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Pigorini A, Avanzini P, Barborica A, Bénar CG, David O, Farisco M, Keller CJ, Manfridi A, Mikulan E, Paulk AC, Roehri N, Subramanian A, Vulliémoz S, Zelmann R. Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity. J Neurosci Methods 2024; 408:110160. [PMID: 38734149 DOI: 10.1016/j.jneumeth.2024.110160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 04/10/2024] [Accepted: 05/01/2024] [Indexed: 05/13/2024]
Abstract
Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.
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Affiliation(s)
- Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan, Italy; UOC Maxillo-facial Surgery and dentistry, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, Milan, Italy.
| | - Pietro Avanzini
- Institute of Neuroscience, Consiglio Nazionale delle Ricerche, Parma, Italy
| | | | - Christian-G Bénar
- Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Olivier David
- Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Michele Farisco
- Centre for Research Ethics and Bioethics, Department of Public Health and Caring Sciences, Uppsala University, P.O. Box 256, Uppsala, SE 751 05, Sweden; Science and Society Unit Biogem, Biology and Molecular Genetics Institute, Via Camporeale snc, Ariano Irpino, AV 83031, Italy
| | - Corey J Keller
- Department of Psychiatry & Behavioral Sciences, Stanford University Medical Center, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University Medical Center, Stanford, CA 94305, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA 94394, USA
| | - Alfredo Manfridi
- Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy
| | - Ezequiel Mikulan
- Department of Health Sciences, Università degli Studi di Milano, Milan, Italy
| | - Angelique C Paulk
- Department of Neurology and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicolas Roehri
- EEG and Epilepsy Unit, Dpt of Clinical Neurosciences, Geneva University Hospitals and University of Geneva, Switzerland
| | - Ajay Subramanian
- Department of Psychiatry & Behavioral Sciences, Stanford University Medical Center, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University Medical Center, Stanford, CA 94305, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA 94394, USA
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, Dpt of Clinical Neurosciences, Geneva University Hospitals and University of Geneva, Switzerland
| | - Rina Zelmann
- Department of Neurology and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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Afnan J, Cai Z, Lina JM, Abdallah C, Delaire E, Avigdor T, Ros V, Hedrich T, von Ellenrieder N, Kobayashi E, Frauscher B, Gotman J, Grova C. EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy. Hum Brain Mapp 2024; 45:e26720. [PMID: 38994740 PMCID: PMC11240147 DOI: 10.1002/hbm.26720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 04/16/2024] [Accepted: 05/06/2024] [Indexed: 07/13/2024] Open
Abstract
Electro/Magneto-EncephaloGraphy (EEG/MEG) source imaging (EMSI) of epileptic activity from deep generators is often challenging due to the higher sensitivity of EEG/MEG to superficial regions and to the spatial configuration of subcortical structures. We previously demonstrated the ability of the coherent Maximum Entropy on the Mean (cMEM) method to accurately localize the superficial cortical generators and their spatial extent. Here, we propose a depth-weighted adaptation of cMEM to localize deep generators more accurately. These methods were evaluated using realistic MEG/high-density EEG (HD-EEG) simulations of epileptic activity and actual MEG/HD-EEG recordings from patients with focal epilepsy. We incorporated depth-weighting within the MEM framework to compensate for its preference for superficial generators. We also included a mesh of both hippocampi, as an additional deep structure in the source model. We generated 5400 realistic simulations of interictal epileptic discharges for MEG and HD-EEG involving a wide range of spatial extents and signal-to-noise ratio (SNR) levels, before investigating EMSI on clinical HD-EEG in 16 patients and MEG in 14 patients. Clinical interictal epileptic discharges were marked by visual inspection. We applied three EMSI methods: cMEM, depth-weighted cMEM and depth-weighted minimum norm estimate (MNE). The ground truth was defined as the true simulated generator or as a drawn region based on clinical information available for patients. For deep sources, depth-weighted cMEM improved the localization when compared to cMEM and depth-weighted MNE, whereas depth-weighted cMEM did not deteriorate localization accuracy for superficial regions. For patients' data, we observed improvement in localization for deep sources, especially for the patients with mesial temporal epilepsy, for which cMEM failed to reconstruct the initial generator in the hippocampus. Depth weighting was more crucial for MEG (gradiometers) than for HD-EEG. Similar findings were found when considering depth weighting for the wavelet extension of MEM. In conclusion, depth-weighted cMEM improved the localization of deep sources without or with minimal deterioration of the localization of the superficial sources. This was demonstrated using extensive simulations with MEG and HD-EEG and clinical MEG and HD-EEG for epilepsy patients.
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Affiliation(s)
- Jawata Afnan
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Zhengchen Cai
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Jean-Marc Lina
- Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada
- Electrical Engineering Department, École De Technologie Supérieure, Montréal, Québec, Canada
- Center for Advanced Research in Sleep Medicine, Sacré-Coeur Hospital, Montréal, Québec, Canada
| | - Chifaou Abdallah
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada
- Analytical Neurophysiology Lab, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Edouard Delaire
- Multimodal Functional Imaging Lab, Department of Physics and Concordia School of Health, Concordia University, Montréal, Québec, Canada
| | - Tamir Avigdor
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada
- Analytical Neurophysiology Lab, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Victoria Ros
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Tanguy Hedrich
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
| | - Nicolas von Ellenrieder
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Eliane Kobayashi
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
- Analytical Neurophysiology Lab, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Jean Gotman
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Christophe Grova
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
- Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada
- Multimodal Functional Imaging Lab, Department of Physics and Concordia School of Health, Concordia University, Montréal, Québec, Canada
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Zauli FM, Del Vecchio M, Pigorini A, Russo S, Massimini M, Sartori I, Cardinale F, d'Orio P, Mikulan E. Localizing hidden Interictal Epileptiform Discharges with simultaneous intracerebral and scalp high-density EEG recordings. J Neurosci Methods 2024; 409:110193. [PMID: 38871302 DOI: 10.1016/j.jneumeth.2024.110193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 05/02/2024] [Accepted: 06/08/2024] [Indexed: 06/15/2024]
Abstract
BACKGROUND Scalp EEG is one of the main tools in the clinical evaluation of epilepsy. In some cases intracranial Interictal Epileptiform Discharges (IEDs) are not visible from the scalp. Recent studies have shown the feasibility of revealing them in the EEG if their timings are extracted from simultaneous intracranial recordings, but their potential for the localization of the epileptogenic zone is not yet well defined. NEW METHOD We recorded simultaneous high-density EEG (HD-EEG) and stereo-electroencephalography (SEEG) during interictal periods in 8 patients affected by drug-resistant focal epilepsy. We identified IEDs in the SEEG and systematically analyzed the time-locked signals on the EEG by means of evoked potentials, topographical analysis and Electrical Source Imaging (ESI). The dataset has been standardized and is being publicly shared. RESULTS Our results showed that IEDs that were not clearly visible at single-trials could be uncovered by averaging, in line with previous reports. They also showed that their topographical voltage distributions matched the position of the SEEG electrode where IEDs had been identified, and that ESI techniques can reconstruct it with an accuracy of ∼2 cm. Finally, the present dataset provides a reference to test the accuracy of different methods and parameters. COMPARISON WITH EXISTING METHODS Our study is the first to systematically compare ESI methods on simultaneously recorded IEDs, and to share a public resource with in-vivo data for their evaluation. CONCLUSIONS Simultaneous HD-EEG and SEEG recordings can unveil hidden IEDs whose origins can be reconstructed using topographical and ESI analyses, but results depend on the selected methods and parameters.
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Affiliation(s)
- Flavia Maria Zauli
- Department of Philosophy "P. Martinetti", Università degli Studi di Milano, Milan, Italy; Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan, Italy; ASST GOM Niguarda, Piazza dell'Ospedale Maggiore 3, Milan, Italy
| | - Maria Del Vecchio
- Institute of Neuroscience, Consiglio Nazionale delle Ricerche, Parma, Italy
| | - Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan, Italy; UOC Maxillo-facial Surgery and dentistry, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Simone Russo
- Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan, Italy; Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan, Italy; Istituto Di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan, Italy
| | - Ivana Sartori
- ASST GOM Niguarda, Piazza dell'Ospedale Maggiore 3, Milan, Italy
| | - Francesco Cardinale
- ASST GOM Niguarda, Piazza dell'Ospedale Maggiore 3, Milan, Italy; Institute of Neuroscience, Consiglio Nazionale delle Ricerche, Parma, Italy; Department of Medicine and Surgery, Unit of Neuroscience, Università degli Studi di Parma, Parma, Italy
| | - Piergiorgio d'Orio
- ASST GOM Niguarda, Piazza dell'Ospedale Maggiore 3, Milan, Italy; Institute of Neuroscience, Consiglio Nazionale delle Ricerche, Parma, Italy; Department of Medicine and Surgery, Unit of Neuroscience, Università degli Studi di Parma, Parma, Italy
| | - Ezequiel Mikulan
- Department of Health Sciences, Università degli Studi di Milano, Milan, Italy.
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Wong SM, Sharma R, Abushama A, Ochi A, Otsubo H, Ibrahim GM. The impact of simultaneous intracranial recordings on scalp EEG: A finite element analysis. J Neurosci Methods 2024; 405:110101. [PMID: 38432305 DOI: 10.1016/j.jneumeth.2024.110101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 02/06/2024] [Accepted: 02/27/2024] [Indexed: 03/05/2024]
Abstract
BACKGROUND In this study, we examined the utility of simultaneous scalp and stereotactic intracranial electroencephalography (SSIEEG) in epilepsy patients. Although SSIEEG offers valuable insights into epilepsy and cognitive function, its routine use is uncommon. Challenges include interpreting post-craniotomy scalp EEG due to surgically implanted electrodes. NEW METHOD We describe our methodology for conducting SSIEEG recordings. To simulate the potential impact on EEG interpretation, we computed the leadfield of scalp electrodes with and without burrholes using Finite Element Analysis to compare the resulting sensitivity volume and waveforms of simulated intracranial signals between skulls with and without burrholes. RESULTS The presence of burr holes in the skull layer of the leadfield models did not discernibly modify simulated waveforms or scalp EEG topology. Using realistic SEEG burr hole diameter, the difference in the average leadfield of scalp electrodes was 0.12% relative to the effect of switching two nearby electrodes, characterized by the cosine similarity difference. No patients experienced adverse events related to SSIEEG. COMPARISON WITH EXISTING METHODS Although there is increasing acceptance and interest in SSIEEG, few studies have characterized the technical feasibility. Here, we demonstrate through modelling that scalp recordings from SSIEEG are comparable to that through an intact skull. CONCLUSION The placement and simultaneous acquisition of scalp EEG during invasive monitoring through stereotactically inserted EEG electrodes is routinely performed at the Hospital for Sick Children. Scalp EEG recordings may assist with clinical interpretation. Burr holes in the skull layer did not discernibly alter EEG waveforms or topology.
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Affiliation(s)
- Simeon M Wong
- Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
| | - Rohit Sharma
- Department of Neurology, Hospital for Sick Children, Toronto, Canada
| | - Ahmed Abushama
- Department of Neurology, Hospital for Sick Children, Toronto, Canada
| | - Ayako Ochi
- Department of Neurology, Hospital for Sick Children, Toronto, Canada
| | - Hiroshi Otsubo
- Department of Neurology, Hospital for Sick Children, Toronto, Canada
| | - George M Ibrahim
- Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Canada; Division of Neurosurgery, Hospital for Sick Children, Toronto, Canada; Department of Surgery, University of Toronto, Toronto, Canada.
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Lee HJ, Chien LY, Yu HY, Lee CC, Chou CC, Kuo WJ, Lin FH. Distributed source modeling of stereoencephalographic measurements of ictal activity. Clin Neurophysiol 2024; 161:112-121. [PMID: 38461595 DOI: 10.1016/j.clinph.2024.02.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 02/07/2024] [Accepted: 02/17/2024] [Indexed: 03/12/2024]
Abstract
OBJECTIVES Stereoelectroencephalography (SEEG) can define the epileptogenic zone (EZ). However, SEEG is susceptible to the sampling bias, where no SEEG recording is taken within a circumscribed EZ. METHODS Nine patients with medically refractory epilepsy underwent SEEG recording, and brain resection got positive outcomes. Ictal neuronal currents were estimated by distributed source modeling using the SEEG data and individual's anatomical magnetic resonance imaging. Using a retrospective leave-one-out data sub-sampling, we evaluated the sensitivity and specificity of the current estimates using MRI after surgical resection or radio-frequency ablation. RESULTS The sensitivity and specificity in detecting the EZ were indistinguishable from either the data from all electrodes or the sub-sampled data (rank sum test: rank sum = 23719, p = 0.13) when at least one remaining electrode contact was no more than 20 mm away. CONCLUSIONS The distributed neuronal current estimates of ictal SEEG data can mitigate the challenge of delineating the boundary of the EZ in cases of missing an electrode implanted within the EZ and a required second SEEG exploration. SIGNIFICANCE Distributed source modeling can be a tool for clinicians to infer the EZ by allowing for more flexible planning of the electrode implantation route and minimizing the number of electrodes.
