying sources were localized in the right middle temporal gyrus, anterior cingulate and right parahippocampal areas. Given that the 3 expertise groups were carefully matched for demographic factors, these results provide evidence of the progressive impact of training on brain and behavior.
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Affiliation(s)
- Clara E James
- School of Health Sciences, University of Applied Sciences and Arts Western Switzerland, Geneva, Switzerland.,Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland.,Neuroscience Center, University of Geneva, Geneva, Switzerland
| | - Mathias S Oechslin
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland.,Department of Education and Culture of the Canton of Thurgau, Frauenfeld, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland.,Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Michael De Pretto
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland.,Neurology Unit, Medicine Department, Faculty of Sciences, University of Fribourg, Fribourg, Switzerland
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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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78
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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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79
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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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80
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Khoo HM, Hao Y, von Ellenrieder N, Zazubovits N, Hall J, Olivier A, Dubeau F, Gotman J. The hemodynamic response to interictal epileptic discharges localizes the seizure-onset zone. Epilepsia 2017; 58:811-823. [DOI: 10.1111/epi.13717] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/07/2017] [Indexed: 01/14/2023]
Affiliation(s)
- Hui Ming Khoo
- Montreal Neurological Institute and Hospital; McGill University; Montreal Quebec Canada
- Department of Neurosurgery; Osaka University Graduate School of Medicine; Suita Japan
| | - Yongfu Hao
- Montreal Neurological Institute and Hospital; McGill University; Montreal Quebec Canada
| | | | - Natalja Zazubovits
- Montreal Neurological Institute and Hospital; McGill University; Montreal Quebec Canada
| | - Jeffery Hall
- Montreal Neurological Institute and Hospital; McGill University; Montreal Quebec Canada
| | - André Olivier
- Montreal Neurological Institute and Hospital; McGill University; Montreal Quebec Canada
| | - François Dubeau
- Montreal Neurological Institute and Hospital; McGill University; Montreal Quebec Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital; McGill University; Montreal Quebec Canada
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81
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Staljanssens W, Strobbe G, Holen RV, Birot G, Gschwind M, Seeck M, Vandenberghe S, Vulliémoz S, van Mierlo P. Seizure Onset Zone Localization from Ictal High-Density EEG in Refractory Focal Epilepsy. Brain Topogr 2016; 30:257-271. [PMID: 27853892 DOI: 10.1007/s10548-016-0537-8] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Accepted: 11/04/2016] [Indexed: 10/20/2022]
Abstract
Epilepsy surgery is the most efficient treatment option for patients with refractory epilepsy. Before surgery, it is of utmost importance to accurately delineate the seizure onset zone (SOZ). Non-invasive EEG is the most used neuroimaging technique to diagnose epilepsy, but it is hard to localize the SOZ from EEG due to its low spatial resolution and because epilepsy is a network disease, with several brain regions becoming active during a seizure. In this work, we propose and validate an approach based on EEG source imaging (ESI) combined with functional connectivity analysis to overcome these problems. We considered both simulations and real data of patients. Ictal epochs of 204-channel EEG and subsets down to 32 channels were analyzed. ESI was done using realistic head models and LORETA was used as inverse technique. The connectivity pattern between the reconstructed sources was calculated, and the source with the highest number of outgoing connections was selected as SOZ. We compared this algorithm with a more straightforward approach, i.e. selecting the source with the highest power after ESI as the SOZ. We found that functional connectivity analysis estimated the SOZ consistently closer to the simulated EZ/RZ than localization based on maximal power. Performance, however, decreased when 128 electrodes or less were used, especially in the realistic data. The results show the added value of functional connectivity analysis for SOZ localization, when the EEG is obtained with a high-density setup. Next to this, the method can potentially be used as objective tool in clinical settings.
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Affiliation(s)
- Willeke Staljanssens
- MEDISIP, Department of Electronics and Information Systems, Ghent University, De Pintelaan 185, Building B Entrance 36, 9000, Ghent, Belgium. .,iMinds Medical IT, Ghent, Belgium.