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Affiliation(s)
- Hsin-Ju Lee
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Lin-Yao Chien
- Institute of Neuroscience, National Yang Ming University, Taipei, Taiwan
| | - Hsiang-Yu Yu
- Department of Epilepsy, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming University, Taipei, Taiwan
| | - Cheng-Chia Lee
- School of Medicine, National Yang Ming University, Taipei, Taiwan; Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chien-Chen Chou
- Department of Epilepsy, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming University, Taipei, Taiwan
| | - Wen-Jui Kuo
- Institute of Neuroscience, National Yang Ming University, Taipei, Taiwan.
| | - Fa-Hsuan Lin
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
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Bonacci MC, Sammarra I, Caligiuri ME, Sturniolo M, Martino I, Vizza P, Veltri P, Gambardella A. Quantitative analysis of visually normal EEG reveals spectral power abnormalities in temporal lobe epilepsy. Neurophysiol Clin 2024; 54:102951. [PMID: 38552384 DOI: 10.1016/j.neucli.2024.102951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/29/2024] [Accepted: 01/31/2024] [Indexed: 05/25/2024] Open
Abstract
OBJECTIVE To compare quantitative spectral parameters of visually-normal EEG between Mesial Temporal Lobe Epilepsy (MTLE) patients and healthy controls (HC). METHOD We enrolled 26 MTLE patients and 26 HC. From each recording we calculated total power of all frequency bands and determined alpha-theta (ATR) and alpha-delta (ADR) power ratios in different brain regions. Group-wise differences between spectral parameters were investigated (p < 0.05). To test for associations between spectral-power and cognitive status, we evaluated correlations between neuropsychological tests and quantitative EEG (qEEG) metrics. RESULTS In all comparisons, ATR and ADR were significantly decreased in MTLE patients compared to HC, particularly over the hemisphere ipsilateral to epileptic activity. A positive correlation was seen in MTLE patients between ATR in ipsilateral temporal lobe, and results of neuropsychological tests of auditory verbal learning (RAVLT and RAVLT-D), short term verbal memory (Digit span backwards), and executive function (Weigl's sorting test). ADR values in the contralateral posterior region correlated positively with RAVLT-D and Digit span backwards tests. DISCUSSION Results confirmed that the power spectrum of qEEG is shifted towards lower frequencies in MTLE patients compared to HC. CONCLUSION Of note, our results were found in visually-normal recordings, providing further evidence of the value of qEEG for longitudinal monitoring of MTLE patients over time. Exploratory analysis of associations between qEEG and neuropsychological data suggest this could be useful for investigating effects of antiseizure medications on cognitive integrity in patients.
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Affiliation(s)
| | - Ilaria Sammarra
- Institute of Neurology, Department of Medical and Surgical Sciences, University of Magna Graecia, Italy
| | - Maria Eugenia Caligiuri
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University Magna Graecia, Italy.
| | - Miriam Sturniolo
- Institute of Neurology, Department of Medical and Surgical Sciences, University of Magna Graecia, Italy
| | - Iolanda Martino
- U.O.C. Neurology, Renato Dulbecco University hospital, Italy
| | - Patrizia Vizza
- Department of Medical and Surgical Science, University of Magna Graecia, Italy
| | | | - Antonio Gambardella
- Institute of Neurology, Department of Medical and Surgical Sciences, University of Magna Graecia, Italy
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Bolzan A, Benoit J, Pizzo F, Makhalova J, Villeneuve N, Carron R, Scavarda D, Bartolomei F, Lagarde S. Correspondence between scalp-EEG and stereoelectroencephalography seizure-onset patterns in patients with MRI-negative drug-resistant focal epilepsy. Epilepsia Open 2024; 9:568-581. [PMID: 38148028 PMCID: PMC10984298 DOI: 10.1002/epi4.12886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/28/2023] [Accepted: 12/14/2023] [Indexed: 12/28/2023] Open
Abstract
OBJECTIVE Our objective was to evaluate the relationship between scalp-EEG and stereoelectroencephalography (SEEG) seizure-onset patterns (SOP) in patients with MRI-negative drug-resistant focal epilepsy. METHODS We analyzed retrospectively 41 patients without visible lesion on brain MRI who underwent video-EEG followed by SEEG. We defined five types of SOPs on scalp-EEG and eight types on SEEG. We examined how various clinical variables affected scalp-EEG SOPs. RESULTS The most prevalent scalp SOPs were rhythmic sinusoidal activity (56.8%), repetitive epileptiform discharges (22.7%), and paroxysmal fast activity (15.9%). The presence of paroxysmal fast activity on scalp-EEG was always seen without delay from clinical onset and correlated with the presence of low-voltage fast activity in SEEG (sensitivity = 22.6%, specificity = 100%). The main factor explaining the discrepancy between the scalp and SEEG SOPs was the delay between clinical and scalp-EEG onset. There was a correlation between the scalp and SEEG SOPs when the scalp onset was simultaneous with the clinical onset (p = 0.026). A significant delay between clinical and scalp discharge onset was observed in 25% of patients and featured always with a rhythmic sinusoidal activity on scalp, corresponding to similar morphology of the discharge on SEEG. The presence of repetitive epileptiform discharges on scalp was associated with an underlying focal cortical dysplasia (sensitivity = 30%, specificity = 90%). There was no significant association between the scalp SOP and the epileptogenic zone location (deep or superficial), or surgical outcome. SIGNIFICANCE In patients with MRI-negative focal epilepsy, scalp SOP could suggest the SEEG SOP and some etiology (focal cortical dysplasia) but has no correlation with surgical prognosis. Scalp SOP correlates with the SEEG SOP in cases of simultaneous EEG and clinical onset; otherwise, scalp SOP reflects the propagation of the SEEG discharge. PLAIN LANGUAGE SUMMARY We looked at the correspondence between the electrical activity recorded during the start of focal seizure using scalp and intracerebral electrodes in patients with no visible lesion on MRI. If there is a fast activity on scalp, it reflects similar activity inside the brain. We found a good correspondence between scalp and intracerebral electrical activity for cases without significant delay between clinical and scalp electrical onset (seen in 75% of the cases we studied). Visualizing repetitive epileptic activity on scalp could suggest a particular cause of the epilepsy: a subtype of brain malformation called focal cortical dysplasia.
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Affiliation(s)
- Anna Bolzan
- APHM, Timone Hospital, Epileptology and Cerebral RhythmologyMarseilleFrance
| | - Jeanne Benoit
- CHU de Nice, Epileptology DepartmentUniversité Côte d'Azur, UMR2CA (URRIS)NiceFrance
| | - Francesca Pizzo
- APHM, Timone Hospital, Epileptology and Cerebral RhythmologyMarseilleFrance
- Aix Marseille Univ, INSERM, INS, Inst Neurosci SystMarseilleFrance
| | - Julia Makhalova
- APHM, Timone Hospital, Epileptology and Cerebral RhythmologyMarseilleFrance
- Aix Marseille Univ, INSERM, INS, Inst Neurosci SystMarseilleFrance
- APHM, Timone Hospital, CEMEREMMarseilleFrance
| | | | - Romain Carron
- Aix Marseille Univ, INSERM, INS, Inst Neurosci SystMarseilleFrance
- APHM, Timone Hospital, Stereotactic and Functional Neurosurgery, Gamma UnitMarseilleFrance
| | - Didier Scavarda
- Aix Marseille Univ, INSERM, INS, Inst Neurosci SystMarseilleFrance
- APHM, Timone Hospital, Paediatric NeurosurgeryMarseilleFrance
| | - Fabrice Bartolomei
- APHM, Timone Hospital, Epileptology and Cerebral RhythmologyMarseilleFrance
- Aix Marseille Univ, INSERM, INS, Inst Neurosci SystMarseilleFrance
| | - Stanislas Lagarde
- APHM, Timone Hospital, Epileptology and Cerebral RhythmologyMarseilleFrance
- Aix Marseille Univ, INSERM, INS, Inst Neurosci SystMarseilleFrance
- University Hospitals of Geneva (HUG), University of Geneva (UNIGE)GenevaSwitzerland
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8
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Ahveninen J, Lee HJ, Yu HY, Lee CC, Chou CC, Ahlfors SP, Kuo WJ, Jääskeläinen IP, Lin FH. Visual Stimuli Modulate Local Field Potentials But Drive No High-Frequency Activity in Human Auditory Cortex. J Neurosci 2024; 44:e0890232023. [PMID: 38129133 PMCID: PMC10869150 DOI: 10.1523/jneurosci.0890-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 11/06/2023] [Accepted: 11/07/2023] [Indexed: 12/23/2023] Open
Abstract
Neuroimaging studies suggest cross-sensory visual influences in human auditory cortices (ACs). Whether these influences reflect active visual processing in human ACs, which drives neuronal firing and concurrent broadband high-frequency activity (BHFA; >70 Hz), or whether they merely modulate sound processing is still debatable. Here, we presented auditory, visual, and audiovisual stimuli to 16 participants (7 women, 9 men) with stereo-EEG depth electrodes implanted near ACs for presurgical monitoring. Anatomically normalized group analyses were facilitated by inverse modeling of intracranial source currents. Analyses of intracranial event-related potentials (iERPs) suggested cross-sensory responses to visual stimuli in ACs, which lagged the earliest auditory responses by several tens of milliseconds. Visual stimuli also modulated the phase of intrinsic low-frequency oscillations and triggered 15-30 Hz event-related desynchronization in ACs. However, BHFA, a putative correlate of neuronal firing, was not significantly increased in ACs after visual stimuli, not even when they coincided with auditory stimuli. Intracranial recordings demonstrate cross-sensory modulations, but no indication of active visual processing in human ACs.
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Affiliation(s)
- Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts 02129
- Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115
| | - Hsin-Ju Lee
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario M4N 3M5, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
| | - Hsiang-Yu Yu
- Department of Epilepsy, Neurological Institute, Taipei Veterans General Hospital, Taipei 11217, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Cheng-Chia Lee
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
- Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Chien-Chen Chou
- Department of Epilepsy, Neurological Institute, Taipei Veterans General Hospital, Taipei 11217, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Seppo P Ahlfors
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts 02129
- Department of Radiology, Harvard Medical School, Boston, Massachusetts 02115
| | - Wen-Jui Kuo
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Iiro P Jääskeläinen
- Brain and Mind Laboratory, Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, FI-00076 AALTO, Finland
- International Laboratory of Social Neurobiology, Institute of Cognitive Neuroscience, Higher School of Economics, Moscow 101000, Russia
| | - Fa-Hsuan Lin
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario M4N 3M5, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Brain and Mind Laboratory, Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, FI-00076 AALTO, Finland
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9
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Brinkmann BH. Technical Considerations in EEG Source Imaging. J Clin Neurophysiol 2024; 41:2-7. [PMID: 38181382 DOI: 10.1097/wnp.0000000000001029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2024] Open
Abstract
SUMMARY EEG source imaging is an established technique for identifying the origin of interictal and ictal epileptiform discharges in patients with epilepsy, and it is an important tool in neurophysiology research. Accurate and reliable EEG source imaging requires appropriate choices of how the head, skull, and scalp are modeled, and understanding of the different approaches to modeling is important to guide these choices. Similarly, numerous different approaches to modeling the electrical sources within the brain exist, and appropriate understanding of the strengths and limitations of each are essential to obtaining accurate, reliable, and interpretable solutions. This review aims to describe the essential theoretical basis for these head and source models while also discussing the practical implications of each in clinical or research applications.
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Affiliation(s)
- Benjamin H Brinkmann
- Departments of Neurology and Physiology and Biomedical Engineering, Mayo Clinic, Alfred 9-441C, SMH; 200 First Street SW, Rochester, Minnesota, U.S.A
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10
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Liu C, Qi Y, Wang L, Zhang C, Kang L, Shang S, Dang J. Latencies to the first interictal epileptiform discharges recorded by the electroencephalography in different epileptic patients. BMC Neurol 2023; 23:427. [PMID: 38041003 PMCID: PMC10691041 DOI: 10.1186/s12883-023-03474-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 11/23/2023] [Indexed: 12/03/2023] Open
Abstract
PURPOSE Interictal epileptiform discharges (IEDs) captured in electroencephalography (EEG) have a high diagnostic value for epileptic patients. Extending the recording time may increase the possibility of obtaining IEDs. The purpose of our research was to determine how long it took for various epileptic individuals to receive their first IEDs. METHODS We retrospectively analyzed patients who were diagnosed with epilepsy and had no anti-seizure medications (ASMs) between September 2018 and March 2019 in the neurology department of the First Affiliated Hospital of Xi'an Jiaotong University. Each individual underwent a 24-h long-term video electroencephalographic monitoring (VEM) procedure. Clinical information including age, gender, age of seizure onset, frequency of seizures, the interval between last seizure and VEM, and results of neuroimaging were gathered. We also calculated the times from the start of the VEM to the first definite IEDs. RESULTS A total of 241 patients were examined, including 191 with focal-onset epilepsy and 50 with generalized epilepsy. In individuals with focal-onset epilepsy, the median latency to the first IED was 63.0 min (IQR 19.0-299.0 min), as compared to 30.0 min (IQR 12.5-62.0 min) in patients with generalized epilepsy (p < 0.001). The latency to the first IED is significantly related to the age of seizure onset (HR = 0.988, p = 0.049), the interval between last seizure and VEM (HR = 0.998, p = 0.013). But it is not correlated with seizure frequency, gender and age. CONCLUSIONS IEDs were discovered during 24-h EEG monitoring in 222/241(92.1%) of the epilepsy patients that were included. Compared to focal-onset epilepsy, generalized epilepsy demonstrated a much shorter latency to IED. Patients with late-onset epilepsy or those without recent episodes may require longer EEG monitoring periods.
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Affiliation(s)
- Chenyu Liu
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, Shaanxi, 710061, China
| | - Yi Qi
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, Shaanxi, 710061, China
| | - Liang Wang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, Shaanxi, 710061, China
| | - Ce Zhang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, Shaanxi, 710061, China
| | - Li Kang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, Shaanxi, 710061, China
| | - Suhang Shang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, Shaanxi, 710061, China
| | - Jingxia Dang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, Shaanxi, 710061, China.
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11
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Ferrand M, Baumann C, Aron O, Vignal JP, Jonas J, Tyvaert L, Colnat-Coulbois S, Koessler L, Maillard L. Intracerebral Correlates of Scalp EEG Ictal Discharges Based on Simultaneous Stereo-EEG Recordings. Neurology 2023; 100:e2045-e2059. [PMID: 36963841 PMCID: PMC10186237 DOI: 10.1212/wnl.0000000000207135] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 01/18/2023] [Indexed: 03/26/2023] Open
Abstract
BACKGROUND AND OBJECTIVES It remains unknown to what extent ictal scalp EEG can accurately predict the localization of the intracerebral seizure onset in presurgical evaluation of drug-resistant epilepsies. In this study, we aimed to define homogeneous ictal scalp EEG profiles (based on their first ictal abnormality) and assess their localizing value using simultaneously recorded scalp EEG and stereo-EEG. METHODS We retrospectively included consecutive patients with drug-resistant focal epilepsy who had simultaneous stereo-EEG and scalp EEG recordings of at least 1 seizure in the epileptology unit in Nancy, France. We analyzed 1 seizure per patient and used hierarchical cluster analysis to group similar seizure profiles on scalp EEG and then performed a descriptive analysis of their intracerebral correlates. RESULTS We enrolled 129 patients in this study. The hierarchical cluster analysis showed 6 profiles on scalp EEG first modification. None were specific to a single intracerebral localization. The "normal EEG" and "blurred EEG" clusters (early muscle artifacts) comprised only 5 patients each and corresponded to no preferential intracerebral localization. The "temporal discharge" cluster (n = 46) was characterized by theta or delta discharges on ipsilateral anterior temporal scalp electrodes and corresponded to a preferential mesial temporal intracerebral localization. The "posterior discharge" cluster (n = 42) was characterized by posterior ipsilateral or contralateral rhythmic alpha discharges or slow waves on scalp and corresponded to a preferential temporal localization. However, this profile was the statistically most frequent scalp EEG correlate of occipital and parietal seizures. The "diffuse suppression" cluster (n = 9) was characterized by a bilateral and diffuse background activity suppression on scalp and corresponded to mesial, and particularly insulo-opercular, localization. Finally, the "frontal discharge" cluster (n = 22) was characterized by bilateral frontal rhythmic fast activity or preictal spike on scalp and corresponded to preferential ventrodorsal frontal intracerebral localizations. DISCUSSION The hierarchical cluster analysis identified 6 seizure profiles regarding the first abnormality on scalp EEG. None of them were specific of a single intracerebral localization. Nevertheless, the strong relationships between the "temporal," "frontal," "diffuse suppression," and "posterior" profiles and intracerebral discharge localizations may contribute to hierarchize hypotheses derived from ictal scalp EEG analysis regarding intracerebral seizure onset.
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Affiliation(s)
- Mickaël Ferrand
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Cédric Baumann
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Olivier Aron
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Jean-Pierre Vignal
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Jacques Jonas
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Louise Tyvaert
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Sophie Colnat-Coulbois
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Laurent Koessler
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Louis Maillard
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France.
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12
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van Nifterick AM, Mulder D, Duineveld DJ, Diachenko M, Scheltens P, Stam CJ, van Kesteren RE, Linkenkaer-Hansen K, Hillebrand A, Gouw AA. Resting-state oscillations reveal disturbed excitation-inhibition ratio in Alzheimer's disease patients. Sci Rep 2023; 13:7419. [PMID: 37150756 PMCID: PMC10164744 DOI: 10.1038/s41598-023-33973-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 04/21/2023] [Indexed: 05/09/2023] Open
Abstract
An early disruption of neuronal excitation-inhibition (E-I) balance in preclinical animal models of Alzheimer's disease (AD) has been frequently reported, but is difficult to measure directly and non-invasively in humans. Here, we examined known and novel neurophysiological measures sensitive to E-I in patients across the AD continuum. Resting-state magnetoencephalography (MEG) data of 86 amyloid-biomarker-confirmed subjects across the AD continuum (17 patients diagnosed with subjective cognitive decline, 18 with mild cognitive impairment (MCI) and 51 with dementia due to probable AD (AD dementia)), 46 healthy elderly and 20 young control subjects were reconstructed to source-space. E-I balance was investigated by detrended fluctuation analysis (DFA), a functional E/I (fE/I) algorithm, and the aperiodic exponent of the power spectrum. We found a disrupted E-I ratio in AD dementia patients specifically, by a lower DFA, and a shift towards higher excitation, by a higher fE/I and a lower aperiodic exponent. Healthy subjects showed lower fE/I ratios (< 1.0) than reported in previous literature, not explained by age or choice of an arbitrary threshold parameter, which warrants caution in interpretation of fE/I results. Correlation analyses showed that a lower DFA (E-I imbalance) and a lower aperiodic exponent (more excitation) was associated with a worse cognitive score in AD dementia patients. In contrast, a higher DFA in the hippocampi of MCI patients was associated with a worse cognitive score. This MEG-study showed E-I imbalance, likely due to increased excitation, in AD dementia, but not in early stage AD patients. To accurately determine the direction of shift in E-I balance, validations of the currently used markers and additional in vivo markers of E-I are required.
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Affiliation(s)
- Anne M van Nifterick
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands.
| | - Danique Mulder
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Denise J Duineveld
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Marina Diachenko
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Ronald E van Kesteren
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Klaus Linkenkaer-Hansen
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Alida A Gouw
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
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13
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Frauscher B, Bénar CG, Engel JJ, Grova C, Jacobs J, Kahane P, Wiebe S, Zjilmans M, Dubeau F. Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy. Epilepsy Behav 2023; 143:109221. [PMID: 37119580 DOI: 10.1016/j.yebeh.2023.109221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 05/01/2023]
Abstract
Since the discovery of the human electroencephalogram (EEG), neurophysiology techniques have become indispensable tools in our armamentarium to localize epileptic seizures. New signal analysis techniques and the prospects of artificial intelligence and big data will offer unprecedented opportunities to further advance the field in the near future, ultimately resulting in improved quality of life for many patients with drug-resistant epilepsy. This article summarizes selected presentations from Day 1 of the two-day symposium "Neurophysiology, Neuropsychology, Epilepsy, 2022: Hills We Have Climbed and the Hills Ahead". Day 1 was dedicated to highlighting and honoring the work of Dr. Jean Gotman, a pioneer in EEG, intracranial EEG, simultaneous EEG/ functional magnetic resonance imaging, and signal analysis of epilepsy. The program focused on two main research directions of Dr. Gotman, and was dedicated to "High-frequency oscillations, a new biomarker of epilepsy" and "Probing the epileptic focus from inside and outside". All talks were presented by colleagues and former trainees of Dr. Gotman. The extended summaries provide an overview of historical and current work in the neurophysiology of epilepsy with emphasis on novel EEG biomarkers of epilepsy and source imaging and concluded with an outlook on the future of epilepsy research, and what is needed to bring the field to the next level.
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Affiliation(s)
- B Frauscher
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
| | - C G Bénar
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - J Jr Engel
- David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - C Grova
- Multimodal Functional Imaging Lab, PERFORM Centre, Department of Physics, Concordia University, Montreal, QC, Canada; Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, QC, Canada; Montreal Neurological Institute and Hospital, Neurology and Neurosurgery Department, McGill University, Montreal, QC, Canada
| | - J Jacobs
- Department of Pediatric and Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - P Kahane
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institute Neurosciences, Department of Neurology, 38000 Grenoble, France
| | - S Wiebe
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - M Zjilmans
- Stichting Epilepsie Instellingen Nederland, The Netherlands; Brain Center, University Medical Center Utrecht, The Netherlands
| | - F Dubeau
- Montreal Neurological Institute and Hospital, Neurology and Neurosurgery Department, McGill University, Montreal, QC, Canada
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14
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Barborica A, Mindruta I, López-Madrona VJ, Alario FX, Trébuchon A, Donos C, Oane I, Pistol C, Mihai F, Bénar CG. Studying memory processes at different levels with simultaneous depth and surface EEG recordings. Front Hum Neurosci 2023; 17:1154038. [PMID: 37082152 PMCID: PMC10110965 DOI: 10.3389/fnhum.2023.1154038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 03/06/2023] [Indexed: 04/07/2023] Open
Abstract
Investigating cognitive brain functions using non-invasive electrophysiology can be challenging due to the particularities of the task-related EEG activity, the depth of the activated brain areas, and the extent of the networks involved. Stereoelectroencephalographic (SEEG) investigations in patients with drug-resistant epilepsy offer an extraordinary opportunity to validate information derived from non-invasive recordings at macro-scales. The SEEG approach can provide brain activity with high spatial specificity during tasks that target specific cognitive processes (e.g., memory). Full validation is possible only when performing simultaneous scalp SEEG recordings, which allows recording signals in the exact same brain state. This is the approach we have taken in 12 subjects performing a visual memory task that requires the recognition of previously viewed objects. The intracranial signals on 965 contact pairs have been compared to 391 simultaneously recorded scalp signals at a regional and whole-brain level, using multivariate pattern analysis. The results show that the task conditions are best captured by intracranial sensors, despite the limited spatial coverage of SEEG electrodes, compared to the whole-brain non-invasive recordings. Applying beamformer source reconstruction or independent component analysis does not result in an improvement of the multivariate task decoding performance using surface sensor data. By analyzing a joint scalp and SEEG dataset, we investigated whether the two types of signals carry complementary information that might improve the machine-learning classifier performance. This joint analysis revealed that the results are driven by the modality exhibiting best individual performance, namely SEEG.
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Affiliation(s)
- Andrei Barborica
- Department of Physics, University of Bucharest, Bucharest, Romania
- *Correspondence: Andrei Barborica
| | - Ioana Mindruta
- Epilepsy Monitoring Unit, Department of Neurology, Emergency University Hospital Bucharest, Bucharest, Romania
- Department of Neurology, Medical Faculty, Carol Davila University of Medicine and Pharmacy Bucharest, Bucharest, Romania
| | | | | | - Agnès Trébuchon
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- APHM, Timone Hospital, Functional and Stereotactic Neurosurgery, Marseille, France
| | - Cristian Donos
- Department of Physics, University of Bucharest, Bucharest, Romania
| | - Irina Oane
- Epilepsy Monitoring Unit, Department of Neurology, Emergency University Hospital Bucharest, Bucharest, Romania
| | | | - Felicia Mihai
- Department of Physics, University of Bucharest, Bucharest, Romania
| | - Christian G. Bénar
- Aix Marseille University, INSERM, INS, Institute of Neuroscience System, Marseille, France
- Christian G. Bénar
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15
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Peltola ME, Leitinger M, Halford JJ, Vinayan KP, Kobayashi K, Pressler RM, Mindruta I, Mayor LC, Lauronen L, Beniczky S. Routine and sleep EEG: Minimum recording standards of the International Federation of Clinical Neurophysiology and the International League Against Epilepsy. Epilepsia 2023; 64:602-618. [PMID: 36762397 PMCID: PMC10006292 DOI: 10.1111/epi.17448] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/18/2022] [Accepted: 10/25/2022] [Indexed: 02/11/2023]
Abstract
This article provides recommendations on the minimum standards for recording routine ("standard") and sleep electroencephalography (EEG). The joint working group of the International Federation of Clinical Neurophysiology (IFCN) and the International League Against Epilepsy (ILAE) developed the standards according to the methodology suggested for epilepsy-related clinical practice guidelines by the Epilepsy Guidelines Working Group. We reviewed the published evidence using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. The quality of evidence for sleep induction methods was assessed by the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) method. A tool for Quality Assessment of Diagnostic Studies (QUADAS-2) was used to assess the risk of bias in technical and methodological studies. Where high-quality published evidence was lacking, we used modified Delphi technique to reach expert consensus. The GRADE system was used to formulate the recommendations. The quality of evidence was low or moderate. We formulated 16 consensus-based recommendations for minimum standards for recording routine and sleep EEG. The recommendations comprise the following aspects: indications, technical standards, recording duration, sleep induction, and provocative methods.