| | - Gregor Strobbe
- MEDISIP, Department of Electronics and Information Systems, Ghent University, De Pintelaan 185, Building B Entrance 36, 9000, Ghent, Belgium.,iMinds Medical IT, Ghent, Belgium
| | - Roel Van Holen
- MEDISIP, Department of Electronics and Information Systems, Ghent University, De Pintelaan 185, Building B Entrance 36, 9000, Ghent, Belgium.,iMinds Medical IT, Ghent, Belgium
| | - Gwénaël Birot
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Geneva, Switzerland
| | - Markus Gschwind
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Geneva, Switzerland.,EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Stefaan Vandenberghe
- MEDISIP, Department of Electronics and Information Systems, Ghent University, De Pintelaan 185, Building B Entrance 36, 9000, Ghent, Belgium.,iMinds Medical IT, Ghent, Belgium
| | - Serge Vulliémoz
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Geneva, Switzerland.,EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Pieter van Mierlo
- MEDISIP, Department of Electronics and Information Systems, Ghent University, De Pintelaan 185, Building B Entrance 36, 9000, Ghent, Belgium.,iMinds Medical IT, Ghent, Belgium.,Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Geneva, Switzerland
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82
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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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83
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Wostyn S, Staljanssens W, De Taeye L, Strobbe G, Gadeyne S, Van Roost D, Raedt R, Vonck K, van Mierlo P. EEG Derived Brain Activity Reflects Treatment Response from Vagus Nerve Stimulation in Patients with Epilepsy. Int J Neural Syst 2016; 27:1650048. [PMID: 27712133 DOI: 10.1142/s0129065716500489] [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] [Indexed: 12/12/2022]
Abstract
The mechanism of action of vagus nerve stimulation (VNS) is yet to be elucidated. To that end, the effects of VNS on the brain of epileptic patients were studied. Both when VNS was switched "On" and "Off", the brain activity of responders (R, seizure frequency reduction of over 50%) was compared to the brain activity of nonresponders (NR, seizure frequency reduction of less than 50%). Using EEG recordings, a significant increase in P300 amplitude for R and a significant decrease in P300 amplitude for NR were found. We found biomarkers for checking the efficacy of VNS with accuracy up to 94%. The results show that P300 features recorded in nonmidline electrodes are better P300 biomarkers for VNS efficacy than P300 features recorded in midline electrodes. Using source localization and connectivity analyses, the activity of the limbic system, insula and orbitofrontal cortex was found to be dependent on VNS switched "On" versus "Off" or patient group (R versus NR). The results suggest an important role for these areas in the mechanism of action of VNS, although a larger patient study should be done to confirm the findings.
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Affiliation(s)
- Simon Wostyn
- * MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium.,† iMinds Medical IT Department, Ghent University, Ghent, Belgium
| | - Willeke Staljanssens
- * MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium.,† iMinds Medical IT Department, Ghent University, Ghent, Belgium
| | - Leen De Taeye
- ‡ LCEN3, Department of Neurology, Ghent University, Ghent, Belgium
| | - Gregor Strobbe
- * MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Stefanie Gadeyne
- ‡ LCEN3, Department of Neurology, Ghent University, Ghent, Belgium
| | - Dirk Van Roost
- § Department of Neurosurgery, Ghent University Hospital, Ghent, Belgium
| | - Robrecht Raedt
- ‡ LCEN3, Department of Neurology, Ghent University, Ghent, Belgium
| | - Kristl Vonck
- ‡ LCEN3, Department of Neurology, Ghent University, Ghent, Belgium
| | - Pieter van Mierlo
- * MEDISIP, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium.,† iMinds Medical IT Department, Ghent University, Ghent, Belgium.,¶ Functional Brain Mapping lab, University of Geneva, Geneva, Switzerland
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84
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Zerouali Y, Pouliot P, Robert M, Mohamed I, Bouthillier A, Lesage F, Nguyen DK. Magnetoencephalographic signatures of insular epileptic spikes based on functional connectivity. Hum Brain Mapp 2016; 37:3250-61. [PMID: 27220112 DOI: 10.1002/hbm.23238] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Revised: 04/19/2016] [Accepted: 04/21/2016] [Indexed: 11/10/2022] Open
Abstract