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Affiliation(s)
- Maria E Peltola
- HUS Diagnostic Center, Clinical Neurophysiology, Clinical Neurosciences, Epilepsia Helsinki, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Markus Leitinger
- Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University, Salzburg, Austria
| | - Jonathan J Halford
- Department of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA
| | | | - Katsuhiro Kobayashi
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Ronit M Pressler
- Clinical Neuroscience, UCL-Great Ormond Street Institute of Child Health and Department of Clinical Neurophysiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Ioana Mindruta
- Department of Neurology, University Emergency Hospital of Bucharest and University of Medicine and Pharmacy "Carol Davila", Bucharest, Romania
| | - Luis Carlos Mayor
- Department of Neurology, Hospital Universitario Fundacion Santa Fe de Bogota, Bogota, Colombia
| | - Leena Lauronen
- HUS Diagnostic Center, Clinical Neurophysiology, Clinical Neurosciences, Epilepsia Helsinki, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Sándor Beniczky
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, and Danish Epilepsy Centre, Dianalund, Denmark
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16
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Ternisien E, Cecchin T, Colnat-Coulbois S, Maillard LG, Koessler L. Extracting the Invisible: Mesial Temporal Source Detection in Simultaneous EEG and SEEG Recordings. Brain Topogr 2023; 36:192-209. [PMID: 36732440 DOI: 10.1007/s10548-023-00940-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/19/2023] [Indexed: 02/04/2023]
Abstract
Epileptic source detection relies mainly on visual expertise of scalp EEG signals, but it is recognised that epileptic discharges can escape to this expertise due to a deep localization of the brain sources that induce a very low, even negative, signal to noise ratio. In this methodological study, we aimed to investigate the feasibility of extracting deep mesial temporal sources that were invisible in scalp EEG signals using blind source separation (BSS) methods (infomax ICA, extended infomax ICA, and JADE) combined with a statistical measure (kurtosis). We estimated the effect of different methodological and physiological parameters that could alter or improve the extraction. Using nine well-defined mesial epileptic networks (1949 spikes) obtained from seven patients and simultaneous EEG-SEEG recordings, the first independent component extracted from the scalp EEG signals was validated in mean from 46 to 80% according to the different parameters. The three BSS methods equally performed (no significant difference) and no influence of the number of scalp electrodes used was found. At the opposite, the number and amplitude of spikes included in the averaging before the extraction modified the performance. Anyway, despite their invisibility in scalp EEG signals, this study demonstrates that deep source extraction is feasible under certain conditions and with the use of common signal analysis toolboxes. This finding confirms the crucial need to continue the signal analysis of scalp EEG recordings which contains subcortical signals that escape to expert visual analysis but could be found by signal processing.
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Affiliation(s)
| | | | - Sophie Colnat-Coulbois
- Université de Lorraine, CNRS, CRAN, Nancy, France.,Université de Lorraine, CHRU-Nancy, Service de Neurochirurgie, Nancy, France
| | - Louis Georges Maillard
- Université de Lorraine, CNRS, CRAN, Nancy, France.,Université de Lorraine, CHRU-Nancy, Service de Neurologie, Nancy, France
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17
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Peltola ME, Leitinger M, Halford JJ, Vinayan KP, Kobayashi K, Pressler RM, Mindruta I, Mayor LC, Lauronen L, Beniczky S. Routine and sleep EEG: Minimum recording standards of the International Federation of Clinical Neurophysiology and the International League Against Epilepsy. Clin Neurophysiol 2023; 147:108-120. [PMID: 36775678 DOI: 10.1016/j.clinph.2023.01.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
This article provides recommendations on the minimum standards for recording routine ("standard") and sleep electroencephalography (EEG). The joint working group of the International Federation of Clinical Neurophysiology (IFCN) and the International League Against Epilepsy (ILAE) developed the standards according to the methodology suggested for epilepsy-related clinical practice guidelines by the Epilepsy Guidelines Working Group. We reviewed the published evidence using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. The quality of evidence for sleep induction methods was assessed by the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) method. A tool for Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was used to assess the risk of bias in technical and methodological studies. Where high-quality published evidence was lacking, we used modified Delphi technique to reach expert consensus. The GRADE system was used to formulate the recommendations. The quality of evidence was low or moderate. We formulated 16 consensus-based recommendations for minimum standards for recording routine and sleep EEG. The recommendations comprise the following aspects: indications, technical standards, recording duration, sleep induction, and provocative methods.
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Affiliation(s)
- Maria E Peltola
- HUS Diagnostic Center, Clinical Neurophysiology, Clinical Neurosciences, Epilepsia Helsinki, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
| | - Markus Leitinger
- Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University, Salzburg, Austria
| | - Jonathan J Halford
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | | | - Katsuhiro Kobayashi
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Ronit M Pressler
- Clinical Neuroscience, UCL-Great Ormond Street Institute of Child Health and Department of Clinical Neurophysiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Ioana Mindruta
- Department of Neurology, University Emergency Hospital of Bucharest and University of Medicine and Pharmacy "Carol Davila", Bucharest, Romania
| | - Luis Carlos Mayor
- Department of Neurology, Hospital Universitario Fundacion Santa Fe de Bogota, Bogota, Colombia
| | - Leena Lauronen
- HUS Diagnostic Center, Clinical Neurophysiology, Clinical Neurosciences, Epilepsia Helsinki, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Sándor Beniczky
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, and Danish Epilepsy Centre, Dianalund, Denmark
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18
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Lee S, Wu S, Tao JX, Rose S, Warnke PC, Issa NP, van Drongelen W. Manifestation of Hippocampal Interictal Discharges on Clinical Scalp EEG Recordings. J Clin Neurophysiol 2023; 40:144-150. [PMID: 34010227 PMCID: PMC8590709 DOI: 10.1097/wnp.0000000000000867] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
PURPOSE Epileptiform activity limited to deep sources such as the hippocampus currently lacks reliable scalp correlates. Recent studies, however, have found that a subset of hippocampal interictal discharges may be associated with visible scalp signals, suggesting that some types of hippocampal activity may be monitored noninvasively. The purpose of this study is to characterize the relationship between these scalp waveforms and the underlying intracranial activity. METHODS Paired intracranial and scalp EEG recordings obtained from 16 patients were used to identify hippocampal interictal discharges. Discharges were grouped by waveform shape, and spike-triggered averages of the intracranial and scalp signals were calculated for each group. Cross-correlation of intracranial and scalp spike-triggered averages was used to determine their temporal relationship, and topographic maps of the scalp were generated for each group. RESULTS Cross-correlation of intracranial and scalp correlates resulted in two classes of scalp waveforms-those with and without time delays from the associated hippocampal discharges. Scalp signals with no delay showed topographies with a broad field with higher amplitudes on the side ipsilateral to the discharges and a left-right flip in polarity-observations consistent with the volume conduction of a single unilateral deep source. In contrast, scalp correlates with time lags showed rotational dynamics, suggesting synaptic propagation mechanisms. CONCLUSIONS The temporal relationship between the intracranial and scalp signals suggests that both volume conduction and synaptic propagation contribute to these scalp manifestations. Furthermore, the topographic evolution of these scalp waveforms may be used to distinguish spikes that are limited to the hippocampus from those that travel to or engage other brain areas.
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Affiliation(s)
- Somin Lee
- Department of Pediatrics, The University of Chicago, Chicago, IL, 60607, USA
- Committee on Neurobiology, The University of Chicago, Chicago, IL, 60607, USA
| | - Shasha Wu
- Department of Neurology, The University of Chicago, Chicago, IL, 60607, USA
| | - James X. Tao
- Department of Neurology, The University of Chicago, Chicago, IL, 60607, USA
| | - Sandra Rose
- Department of Neurology, The University of Chicago, Chicago, IL, 60607, USA
| | - Peter C. Warnke
- Department of Surgery, The University of Chicago, Chicago, IL, 60607, USA
| | - Naoum P. Issa
- Department of Neurology, The University of Chicago, Chicago, IL, 60607, USA
| | - Wim van Drongelen
- Department of Pediatrics, The University of Chicago, Chicago, IL, 60607, USA
- Committee on Neurobiology, The University of Chicago, Chicago, IL, 60607, USA
- Department of Neurology, The University of Chicago, Chicago, IL, 60607, USA
- Committee on Computational Neuroscience, The University of Chicago, Chicago, IL, 60607, USA
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19
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Okadome T, Yamaguchi T, Mukaino T, Sakata A, Ogata K, Shigeto H, Isobe N, Uehara T. The effect of interictal epileptic discharges and following spindles on motor sequence learning in epilepsy patients. Front Neurol 2022; 13:979333. [PMID: 36438951 PMCID: PMC9686303 DOI: 10.3389/fneur.2022.979333] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 10/25/2022] [Indexed: 09/05/2023] Open
Abstract
PURPOSE Interictal epileptic discharges (IEDs) are known to affect cognitive function in patients with epilepsy, but the mechanism has not been elucidated. Sleep spindles appearing in synchronization with IEDs were recently demonstrated to impair memory consolidation in rat, but this has not been investigated in humans. On the other hand, the increase of sleep spindles at night after learning is positively correlated with amplified learning effects during sleep for motor sequence learning. In this study, we examined the effects of IEDs and IED-coupled spindles on motor sequence learning in patients with epilepsy, and clarified their pathological significance. MATERIALS AND METHODS Patients undergoing long-term video-electroencephalography (LT-VEEG) at our hospital from June 2019 to November 2021 and age-matched healthy subjects were recruited. Motor sequence learning consisting of a finger-tapping task was performed before bedtime and the next morning, and the improvement rate of performance was defined as the sleep-dependent learning effect. We searched for factors associated with the changes in learning effect observed between the periods of when antiseizure medications (ASMs) were withdrawn for LT-VEEG and when they were returned to usual doses after LT-VEEG. RESULTS Excluding six patients who had epileptic seizures at night after learning, nine patients and 11 healthy subjects were included in the study. In the patient group, there was no significant learning effect when ASMs were withdrawn. The changes in learning effect of the patient group during ASM withdrawal were not correlated with changes in sleep duration or IED density; however, they were significantly negatively correlated with changes in IED-coupled spindle density. CONCLUSION We found that the increase of IED-coupled spindles correlated with the decrease of sleep-dependent learning effects of procedural memory. Pathological IED-coupled sleep spindles could hinder memory consolidation, that is dependent on physiological sleep spindles, resulting in cognitive dysfunction in patients with epilepsy.
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Affiliation(s)
- Toshiki Okadome
- Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Takahiro Yamaguchi
- Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Takahiko Mukaino
- Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Ayumi Sakata
- Department of Clinical Chemistry and Laboratory Medicine, Kyushu University Hospital, Fukuoka, Japan
| | - Katsuya Ogata
- Department of Pharmacy, School of Pharmaceutical Sciences at Fukuoka, International University of Health and Welfare, Okawa, Japan
| | - Hiroshi Shigeto
- Division of Medical Technology, Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Noriko Isobe
- Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Taira Uehara
- Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
- Department of Neurology, School of Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan
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20
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Moorhouse FJ, Cornell S, Gerstl L, Wagner J, Tacke M, Roser T, Heinen F, von Stülpnagel C, Vollmar C, Kunz M, Ramantani G, Borggraefe I. Cognitive profiles in pediatric unilobar vs. multilobar epilepsy. Eur J Paediatr Neurol 2022; 41:48-54. [PMID: 36265333 DOI: 10.1016/j.ejpn.2022.09.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 09/12/2022] [Accepted: 09/24/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVES We aimed to determine how cognitive impairment relates to the extent of the presumed epileptogenic zone in pediatric focal epilepsies. We analyzed the cognitive functions in unilobar compared to multilobar focal epilepsy patients that underwent neuropsychological testing at a tertiary epilepsy center. METHODS We assessed cognitive functions of pediatric focal epilepsy patients with the German version of the Wechsler Intelligence Scales that measures full-scale IQ and subcategories. We assessed differences in IQ and epilepsy-related variables between unilobar and multilobar epilepsy patients. RESULTS We included 62 patients (37 unilobar, 25 multilobar), aged 10.6 ± 3.7 years. Full-scale IQ values were significantly higher in unilobar (93.6 ± 17.7, 95% CI 87.7-99.6) than in multilobar epilepsy patients (77.3 ± 17.2, 95% CI 69.3-85.0; p = 0.001). In all but one IQ subcategory (working memory), significantly higher values were measured in unilobar than in multilobar epilepsy patients. The proportion of unilobar epilepsy patients with severe cognitive impairment (8.3%) and below-average intelligence (30.5%) was lower compared to multilobar epilepsy patients (47.6% and 61.9%; p = 0.002 and p = 0.021, respectively). Epilepsy onset occurred earlier in multilobar (4.0 years, 95% CI 2.6-5.5, SD ± 3.4 years) than in unilobar epilepsy patients (7.0 years, 95% CI 5.5-8.5, SD ± 4.4 years, p = 0.008). CONCLUSIONS Pediatric multilobar epilepsy patients face more cognitive issues than unilobar epilepsy patients on average. Our findings should help to identify children and adolescents who are most at risk for impaired cognitive development. A limitation of our study is the simple division into unilobar and multilobar epilepsies, with no specific account being taken of etiology/epilepsy syndrome, which can have a profound effect on cognition.
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Affiliation(s)
- Frederik Jan Moorhouse
- Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Sonia Cornell
- Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Lucia Gerstl
- Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Johanna Wagner
- Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Moritz Tacke
- Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Timo Roser
- Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Florian Heinen
- Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Celina von Stülpnagel
- Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University, Munich, Germany; Paracelsus Medical University, Salzburg, Austria
| | - Christian Vollmar
- Department of Neurology, Ludwig-Maximilians-University, Munich, Germany; Comprehensive Epilepsy Center, Ludwig-Maximilians-University, Munich, Germany
| | - Mathias Kunz
- Comprehensive Epilepsy Center, Ludwig-Maximilians-University, Munich, Germany; Department of Neurosurgery, Ludwig-Maximilians-University, Munich, Germany
| | - Georgia Ramantani
- Department of Neuropediatrics, University Children's Hospital, Zurich, Switzerland; University of Zurich, Zurich, Switzerland
| | - Ingo Borggraefe
- Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University, Munich, Germany; Comprehensive Epilepsy Center, Ludwig-Maximilians-University, Munich, Germany.
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21
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Doyen M, Chawki MB, Heyer S, Guedj E, Roch V, Marie PY, Tyvaert L, Maillard L, Verger A. Metabolic connectivity is associated with seizure outcome in surgically treated temporal lobe epilepsies: A 18F-FDG PET seed correlation analysis. Neuroimage Clin 2022; 36:103210. [PMID: 36208546 PMCID: PMC9668618 DOI: 10.1016/j.nicl.2022.103210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 09/14/2022] [Accepted: 09/22/2022] [Indexed: 12/14/2022]
Abstract
18F-FDG PET provides high sensitivity for the pre-surgical assessment of drug-resistant temporal lobe epilepsy (TLE). However, little is known about the metabolic connectivity of epileptogenic networks involved. This study therefore aimed to evaluate the association between metabolic connectivity and seizure outcome in surgically treated TLE. METHODS The study included 107 right-handed patients that had undergone a presurgical interictal 18F-FDG PET assessment followed by an anterior temporal lobectomy and were classified according to seizure outcome 2 years after surgery. Metabolic connectivity was evaluated by seed correlation analysis in left and right epilepsy patients with a Class Engel IA or > IA outcome and compared to age-, sex- and handedness-matched healthy controls. RESULTS Increased metabolic connectivity was observed in the >IA compared to the IA group within the operated temporal lobe (respective clusters of 7.5 vs 3.3 cm3 and 2.6 cm3 vs 2.2 cm3 in left and right TLE), and to a lower extent with the contralateral temporal lobe (1.2 vs 0.7 cm3 and 1.7 cm3 vs 0.7 cm3 in left and right TLE). Seed correlations provided added value for the estimated individual performance of seizure outcome over the group comparisons in left TLE (AUC of 0.74 vs 0.67). CONCLUSION Metabolic connectivity is associated with outcome in surgically treated TLE with a strengthened epileptogenic connectome in patients with non-free-seizure outcomes. The added value of seed correlation analysis in left TLE underlines the importance of evaluating metabolic connectivity in network related diseases.
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Affiliation(s)
- Matthieu Doyen
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France,Université de Lorraine, IADI, INSERM U1254, F-54000 Nancy, France,Corresponding author at: Université de Lorraine, IADI - INSERM U1254, Department of Nuclear Medicine and Nancyclotep Imaging Platform, F-54000 Nancy, France.
| | - Mohammad B. Chawki
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France
| | - Sébastien Heyer
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France
| | - Eric Guedj
- Aix Marseille Univ, APHM, CNRS, Centrale Marseille, Institut Fresnel, Timone Hospital, CERIMED, Nuclear Medicine Department, F-13000 Marseille, France
| | - Véronique Roch
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France
| | - Pierre-Yves Marie
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France,Université de Lorraine, INSERM, DCAC, Nancy, France
| | - Louise Tyvaert
- Université de Lorraine, CRAN UMR 7039, Nancy, France,Department of Neurology, CHRU Nancy, National Reference Center for Rare Epilepsies, F-54000 Nancy, France
| | - Louis Maillard
- Université de Lorraine, CRAN UMR 7039, Nancy, France,Department of Neurology, CHRU Nancy, National Reference Center for Rare Epilepsies, F-54000 Nancy, France
| | - Antoine Verger
- Université de Lorraine, Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, F-54000 Nancy, France,Université de Lorraine, IADI, INSERM U1254, F-54000 Nancy, France
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22
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Niso G, Krol LR, Combrisson E, Dubarry AS, Elliott MA, François C, Héjja-Brichard Y, Herbst SK, Jerbi K, Kovic V, Lehongre K, Luck SJ, Mercier M, Mosher JC, Pavlov YG, Puce A, Schettino A, Schön D, Sinnott-Armstrong W, Somon B, Šoškić A, Styles SJ, Tibon R, Vilas MG, van Vliet M, Chaumon M. Good scientific practice in EEG and MEG research: Progress and perspectives. Neuroimage 2022; 257:119056. [PMID: 35283287 PMCID: PMC11236277 DOI: 10.1016/j.neuroimage.2022.119056] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 02/25/2022] [Accepted: 03/01/2022] [Indexed: 11/22/2022] Open
Abstract
Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.
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Affiliation(s)
- Guiomar Niso
- Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA; Universidad Politecnica de Madrid and CIBER-BBN, Madrid, Spain
| | - Laurens R Krol
- Neuroadaptive Human-Computer Interaction, Brandenburg University of Technology Cottbus-Senftenberg, Germany
| | - Etienne Combrisson
- Aix-Marseille University, Institut de Neurosciences de la Timone, France
| | | | | | | | - Yseult Héjja-Brichard
- Centre d'Ecologie Fonctionnelle et Evolutive, CNRS, EPHE, IRD, Université Montpellier, Montpellier, France
| | - Sophie K Herbst
- Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, NeuroSpin center, Université Paris-Saclay, Gif/Yvette, France
| | - Karim Jerbi
- Cognitive and Computational Neuroscience Laboratory, Department of Psychology, University of Montreal, Montreal, QC, Canada; Mila - Quebec Artificial Intelligence Institute, Canada
| | - Vanja Kovic
- Faculty of Philosophy, Laboratory for neurocognition and applied cognition, University of Belgrade, Serbia
| | - Katia Lehongre
- Institut du Cerveau - Paris Brain Institute - ICM, Inserm U 1127, CNRS UMR 7225, APHP, Hôpital de la Pitié Salpêtrière, Sorbonne Université, Centre MEG-EEG, Centre de NeuroImagerie Recherche (CENIR), Paris, France
| | - Steven J Luck
- Center for Mind & Brain, University of California, Davis, CA, USA
| | - Manuel Mercier
- Aix Marseille Univ, Inserm, INS, Inst Neurosci Syst, Marseille, France
| | - John C Mosher
- McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yuri G Pavlov
- University of Tuebingen, Germany; Ural Federal University, Yekaterinburg, Russia
| | - Aina Puce
- Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Antonio Schettino
- Erasmus University Rotterdam, Rotterdam, the Netherland; Institute for Globally Distributed Open Research and Education (IGDORE), Sweden
| | - Daniele Schön
- Aix Marseille Univ, Inserm, INS, Inst Neurosci Syst, Marseille, France
| | | | | | - Anđela Šoškić
- Faculty of Philosophy, Laboratory for neurocognition and applied cognition, University of Belgrade, Serbia; Teacher Education Faculty, University of Belgrade, Serbia
| | - Suzy J Styles
- Psychology, Nanyang Technological University, Singapore; Singapore Institute for Clinical Sciences, A*STAR, Singapore
| | - Roni Tibon
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK; School of Psychology, University of Nottingham, Nottingham, UK
| | - Martina G Vilas
- Ernst Strüngmann Institute for Neuroscience, Frankfurt am Main, Germany
| | | | - Maximilien Chaumon
- Institut du Cerveau - Paris Brain Institute - ICM, Inserm U 1127, CNRS UMR 7225, APHP, Hôpital de la Pitié Salpêtrière, Sorbonne Université, Centre MEG-EEG, Centre de NeuroImagerie Recherche (CENIR), Paris, France..
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23
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Mercier MR, Dubarry AS, Tadel F, Avanzini P, Axmacher N, Cellier D, Vecchio MD, Hamilton LS, Hermes D, Kahana MJ, Knight RT, Llorens A, Megevand P, Melloni L, Miller KJ, Piai V, Puce A, Ramsey NF, Schwiedrzik CM, Smith SE, Stolk A, Swann NC, Vansteensel MJ, Voytek B, Wang L, Lachaux JP, Oostenveld R. Advances in human intracranial electroencephalography research, guidelines and good practices. Neuroimage 2022; 260:119438. [PMID: 35792291 DOI: 10.1016/j.neuroimage.2022.119438] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 05/23/2022] [Accepted: 06/30/2022] [Indexed: 12/11/2022] Open
Abstract
Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.
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24
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Abdallah C, Hedrich T, Koupparis A, Afnan J, Hall JA, Gotman J, Dubeau F, von Ellenrieder N, Frauscher B, Kobayashi E, Grova C. Clinical Yield of Electromagnetic Source Imaging and Hemodynamic Responses in Epilepsy: Validation With Intracerebral Data. Neurology 2022; 98:e2499-e2511. [PMID: 35473762 PMCID: PMC9231837 DOI: 10.1212/wnl.0000000000200337] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 02/21/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Accurate delineation of the seizure-onset zone (SOZ) in focal drug-resistant epilepsy often requires stereo-EEG (SEEG) recordings. Our aims were to propose a truly objective and quantitative comparison between EEG/magnetoencephalography (MEG) source imaging (EMSI), EEG/fMRI responses for similar spikes with primary irritative zone (PIZ) and SOZ defined by SEEG and to evaluate the value of EMSI and EEG/fMRI to predict postsurgical outcome. METHODS We identified patients with drug-resistant epilepsy who underwent EEG/MEG, EEG/fMRI, and subsequent SEEG at the Epilepsy Service from the Montreal Neurological Institute and Hospital. We quantified multimodal concordance within the SEEG channel space as spatial overlap with PIZ/SOZ and distances to the spike-onset, spike maximum amplitude and seizure core intracerebral channels by applying a new methodology consisting of converting EMSI results into SEEG electrical potentials (EMSIe-SEEG) and projecting the most significant fMRI response on the SEEG channels (fMRIp-SEEG). Spatial overlaps with PIZ/SOZ (AUCPIZ, AUCSOZ) were assessed by using the area under the receiver operating characteristic curve (AUC). Here, AUC represents the probability that a randomly picked active contact exhibited higher amplitude when located inside the spatial reference than outside. RESULTS Seventeen patients were included. Mean spatial overlaps with the PIZ and SOZ were 0.71 and 0.65 for EMSIe-SEEG and 0.57 and 0.62 for fMRIp-SEEG. Good EMSIe-SEEG spatial overlap with the PIZ was associated with smaller distance from the maximum EMSIe-SEEG contact to the spike maximum amplitude channel (median distance 14 mm). Conversely, good fMRIp-SEEG spatial overlap with the SOZ was associated with smaller distances from the maximum fMRIp-SEEG contact to the spike-onset and seizure core channels (median distances 10 and 5 mm, respectively). Surgical outcomes were correctly predicted by EEG/MEG in 12 of 15 (80%) patients and EEG/fMRI in 6 of 11(54%) patients. DISCUSSION With the use of a unique quantitative approach estimating EMSI and fMRI results in the reference SEEG channel space, EEG/MEG and EEG/fMRI accurately localized the SOZ and the PIZ. Precisely, EEG/MEG more accurately localized the PIZ, whereas EEG/fMRI was more sensitive to the SOZ. Both neuroimaging techniques provide complementary localization that can help guide SEEG implantation and select good candidates for surgery.