Failure to recognize insular cortex seizures has recently been identified as a cause of epilepsy surgeries targeting the temporal, parietal, or frontal lobe. Such failures are partly due to the fact that current noninvasive localization techniques fare poorly in recognizing insular epileptic foci. Our group recently demonstrated that magnetoencephalography (MEG) is sensitive to epileptiform spikes generated by the insula. In this study, we assessed the potential of distributed source imaging and functional connectivity analyses to distinguish insular networks underlying the generation of spikes. Nineteen patients with operculo-insular epilepsy were investigated. Each patient underwent MEG as well as T1-weighted magnetic resonance imaging (MRI) as part of their standard presurgical evaluation. Cortical sources of MEG spikes were reconstructed with the maximum entropy on the mean algorithm, and their time courses served to analyze source functional connectivity. The results indicate that the anterior and posterior subregions of the insula have specific patterns of functional connectivity mainly involving frontal and parietal regions, respectively. In addition, while their connectivity patterns are qualitatively similar during rest and during spikes, couplings within these networks are much stronger during spikes. These results show that MEG can establish functional connectivity-based signatures that could help in the diagnosis of different subtypes of insular cortex epilepsy. Hum Brain Mapp 37:3250-3261, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Younes Zerouali
- Département De Génie Électrique, École Polytechnique De Montréal, Montreal, Quebec, Canada.,Research Centre, Centre Hospitalier De L'Université De Montréal (CRCHUM), Montreal, Quebec, Canada
| | - Philippe Pouliot
- Département De Génie Électrique, École Polytechnique De Montréal, Montreal, Quebec, Canada.,Institut De Cardiologie De Montréal, Montreal, Quebec, Canada
| | - Manon Robert
- Research Centre, Centre Hospitalier De L'Université De Montréal (CRCHUM), Montreal, Quebec, Canada
| | - Ismail Mohamed
- Division of Neurology, Department of Pediatrics, IWK Health Centre, Halifax, Nova Scotia, Canada
| | - Alain Bouthillier
- Research Centre, Centre Hospitalier De L'Université De Montréal (CRCHUM), Montreal, Quebec, Canada
| | - Frédéric Lesage
- Département De Génie Électrique, École Polytechnique De Montréal, Montreal, Quebec, Canada.,Institut De Cardiologie De Montréal, Montreal, Quebec, Canada
| | - Dang K Nguyen
- Research Centre, Centre Hospitalier De L'Université De Montréal (CRCHUM), Montreal, Quebec, Canada.,Division of Neurology, Department of Medicine, CHUM - Hôpital Notre-Dame, Montreal, Quebec, Canada
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85
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Iannotti GR, Grouiller F, Centeno M, Carmichael DW, Abela E, Wiest R, Korff C, Seeck M, Michel C, Pittau F, Vulliemoz S. Epileptic networks are strongly connected with and without the effects of interictal discharges. Epilepsia 2016; 57:1086-96. [PMID: 27153929 DOI: 10.1111/epi.13400] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2016] [Indexed: 02/04/2023]
Abstract
OBJECTIVE Epilepsy is increasingly considered as the dysfunction of a pathologic neuronal network (epileptic network) rather than a single focal source. We aimed to assess the interactions between the regions that comprise the epileptic network and to investigate their dependence on the occurrence of interictal epileptiform discharges (IEDs). METHODS We analyzed resting state simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) recordings in 10 patients with drug-resistant focal epilepsy with multifocal IED-related blood oxygen level-dependent (BOLD) responses and a maximum t-value in the IED field. We computed functional connectivity (FC) maps of the epileptic network using two types of seed: (1) a 10-mm diameter sphere centered in the global maximum of IED-related BOLD map, and (2) the independent component with highest correlation to the IED-related BOLD map, named epileptic component. For both approaches, we compared FC maps before and after regressing out the effect of IEDs in terms of maximum and mean t-values and percentage of map overlap. RESULTS Maximum and mean FC maps t-values were significantly lower after regressing out IEDs at the group level (p < 0.01). Overlap extent was 85% ± 12% and 87% ± 12% when the seed was the 10-mm diameter sphere and the epileptic component, respectively. SIGNIFICANCE Regions involved in a specific epileptic network show coherent BOLD fluctuations independent of scalp EEG IEDs. FC topography and strength is largely preserved by removing the IED effect. This could represent a signature of a sustained pathologic network with contribution from epileptic activity invisible to the scalp EEG.
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Affiliation(s)
- Giannina R Iannotti
- Functional Brain Mapping Lab, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Frédéric Grouiller
- Department of Radiology and Medical Informatics, University Hospital of Geneva, Geneva, Switzerland
| | - Maria Centeno
- Developmental Imaging and Biophysics Section, UCL Institute of Child Health, London, United Kingdom
| | - David W Carmichael
- Developmental Imaging and Biophysics Section, UCL Institute of Child Health, London, United Kingdom
| | - Eugenio Abela
- Support Center of Advanced Neuroimaging (SCAN), Institute for Diagnostic and Interventional Neuroradiology, University Hospital Inselspital, Bern, Switzerland
| | - Roland Wiest
- Support Center of Advanced Neuroimaging (SCAN), Institute for Diagnostic and Interventional Neuroradiology, University Hospital Inselspital, Bern, Switzerland
| | - Christian Korff
- Pediatric Neurology, Child and Adolescent Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Margitta Seeck
- Neurology Clinic, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Christoph Michel
- Functional Brain Mapping Lab, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Francesca Pittau
- Neurology Clinic, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- Neurology Clinic, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
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86
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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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87
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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: 193] [Impact Index Per Article: 24.1] [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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88
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Gschwind M, Picard F. Ecstatic Epileptic Seizures: A Glimpse into the Multiple Roles of the Insula. Front Behav Neurosci 2016; 10:21. [PMID: 26924970 PMCID: PMC4756129 DOI: 10.3389/fnbeh.2016.00021] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2015] [Accepted: 02/02/2016] [Indexed: 01/18/2023] Open
Abstract
Ecstatic epileptic seizures are a rare but compelling epileptic entity. During the first seconds of these seizures, ecstatic auras provoke feelings of well-being, intense serenity, bliss, and "enhanced self-awareness." They are associated with the impression of time dilation, and can be described as a mystic experience by some patients. The functional neuroanatomy of ecstatic seizures is still debated. During recent years several patients presenting with ecstatic auras have been reported by others and us (in total n = 52); a few of them in the setting of presurgical evaluation including electrical brain stimulation. According to the recently recognized functions of the insula, and the results of nuclear brain imaging and electrical stimulation, the ecstatic symptoms in these patients seem to localize to a functional network centered around the anterior insular cortex, where we thus propose to locate this rare ictal phenomenon. Here we summarize the role of the multiple sensory, autonomic, affective, and cognitive functions of the insular cortex, which are integrated into the creation of self-awareness, and we suggest how this system may become dysfunctional on several levels during ecstatic aura.
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Affiliation(s)
- Markus Gschwind
- Department of Neurology, University Hospital and Medical School of GenevaGeneva, Switzerland
- Functional Brain Mapping Laboratory, Department of Neuroscience, Biotech Campus, University of GenevaGeneva, Switzerland
| | - Fabienne Picard
- Department of Neurology, University Hospital and Medical School of GenevaGeneva, Switzerland
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89
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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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Lascano AM, Perneger T, Vulliemoz S, Spinelli L, Garibotto V, Korff CM, Vargas MI, Michel CM, Seeck M. Yield of MRI, high-density electric source imaging (HD-ESI), SPECT and PET in epilepsy surgery candidates. Clin Neurophysiol 2016; 127:150-155. [DOI: 10.1016/j.clinph.2015.03.025] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2014] [Revised: 02/09/2015] [Accepted: 03/06/2015] [Indexed: 11/16/2022]
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91
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Schulz R, Scherg M, Woermann F, Bien C. V1. Electric source imaging (ESI) with 10–10 electrodes and individual MRI in presurgical epilepsy monitoring (BESA-Research and BESA-MRI). Clin Neurophysiol 2015. [DOI: 10.1016/j.clinph.2015.04.079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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92
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93
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All-in-one interictal presurgical imaging in patients with epilepsy: single-session EEG/PET/(f)MRI. Eur J Nucl Med Mol Imaging 2015; 42:1133-43. [PMID: 25893383 DOI: 10.1007/s00259-015-3045-2] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Accepted: 03/10/2015] [Indexed: 10/23/2022]
Abstract
PURPOSE In patients with pharmacoresistant focal epilepsy, resection of the epileptic focus can lead to freedom from seizures or significant improvement in well-selected candidates. Localization of the epileptic focus with multimodal concordance is crucial for a good postoperative outcome. Beyond the detection of epileptogenic lesions on structural MRI and focal hypometabolism on FDG PET, EEG-based Electric Source Imaging (ESI) and simultaneous EEG and functional MRI (EEG-fMRI) are increasingly applied for mapping epileptic activity. We here report presurgical multimodal interictal imaging using a hybrid PET/MR scanner for single-session FDG PET, MRI, EEG-fMRI and ESI. METHODS This quadrimodal imaging procedure was performed in a single session in 12 patients using a high-density (256 electrodes) MR-compatible EEG system and a hybrid PET/MR scanner. EEG was used to exclude subclinical seizures during uptake of the PET tracer, to compute ESI on interictal epileptiform discharges and to guide fMRI analysis for mapping haemodynamic changes correlated with interictal epileptiform activity. RESULTS The whole multimodal recording was performed in less than 2 hours with good patient comfort and data quality. Clinically contributory examinations with at least two modalities were obtained in nine patients and with all modalities in five patients. CONCLUSION This single-session quadrimodal imaging procedure provided reliable and contributory interictal clinical data. This procedure avoids multiple scanning sessions and is associated with less radiation exposure than PET-CT. Moreover, it guarantees the same medication level and medical condition for all modalities. The procedure improves workflow and could reduce the duration and cost of presurgical epilepsy evaluations.