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Affiliation(s)
- Chifaou Abdallah
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada.
| | - Tanguy Hedrich
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Andreas Koupparis
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Jawata Afnan
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Jeffrey Alan Hall
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Jean Gotman
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Francois Dubeau
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Nicolas von Ellenrieder
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Birgit Frauscher
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Eliane Kobayashi
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Christophe Grova
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
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Abou Jaoude M, Jacobs CS, Sarkis RA, Jing J, Pellerin KR, Cole AJ, Cash SS, Westover MB, Lam AD. Noninvasive Detection of Hippocampal Epileptiform Activity on Scalp Electroencephalogram. JAMA Neurol 2022; 79:614-622. [PMID: 35499837 PMCID: PMC9062772 DOI: 10.1001/jamaneurol.2022.0888] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 03/09/2022] [Indexed: 01/18/2023]
Abstract
Importance The hippocampus is a highly epileptogenic brain region, yet over 90% of hippocampal epileptiform activity (HEA) cannot be identified on scalp electroencephalogram (EEG) by human experts. Currently, detection of HEA requires intracranial electrodes, which limits our understanding of the role of HEA in brain diseases. Objective To develop and validate a machine learning algorithm that accurately detects HEA from a standard scalp EEG, without the need for intracranial electrodes. Design, Setting, and Participants In this diagnostic study, conducted from 2008 to 2021, EEG data were used from patients with temporal lobe epilepsy (TLE) and healthy controls (HCs) to train and validate a deep neural network, HEAnet, to detect HEA on scalp EEG. Participants were evaluated at tertiary-level epilepsy centers at 2 academic hospitals: Massachusetts General Hospital (MGH) or Brigham and Women's Hospital (BWH). Included in the study were patients aged 12 to 78 years with a clinical diagnosis of TLE and HCs without epilepsy. Patients with TLE and HCs with a history of intracranial surgery were excluded from the study. Exposures Simultaneous intracranial EEG and/or scalp EEG. Main Outcomes and Measures Performance was assessed using cross-validated areas under the receiver operating characteristic curve (AUC ROC) and precision-recall curve (AUC PR) and additional clinically relevant metrics. Results HEAnet was trained and validated using data sets that were derived from a convenience sample of 141 eligible participants (97 with TLE and 44 HCs without epilepsy) whose retrospective EEG data were readily available. Data set 1 included the simultaneous scalp EEG and intracranial electrode recordings of 51 patients with TLE (mean [SD] age, 40.7 [15.9] years; 30 men [59%]) at MGH. An automatically generated training data set with 972 095 positive HEA examples was created, in addition to a held-out expert-annotated testing data set with 22 762 positive HEA examples. HEAnet's performance was validated on 2 independent scalp EEG data sets: (1) data set 2 (at MGH; 24 patients with TLE and 20 HCs; mean [SD] age, 42.3 [16.2] years; 17 men [39%]) and (2) data set 3 (at BWH; 22 patients with TLE and 24 HCs; mean [SD] age, 43.0 [14.4] years; 20 men [43%]). For single-event detection of HEA on data set 1, HEAnet achieved a mean (SD) AUC ROC of 0.89 (0.01) and a mean (SD) AUC PR of 0.39 (0.03). On external validation with data sets 2 and 3, HEAnet accurately distinguished TLE from HC (AUC ROC of 0.88 and 0.95, respectively) and predicted epilepsy lateralization with 100% and 92% accuracy, respectively. HEAnet tracked dynamic changes in HEA in response to seizure medication adjustments and performed comparably with human experts in diagnosing TLE from 1-hour scalp EEG recordings, diagnosing TLE in several individuals that experts missed. Without reducing specificity, addition of HEAnet to human expert EEG review increased sensitivity for diagnosing TLE in humans from 50% to 58% to 63% to 67%. Conclusions and Relevance Results of this diagnostic study suggest that HEAnet provides a novel, noninvasive, quantitative, and clinically relevant biomarker of hippocampal hyperexcitability in humans.
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Affiliation(s)
| | - Claire S. Jacobs
- Department of Neurology, Massachusetts General Hospital, Boston
- Harvard Medical School, Boston, Massachusetts
| | - Rani A. Sarkis
- Harvard Medical School, Boston, Massachusetts
- Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Jin Jing
- Department of Neurology, Massachusetts General Hospital, Boston
| | | | - Andrew J. Cole
- Department of Neurology, Massachusetts General Hospital, Boston
- Harvard Medical School, Boston, Massachusetts
| | - Sydney S. Cash
- Department of Neurology, Massachusetts General Hospital, Boston
- Harvard Medical School, Boston, Massachusetts
| | - M. Brandon Westover
- Department of Neurology, Massachusetts General Hospital, Boston
- Harvard Medical School, Boston, Massachusetts
| | - Alice D. Lam
- Department of Neurology, Massachusetts General Hospital, Boston
- Harvard Medical School, Boston, Massachusetts
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Bruzzone MJ, Issa NP, Wu S, Rose S, Esengul YT, Towle VL, Nordli D, Warnke PC, Tao JX. Hippocampal spikes have heterogeneous scalp EEG correlates important for defining IEDs. Epilepsy Res 2022; 182:106914. [DOI: 10.1016/j.eplepsyres.2022.106914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 02/20/2022] [Accepted: 03/27/2022] [Indexed: 11/03/2022]
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Satzer D, Esengul YT, Warnke PC, Issa NP, Nordli DR. SEEG in 3D: Interictal Source Localization From Intracerebral Recordings. Front Neurol 2022; 13:782880. [PMID: 35211078 PMCID: PMC8861202 DOI: 10.3389/fneur.2022.782880] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 01/14/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Stereo-electroencephalography (SEEG) uses a three-dimensional configuration of depth electrodes to localize epileptiform activity, but traditional analysis of SEEG is spatially restricted to the point locations of the electrode contacts. Interpolation of brain activity between contacts might allow for three-dimensional representation of epileptiform activity and avoid pitfalls of SEEG interpretation. OBJECTIVE The goal of this study was to validate SEEG-based interictal source localization and assess the ability of this technique to monitor far-field activity in non-implanted brain regions. METHODS Interictal epileptiform discharges were identified on SEEG in 26 patients who underwent resection, ablation, or disconnection of the suspected epileptogenic zone. Dipoles without (free) and with (scan) gray matter restriction, and current density (sLORETA and SWARM methods), were calculated using a finite element head model. Source localization results were compared to the conventional irritative zone (IZ) and the surgical treatment volumes (TV) of seizure-free vs. non-seizure-free patients. RESULTS The median distance from dipole solutions to the nearest contact in the conventional IZ was 7 mm (interquartile range 4-15 mm for free dipoles and 4-14 mm for scan dipoles). The IZ modeled with SWARM predicted contacts within the conventional IZ with 83% (75-100%) sensitivity and 94% (88-100%) specificity. The proportion of current within the TV was greater in seizure-free patients (P = 0.04) and predicted surgical outcome with 45% sensitivity and 93% specificity. Dipole solutions and sLORETA results did not correlate with seizure outcome. Addition of scalp EEG led to more superficial modeled sources (P = 0.03) and negated the ability to predict seizure outcome (P = 0.23). Removal of near-field data from contacts within the TV resulted in smearing of the current distribution (P = 0.007) and precluded prediction of seizure freedom (P = 0.20). CONCLUSIONS Source localization accurately represented interictal discharges from SEEG. The proportion of current within the TV distinguished between seizure-free and non-seizure-free patients when near-field recordings were obtained from the surgical target. The high prevalence of deep sources in this cohort likely obscured any benefit of concurrent scalp EEG. SEEG-based interictal source localization is useful in illustrating and corroborating the epileptogenic zone. Additional techniques are needed to localize far-field epileptiform activity from non-implanted brain regions.
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Affiliation(s)
- David Satzer
- Department of Neurosurgery, University of Chicago, Chicago, IL, United States
| | - Yasar T Esengul
- Department of Neurology, University of Chicago, Chicago, IL, United States
| | - Peter C Warnke
- Department of Neurosurgery, University of Chicago, Chicago, IL, United States
| | - Naoum P Issa
- Department of Neurology, University of Chicago, Chicago, IL, United States
| | - Douglas R Nordli
- Section of Child Neurology, Department of Pediatrics, University of Chicago, Chicago, IL, United States
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Abboud T, Mielke D, Rohde V. Mini Review: Impedance Measurement in Neuroscience and Its Prospective Application in the Field of Surgical Neurooncology. Front Neurol 2022; 12:825012. [PMID: 35111132 PMCID: PMC8801870 DOI: 10.3389/fneur.2021.825012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 12/27/2021] [Indexed: 11/13/2022] Open
Abstract
Impedance measurement of human tissue can be performed either in vivo or ex vivo. The majority of the in-vivo approaches are non-invasive, and few are invasive. To date, there is no gold standard for impedance measurement of intracranial tissue. In addition, most of the techniques addressing this topic are still experimental and have not found their way into clinical practice. This review covers available impedance measurement approaches in the neuroscience in general and specifically addresses recent advances made in the application of impedance measurement in the field of surgical neurooncology. It will provide an understandable picture on impedance measurement and give an overview of limitations that currently hinders clinical application and require future technical and conceptual solutions.
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Casale MJ, Marcuse LV, Young JJ, Jette N, Panov FE, Bender HA, Saad AE, Ghotra RS, Ghatan S, Singh A, Yoo JY, Fields MC. The Sensitivity of Scalp EEG at Detecting Seizures-A Simultaneous Scalp and Stereo EEG Study. J Clin Neurophysiol 2022; 39:78-84. [PMID: 32925173 PMCID: PMC8290181 DOI: 10.1097/wnp.0000000000000739] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
PURPOSE Compare the detection rate of seizures on scalp EEG with simultaneous intracranial stereo EEG (SEEG) recordings. METHODS Twenty-seven drug-resistant epilepsy patients undergoing SEEG with simultaneous scalp EEG as part of their surgical work-up were included. A total of 172 seizures were captured. RESULTS Of the 172 seizures detected on SEEG, 100 demonstrated scalp ictal patterns. Focal aware and subclinical seizures were less likely to be seen on scalp, with 33% of each observed when compared with focal impaired aware (97%) and focal to bilateral tonic-clonic seizures (100%) (P < 0.001). Of the 72 seizures without ictal scalp correlate, 32 demonstrated an abnormality during the SEEG seizure that was identical to an interictal abnormality. Seizures from patients with MRI lesions were statistically less likely to be seen on scalp than seizures from nonlesional patients (P = 0.0162). Stereo EEG seizures not seen on scalp were shorter in duration (49 seconds) compared with SEEG seizures seen on scalp (108.6 seconds) (P < 0.001). CONCLUSIONS Scalp EEG is not a sensitive tool for the detection of focal aware and subclinical seizures but is highly sensitive for the detection of focal impaired aware and focal to bilateral tonic-clonic seizures. Longer duration of seizure and seizures from patients without MRI lesions were more likely to be apparent on scalp. Abnormalities seen interictally may at times represent an underlying seizure. The cognitive, affective, and behavioral long-term effects of ongoing difficult-to-detect seizures are not known.
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Affiliation(s)
- Marc J. Casale
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - Lara V. Marcuse
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - James J. Young
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - Nathalie Jette
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - Fedor E. Panov
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - H. Allison Bender
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - Adam E. Saad
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - Ravi S. Ghotra
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - Saadi Ghatan
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - Anuradha Singh
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - Ji Yeoun Yoo
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
| | - Madeline C. Fields
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A
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Abdi-Sargezeh B, Valentin A, Alarcon G, Martin-Lopez D, Sanei S. Higher-order tensor decomposition based scalp-to-intracranial EEG projection for detection of interictal epileptiform discharges. J Neural Eng 2021; 18. [PMID: 34818640 DOI: 10.1088/1741-2552/ac3cc4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 11/24/2021] [Indexed: 11/12/2022]
Abstract
Objective.Interictal epileptiform discharges (IEDs) occur between two seizures onsets. IEDs are mainly captured by intracranial recordings and are often invisible over the scalp. This study proposes a model based on tensor factorization to map the time-frequency (TF) features of scalp EEG (sEEG) to the TF features of intracranial EEG (iEEG) in order to detect IEDs from over the scalp with high sensitivity.Approach.Continuous wavelet transform is employed to extract the TF features. Time, frequency, and channel modes of IED segments from iEEG recordings are concatenated into a four-way tensor. Tucker and CANDECOMP/PARAFAC decomposition techniques are employed to decompose the tensor into temporal, spectral, spatial, and segmental factors. Finally, TF features of both IED and non-IED segments from scalp recordings are projected onto the temporal components for classification.Main results.The model performance is obtained in two different approaches: within- and between-subject classification approaches. Our proposed method is compared with four other methods, namely a tensor-based spatial component analysis method, TF-based method, linear regression mapping model, and asymmetric-symmetric autoencoder mapping model followed by convolutional neural networks. Our proposed method outperforms all these methods in both within- and between-subject classification approaches by respectively achieving 84.2% and 72.6% accuracy values.Significance.The findings show that mapping sEEG to iEEG improves the performance of the scalp-based IED detection model. Furthermore, the tensor-based mapping model outperforms the autoencoder- and regression-based mapping models.