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94
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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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95
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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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96
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Sleep affects cortical source modularity in temporal lobe epilepsy: A high-density EEG study. Clin Neurophysiol 2014; 126:1677-83. [PMID: 25666728 DOI: 10.1016/j.clinph.2014.12.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2014] [Revised: 12/04/2014] [Accepted: 12/05/2014] [Indexed: 11/22/2022]
Abstract
OBJECTIVE Interictal epileptiform discharges (IEDs) constitute a perturbation of ongoing cerebral rhythms, usually more frequent during sleep. The aim of the study was to determine whether sleep influences the spread of IEDs over the scalp and whether their distribution depends on vigilance-related modifications in cortical interactions. METHODS Wake and sleep 256-channel electroencephalography (EEG) data were recorded in 12 subjects with right temporal lobe epilepsy (TLE) differentiated by whether they had mesial or neocortical TLE. Spikes were selected during wake and sleep. The averaged waking signal was subtracted from the sleep signal and projected on a bidimensional scalp map; sleep and wake spike distributions were compared by using a t-test. The superimposed signal of sleep and wake traces was obtained; the rising phase of the spike, the peak, and the deflections following the spike were identified, and their cortical generator was calculated using low-resolution brain electromagnetic tomography (LORETA) for each group. RESULTS A mean of 21 IEDs in wake and 39 in sleep per subject were selected. As compared to wake, a larger IED scalp projection was detected during sleep in both mesial and neocortical TLE (p<0.05). A series of EEG deflections followed the spike, the cortical sources of which displayed alternating activations of different cortical areas in wake, substituted by isolated, stationary activations in sleep in mesial TLE and a silencing in neocortical TLE. CONCLUSION During sleep, the IED scalp region increases, while cortical interaction decreases. SIGNIFICANCE The interaction of cortical modules in sleep and wake in TLE may influence the appearance of IEDs on scalp EEG; in addition, IEDs could be proxies for cerebral oscillation perturbation.
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97
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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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Magnetic Source Imaging in Posterior Cortex Epilepsies. Brain Topogr 2014; 28:162-71. [DOI: 10.1007/s10548-014-0412-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Accepted: 10/20/2014] [Indexed: 11/27/2022]
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99
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Kalamangalam GP, Cara L, Tandon N, Slater JD. An interictal EEG spectral metric for temporal lobe epilepsy lateralization. Epilepsy Res 2014; 108:1748-57. [PMID: 25270401 DOI: 10.1016/j.eplepsyres.2014.09.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2014] [Revised: 08/23/2014] [Accepted: 09/06/2014] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Visually-obvious abnormalities in the resting baseline EEG--slowing, spiking and high-frequency oscillations (HFOs)--are cardinal, though incompletely understood, features of the seizure onset zone in focal epilepsy. We hypothesized that evidence of cortical network dysfunction in temporal lobe epilepsy (TLE) would persist in the absence of visually-classifiable abnormalities in the baseline EEG recorded within the conventional passband, and that metrics of such dysfunction could serve as a lateralizing diagnostic in TLE. METHODS Epochs of resting EEG without significant abnormalities in light sleep over several days were compared between a group of 10 patients with proven TLE and 10 subjects without epilepsy. A novel laterality metric computed from the line length of normalized power spectra from the temporal channels was compared between the two groups. RESULTS Significant group differences in spectral line length laterality metric were found between the TLE and control group. At the individual level, seven of 10 TLE patients had highly significant laterality metrics, all concordant with the known laterality of their disease. SIGNIFICANCE Detailed spectral analysis offers novel insight into TLE network behavior, independent of the orthodox abnormalities of EEG slowing, spikes or HFOs. The results may be deployed in a practical diagnostic manner, offer insight into the EEG manifestations of disordered cellular network architecture in TLE, and maybe understood through simple analogy with the theory of linear time-invariant physical systems.
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Affiliation(s)
| | - Lukas Cara
- Department of Neurology, University of Texas Health Science Center, Houston, TX, USA
| | - Nitin Tandon
- Department of Neurosurgery, University of Texas Health Science Center, Houston, TX, USA
| | - Jeremy D Slater
- Department of Neurology, University of Texas Health Science Center, Houston, TX, USA
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100
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High density EEG-what do we have to lose? Clin Neurophysiol 2014; 126:433-4. [PMID: 25113273 DOI: 10.1016/j.clinph.2014.07.003] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2014] [Revised: 06/30/2014] [Accepted: 07/02/2014] [Indexed: 11/22/2022]
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