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Affiliation(s)
- Bahman Abdi-Sargezeh
- School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom
| | - Antonio Valentin
- Department of Clinical Neuroscience, King's College London, London, United Kingdom
| | - Gonzalo Alarcon
- Department of Neurology, Hamad General Hospital, Doha, Qatar
| | | | - Saeid Sanei
- School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom
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Yu T, Liu X, Wu J, Wang Q. Electrophysiological Biomarkers of Epileptogenicity in Alzheimer's Disease. Front Hum Neurosci 2021; 15:747077. [PMID: 34916917 PMCID: PMC8669481 DOI: 10.3389/fnhum.2021.747077] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 11/01/2021] [Indexed: 11/13/2022] Open
Abstract
Cortical network hyperexcitability is an inextricable feature of Alzheimer’s disease (AD) that also might accelerate its progression. Seizures are reported in 10–22% of patients with AD, and subclinical epileptiform abnormalities have been identified in 21–42% of patients with AD without seizures. Accurate identification of hyperexcitability and appropriate intervention to slow the compromise of cognitive functions of AD might open up a new approach to treatment. Based on the results of several studies, epileptiform discharges, especially those with specific features (including high frequency, robust morphology, right temporal location, and occurrence during awake or rapid eye movement states), frequent small sharp spikes (SSSs), temporal intermittent rhythmic delta activities (TIRDAs), and paroxysmal slow wave events (PSWEs) recorded in long-term scalp electroencephalogram (EEG) provide sufficient sensitivity and specificity in detecting cortical network hyperexcitability and epileptogenicity of AD. In addition, magnetoencephalogram (MEG), foramen ovale (FO) electrodes, and computational approaches help to find subclinical seizures that are invisible on scalp EEGs. We performed a comprehensive analysis of the aforementioned electrophysiological biomarkers of AD-related seizures.
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Affiliation(s)
- Tingting Yu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xiao Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jianping Wu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China
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Louviot S, Tyvaert L, Maillard LG, Colnat-Coulbois S, Dmochowski J, Koessler L. Transcranial Electrical Stimulation generates electric fields in deep human brain structures. Brain Stimul 2021; 15:1-12. [PMID: 34742994 DOI: 10.1016/j.brs.2021.11.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 10/21/2021] [Accepted: 11/01/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Transcranial electrical stimulation (TES) efficiency is related to the electric field (EF) magnitude delivered on the target. Very few studies (n = 4) have estimated the in-vivo intracerebral electric fields in humans. They have relied mainly on electrocorticographic recordings, which require a craniotomy impacting EF distribution, and did not investigate deep brain structures. OBJECTIVE To measure the electric field in deep brain structures during TES in humans in-vivo. Additionally, to investigate the effects of TES frequencies, intensities, and montages on the intracerebral EF. METHODS Simultaneous bipolar transcranial alternating current stimulation and intracerebral recordings (SEEG) were performed in 8 drug-resistant epileptic patients. TES was applied using small high-definition (HD) electrodes. Seven frequencies, two intensities and 15 montages were applied on one, six and one patients, respectively. RESULTS At 1 mA intensity, we found mean EF magnitudes of 0.21, 0.17 and 0.07 V·m-1 in the amygdala, hippocampus, and cingulate gyrus, respectively. An average of 0.14 ± 0.07 V·m-1 was measured in these deep brain structures. Mean EF magnitudes in these structures at 1Hz were 11% higher than at 300Hz (+0.03 V·m-1). The EF was correlated with the TES intensities. The TES montages that yielded the maximum EF in the amygdalae were T7-T8 and in the cingulate gyri were C3-FT10 and T7-C4. CONCLUSION TES at low intensities and with small HD electrodes can generate an EF in deep brain structures, irrespective of stimulation frequency. EF magnitude is correlated to the stimulation intensity and depends upon the stimulation montage.
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Affiliation(s)
- Samuel Louviot
- Université de Lorraine, CNRS, CRAN, F-54000, Nancy, France
| | - Louise Tyvaert
- Université de Lorraine, CNRS, CRAN, F-54000, Nancy, France; Université de Lorraine, CHRU-Nancy, Service de Neurologie, F-54000, Nancy, France
| | - Louis G Maillard
- Université de Lorraine, CNRS, CRAN, F-54000, Nancy, France; Université de Lorraine, CHRU-Nancy, Service de Neurologie, F-54000, Nancy, France
| | - Sophie Colnat-Coulbois
- Université de Lorraine, CNRS, CRAN, F-54000, Nancy, France; Université de Lorraine, CHRU-Nancy, Service de Neurochirurgie, F-54000, Nancy, France
| | - Jacek Dmochowski
- Department of Biomedical Engineering, City College of New York, New York, NY, USA
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Iachim E, Vespa S, Baroumand AG, Danthine V, Vrielynck P, de Tourtchaninoff M, Fierain A, Ribeiro Vaz JG, Raftopoulos C, Ferrao Santos S, van Mierlo P, El Tahry R. Automated electrical source imaging with scalp EEG to define the insular irritative zone: Comparison with simultaneous intracranial EEG. Clin Neurophysiol 2021; 132:2965-2978. [PMID: 34715421 DOI: 10.1016/j.clinph.2021.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 08/13/2021] [Accepted: 09/16/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To evaluate the accuracy of automatedinterictallow-density electrical source imaging (LD-ESI) to define the insular irritative zone (IZ) by comparing the simultaneous interictal ESI localization with the SEEG interictal activity. METHODS Long-term simultaneous scalp electroencephalography (EEG) and stereo-EEG (SEEG) with at least one depth electrode exploring the operculo-insular region(s) were analyzed. Automated interictal ESI was performed on the scalp EEG using standardized low-resolution brain electromagnetic tomography (sLORETA) and individual head models. A two-step analysis was performed: i) sublobar concordance betweencluster-based ESI localization and SEEG-based IZ; ii) time-locked ESI-/SEEG analysis. Diagnostic accuracy values were calculated using SEEG as reference standard. Subgroup analysis wascarried out, based onthe involvement of insular contacts in the seizure onset and patterns of insular interictal activity. RESULTS Thirty patients were included in the study. ESI showed an overall accuracy of 53% (C.I. 29-76%). Sensitivity and specificity were calculated as 53% (C.I. 29-76%), 55% (C.I. 23-83%) respectively. Higher accuracy was found in patients with frequent and dominant interictal insular spikes. CONCLUSIONS LD-ESI defines with good accuracy the insular implication in the IZ, which is not possible with classical interictalscalpEEG interpretation. SIGNIFICANCE Automated LD-ESI may be a valuable additional tool to characterize the epileptogenic zone in epilepsies with suspected insular involvement.
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Affiliation(s)
- Evelina Iachim
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Simone Vespa
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium.
| | - Amir G Baroumand
- Medical Image and Signal Processing Group (MEDISIP), Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; Epilog NV, Ghent, Belgium
| | - Venethia Danthine
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium
| | - Pascal Vrielynck
- Epileptology and Clinical Neurophysiology, Centre Neurologique William Lennox, Ottignies, Belgium
| | - Marianne de Tourtchaninoff
- Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Alexane Fierain
- Epileptology and Clinical Neurophysiology, Centre Neurologique William Lennox, Ottignies, Belgium
| | - Jose Geraldo Ribeiro Vaz
- Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | | | - Susana Ferrao Santos
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Pieter van Mierlo
- Medical Image and Signal Processing Group (MEDISIP), Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; Epilog NV, Ghent, Belgium
| | - Riëm El Tahry
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
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De Stefano P, Carboni M, Marquis R, Spinelli L, Seeck M, Vulliemoz S. Increased delta power as a scalp marker of epileptic activity: a simultaneous scalp and intracranial electroencephalography study. Eur J Neurol 2021; 29:26-35. [PMID: 34528320 PMCID: PMC9293335 DOI: 10.1111/ene.15106] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 09/09/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND PURPOSE The purpose was to evaluate whether intracranial interictal epileptiform discharges (IEDs) that are not visible on the scalp are associated with changes in the frequency spectrum on scalp electroencephalograms (EEGs). METHODS Simultaneous scalp high-density EEG and intracranial EEG recordings were recorded in nine patients undergoing pre-surgical invasive recordings for pharmaco-resistant temporal lobe epilepsy. Epochs with hippocampal IED visible on intracranial EEG (ic-IED) but not on scalp EEG were selected, as well as control epochs without ic-IED. Welch's power spectral density was computed for each scalp electrode and for each subject; the power spectral density was further averaged across the canonical frequency bands and compared between the two conditions with and without ic-IED. For each patient the peak frequency in the delta band (the significantly strongest frequency band in all patients) was determined during periods of ic-IED. The five electrodes showing strongest power at the peak frequency were also determined. RESULTS It was found that intracranial IEDs are associated with an increase in delta power on scalp EEGs, in particular at a frequency ≥1.4 Hz. Electrodes showing slow frequency power changes associated with IEDs were consistent with the hemispheric lateralization of IEDs. Electrodes with maximum power of slow activity were not limited to temporal regions but also involved frontal (bilateral or unilateral) regions. CONCLUSIONS In patients with a clinical picture suggestive of temporal lobe epilepsy, the presence of delta slowing ≥1.4 Hz in anterior temporal regions can represent a scalp marker of hippocampal IEDs. To our best knowledge this is the first study that demonstrates the co-occurrence of ic-IED and increased delta power.
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Affiliation(s)
- Pia De Stefano
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Margherita Carboni
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Renaud Marquis
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Laurent Spinelli
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Neurology Department, University Hospitals of Geneva, Geneva, Switzerland
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Abboud T, Hahn G, Just A, Paidhungat M, Nazarenus A, Mielke D, Rohde V. An insight into electrical resistivity of white matter and brain tumors. Brain Stimul 2021; 14:1307-1316. [PMID: 34481094 DOI: 10.1016/j.brs.2021.08.023] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/27/2021] [Accepted: 08/31/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND There is a lack of information regarding electrical properties of white matter and brain tumors. OBJECTIVE To investigate the feasibility of in-vivo measurement of electrical resistivity during brain surgery and establish a better understanding of the resistivity patterns of brain tumors in correlation to the white matter. METHODS A bipolar probe was used to measure electrical resistivity during surgery in a prospective cohort of patients with brain tumors. For impedance measurement, the probe applied a constant current of 0.7 μA with a frequency of 140 Hz. The measurement was performed in the white matter within and outside peritumoral edema as well as in non-enhancing, enhancing and necrotic tumor areas. Resistivity values expressed in ohmmeter (Ω∗m) were compared between different intracranial tissues and brain tumors. RESULTS Ninety-two patients (gliomas WHO II:16, WHO III:10, WHO IV:33, metastasis:33) were included. White matter outside peritumoral edema had higher resistivity values (13.3 ± 1.7 Ω∗m) than within peritumoral edema (8.5 ± 1.6 Ω∗m), and both had higher values than brain tumors including non-enhancing (WHO II:6.4 ± 1.3 Ω∗m, WHO III:6.3 ± 0.9 Ω∗m), enhancing (WHO IV:5 ± 1 Ω∗m, metastasis:5.4 ± 1.3 Ω∗m) and necrotic tumor areas (WHO IV:3.9 ± 1.1 Ω∗m, metastasis:4.3 ± 1.3 Ω∗m), p=<0.001. No difference was found between low-grade and anaplastic gliomas, p = 0.808, while resistivity values in both were higher than the highest values found in glioblastomas, p = 0.003 and p = 0.004, respectively. CONCLUSIONS The technique we applied enabled us to measure electrical resistivity of white matter and brain tumors in-vivo presumably with a significant effect with regard to dielectric polarization. Our results suggest that there are significant differences within different areas and subtypes of brain tumors and that white matter exhibits higher electrical resistivity than brain tumors.
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Affiliation(s)
- Tammam Abboud
- Department of Neurosurgery, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany.
| | - Günter Hahn
- Department of Anesthesiology, EIT Research Unit, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
| | - Anita Just
- Department of Anesthesiology, EIT Research Unit, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
| | - Mihika Paidhungat
- Department of Neurosurgery, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
| | - Angelina Nazarenus
- Department of Neurosurgery, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
| | - Dorothee Mielke
- Department of Neurosurgery, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
| | - Veit Rohde
- Department of Neurosurgery, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
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Bénar CG, Velmurugan J, López-Madrona VJ, Pizzo F, Badier JM. Detection and localization of deep sources in magnetoencephalography: A review. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2021. [DOI: 10.1016/j.cobme.2021.100285] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
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Abdi-Sargezeh B, Valentin A, Alarcon G, Sanei S. Incorporating Uncertainty in Data Labeling into Automatic Detection of Interictal Epileptiform Discharges from Concurrent Scalp-EEG via Multi-way Analysis. Int J Neural Syst 2021; 31:2150019. [PMID: 33775232 DOI: 10.1142/s0129065721500192] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Interictal epileptiform discharges (IEDs) are elicited from an epileptic brain, whereas they can also be due to other neurological abnormalities. The diversity in their morphologies, their strengths, and their sources within the brain cause a great deal of uncertainty in their labeling by clinicians. The aim of this study is therefore to exploit and incorporate this uncertainty (the probability of the waveform being an IED) in the IED detection system which combines spatial component analysis (SCA) with the IED probabilities referred to as SCA-IEDP-based method. For comparison, we also propose and study SCA-based method in which probability of the waveform being an IED is ignored. The proposed models are employed to detect IEDs in two different classification approaches: (1) subject-dependent and (2) subject-independent classification approaches. The proposed methods are compared with two other state-of-the-art methods namely, time-frequency features and tensor factorization methods. The proposed SCA-IEDP model has achieved superior performance in comparison with the traditional SCA and other competing methods. It achieved 79.9% and 63.4% accuracy values in subject-dependent and subject-independent classification approaches, respectively. This shows that considering the IED probabilities in designing an IED detection system can boost its performance.
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Affiliation(s)
| | - Antonio Valentin
- Department of Clinical Neuroscience, King's College London, London, UK
| | - Gonzalo Alarcon
- Department of Neurology, Hamad General Hospital, Doha, Qatar
| | - Saeid Sanei
- School of Science and Technology, Nottingham Trent University, Nottingham, UK
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Pyrzowski J, Le Douget JE, Fouad A, Siemiński M, Jędrzejczak J, Le Van Quyen M. Zero-crossing patterns reveal subtle epileptiform discharges in the scalp EEG. Sci Rep 2021; 11:4128. [PMID: 33602954 PMCID: PMC7892826 DOI: 10.1038/s41598-021-83337-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 12/14/2020] [Indexed: 11/08/2022] Open
Abstract
Clinical diagnosis of epilepsy depends heavily on the detection of interictal epileptiform discharges (IEDs) from scalp electroencephalographic (EEG) signals, which by purely visual means is far from straightforward. Here, we introduce a simple signal analysis procedure based on scalp EEG zero-crossing patterns which can extract the spatiotemporal structure of scalp voltage fluctuations. We analyzed simultaneous scalp and intracranial EEG recordings from patients with pharmacoresistant temporal lobe epilepsy. Our data show that a large proportion of intracranial IEDs manifest only as subtle, low-amplitude waveforms below scalp EEG background and could, therefore, not be detected visually. We found that scalp zero-crossing patterns allow detection of these intracranial IEDs on a single-trial level with millisecond temporal precision and including some mesial temporal discharges that do not propagate to the neocortex. Applied to an independent dataset, our method discriminated accurately between patients with epilepsy and normal subjects, confirming its practical applicability.
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Affiliation(s)
- Jan Pyrzowski
- Bioelectrics Lab, Institute of Brain and Spine (ICM), (UMRS 1127, CNRS UMR 7225), Pitié-Salpêtriere Hospital, 47 Boulevard de l'Hôpital, 75013, Paris, France
| | | | - Amal Fouad
- Bioelectrics Lab, Institute of Brain and Spine (ICM), (UMRS 1127, CNRS UMR 7225), Pitié-Salpêtriere Hospital, 47 Boulevard de l'Hôpital, 75013, Paris, France
- Department of Neurology, Ain-Shams University, Cairo, Egypt
| | - Mariusz Siemiński
- Department of Emergency Medicine, Medical University of Gdańsk, Gdańsk, Poland
| | - Joanna Jędrzejczak
- Department of Neurology and Epileptology, Medical Centre for Postgraduate Education, Warsaw, Poland
| | - Michel Le Van Quyen
- Bioelectrics Lab, Institute of Brain and Spine (ICM), (UMRS 1127, CNRS UMR 7225), Pitié-Salpêtriere Hospital, 47 Boulevard de l'Hôpital, 75013, Paris, France.
- Sorbonne University, UPMC Univ, Paris 06, 75005, Paris, France.
- Laboratoire D'Imagerie Biomédicale, (INSERM U1146UMR7371 CNRS, Sorbonne université), Campus des Cordeliers, 15 rue de l'Ecole de Médecine, 75006, Paris, France.
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Del Brutto OH, Wu S, Mera RM, Costa AF, Recalde BY, Issa NP. Cognitive decline among individuals with history of mild symptomatic SARS-CoV-2 infection: A longitudinal prospective study nested to a population cohort. Eur J Neurol 2021; 28:3245-3253. [PMID: 33576150 PMCID: PMC8014083 DOI: 10.1111/ene.14775] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 02/07/2021] [Accepted: 02/09/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND AND PURPOSE Neurological complications of SARS-CoV-2 infection are noticed among critically ill patients soon after disease onset. Information on delayed neurological sequelae of SARS-CoV-2 infection is nil. Following a longitudinal study design, the occurrence of cognitive decline among individuals with a history of mild symptomatic SARS-CoV-2 infection was assessed. METHODS Stroke- and seizure-free Atahualpa residents aged ≥40 years, who had pre-pandemic cognitive assessments as well as normal brain magnetic resonance imaging and electroencephalogram recordings, underwent repeated evaluations 6 months after a SARS-CoV-2 outbreak infection in Atahualpa. Patients requiring oxygen therapy, hospitalization, and those who had initial neurological manifestations were excluded. Cognitive decline was defined as a reduction in the Montreal Cognitive Assessment (MoCA) score between the post-pandemic and pre-pandemic assessments that was ≥4 points greater than the reduction observed between two pre-pandemic MoCAs. The relationship between SARS-CoV-2 infection and cognitive decline was assessed by fitting logistic mixed models for longitudinal data as well as exposure-effect models. RESULTS Of 93 included individuals (mean age 62.6 ± 11 years), 52 (56%) had a history of mild symptomatic SARS-CoV-2 infection. Post-pandemic MoCA decay was worse in seropositive individuals. Cognitive decline was recognized in 11/52 (21%) seropositive and 1/41 (2%) seronegative individuals. In multivariate analyses, the odds for developing cognitive decline were 18.1 times higher among SARS-CoV-2 seropositive individuals (95% confidence interval 1.75-188; p = 0.015). Exposure-effect models confirmed this association (β = 0.24; 95% confidence interval 0.07-0.41; p = 0.006). CONCLUSIONS This study provides evidence of cognitive decline among individuals with mild symptomatic SARS-CoV-2 infection. The pathogenesis of this complication remains unknown.
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Affiliation(s)
- Oscar H Del Brutto
- School of Medicine, Universidad Espíritu Santo-Ecuador, Samborondón, Ecuador
| | - Shasha Wu
- Department of Neurology, University of Chicago, Chicago, IL, USA
| | - Robertino M Mera
- Department of Epidemiology, Gilead Sciences, Inc, Foster City, CA, USA
| | - Aldo F Costa
- Department of Neurology, Hospital Universitario Reina Sofía, Cordoba, Spain
| | | | - Naoum P Issa
- Department of Neurology, University of Chicago, Chicago, IL, USA
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Lin FH, Lee HJ, Ahveninen J, Jääskeläinen IP, Yu HY, Lee CC, Chou CC, Kuo WJ. Distributed source modeling of intracranial stereoelectro-encephalographic measurements. Neuroimage 2021; 230:117746. [PMID: 33454414 DOI: 10.1016/j.neuroimage.2021.117746] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 12/11/2020] [Accepted: 01/06/2021] [Indexed: 11/17/2022] Open
Abstract
Intracranial stereoelectroencephalography (sEEG) provides unsurpassed sensitivity and specificity for human neurophysiology. However, functional mapping of brain functions has been limited because the implantations have sparse coverage and differ greatly across individuals. Here, we developed a distributed, anatomically realistic sEEG source-modeling approach for within- and between-subject analyses. In addition to intracranial event-related potentials (iERP), we estimated the sources of high broadband gamma activity (HBBG), a putative correlate of local neural firing. Our novel approach accounted for a significant portion of the variance of the sEEG measurements in leave-one-out cross-validation. After logarithmic transformations, the sensitivity and signal-to-noise ratio were linearly inversely related to the minimal distance between the brain location and electrode contacts (slope≈-3.6). The signa-to-noise ratio and sensitivity in the thalamus and brain stem were comparable to those locations at the vicinity of electrode contact implantation. The HGGB source estimates were remarkably consistent with analyses of intracranial-contact data. In conclusion, distributed sEEG source modeling provides a powerful neuroimaging tool, which facilitates anatomically-normalized functional mapping of human brain using both iERP and HBBG data.
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Affiliation(s)
- Fa-Hsuan Lin
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada; Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Hsin-Ju Lee
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Iiro P Jääskeläinen
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; International Laboratory of Social Neurobiology, Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation
| | - Hsiang-Yu Yu
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; Institute of Brain Science, Brain Research Center, National Yang-Ming University, Taipei, Taiwan
| | - Cheng-Chia Lee
- Institute of Brain Science, Brain Research Center, National Yang-Ming University, Taipei, Taiwan; Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chien-Chen Chou
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; Institute of Brain Science, Brain Research Center, National Yang-Ming University, Taipei, Taiwan
| | - Wen-Jui Kuo
- Institute of Neuroscience, National Yang Ming University, Taipei, Taiwan; Brain Research Center, National Yang Ming University, Taipei, Taiwan.
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Barborica A, Mindruta I, Sheybani L, Spinelli L, Oane I, Pistol C, Donos C, López-Madrona VJ, Vulliemoz S, Bénar CG. Extracting seizure onset from surface EEG with independent component analysis: Insights from simultaneous scalp and intracerebral EEG. NEUROIMAGE: CLINICAL 2021; 32:102838. [PMID: 34624636 PMCID: PMC8503578 DOI: 10.1016/j.nicl.2021.102838] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 09/16/2021] [Accepted: 09/20/2021] [Indexed: 11/01/2022] Open
Abstract
Independent component analysis (ICA) is able to identify seizure generators. Simultaneous long-term scalp-SEEG allows validation of the ICA results. Ability to record seizure onset patterns on scalp depends on generator depth.
The success of stereoelectroencephalographic (SEEG) investigations depends crucially on the hypotheses on the putative location of the seizure onset zone. This information is derived from non-invasive data either based on visual analysis or advanced source localization algorithms. While source localization applied to interictal spikes recorded on scalp is the classical method, it does not provide unequivocal information regarding the seizure onset zone. Raw ictal activity contains a mixture of signals originating from several regions of the brain as well as EMG artifacts, hampering direct input to the source localization algorithms. We therefore introduce a methodology that disentangles the various sources contributing to the scalp ictal activity using independent component analysis and uses equivalent current dipole localization as putative locus of ictal sources. We validated the results of our analysis pipeline by performing long-term simultaneous scalp – intracerebral (SEEG) recordings in 14 patients and analyzing the wavelet coherence between the independent component encoding the ictal discharge and the SEEG signals in 8 patients passing the inclusion criteria. Our results show that invasively recorded ictal onset patterns, including low-voltage fast activity, can be captured by the independent component analysis of scalp EEG. The visibility of the ictal activity strongly depends on the depth of the sources. The equivalent current dipole localization can point to the seizure onset zone (SOZ) with an accuracy that can be as high as 10 mm for superficially located sources, that gradually decreases for deeper seizure generators, averaging at 47 mm in the 8 analyzed patients. Independent component analysis is therefore shown to have a promising SOZ localizing value, indicating whether the seizure onset zone is neocortical, and its approximate location, or located in mesial structures. That may contribute to a better crafting of the hypotheses used as basis of the stereo-EEG implantations.
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Wennberg R, Tarazi A, Zumsteg D, Garcia Dominguez L. Electromagnetic evidence that benign epileptiform transients of sleep are traveling, rotating hippocampal spikes. Clin Neurophysiol 2020; 131:2915-2925. [DOI: 10.1016/j.clinph.2020.07.023] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 07/05/2020] [Accepted: 07/23/2020] [Indexed: 12/01/2022]
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Vorderwülbecke BJ, Carboni M, Tourbier S, Brunet D, Seeber M, Spinelli L, Seeck M, Vulliemoz S. High-density Electric Source Imaging of interictal epileptic discharges: How many electrodes and which time point? Clin Neurophysiol 2020; 131:2795-2803. [PMID: 33137569 DOI: 10.1016/j.clinph.2020.09.018] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 07/31/2020] [Accepted: 09/07/2020] [Indexed: 11/18/2022]
Abstract
OBJECTIVE To assess the value of caudal EEG electrodes over cheeks and neck for high-density electric source imaging (ESI) in presurgical epilepsy evaluation, and to identify the best time point during averaged interictal epileptic discharges (IEDs) for optimal ESI accuracy. METHODS We retrospectively examined presurgical 257-channel EEG recordings of 45 patients with pharmacoresistant focal epilepsy. By stepwise removal of cheek and neck electrodes, averaged IEDs were downsampled to 219, 204, and 156 EEG channels. Additionally, ESI at the IED's half-rise was compared to other time points. The respective sources of maximum activity were compared to the resected brain area and postsurgical outcome. RESULTS Caudal channels had disproportionately more artefacts. In 30 patients with favourable outcome, the 204-channel array yielded the most accurate results with ESI maxima < 10 mm from the resection in 67% and inside affected sublobes in 83%. Neither in temporal nor in extratemporal cases did the full 257-channel setup improve ESI accuracy. ESI was most accurate at 50% of the IED's rising phase. CONCLUSION Information from cheeks and neck electrodes did not improve high-density ESI accuracy, probably due to higher artefact load and suboptimal biophysical modelling. SIGNIFICANCE Very caudal EEG electrodes should be used for ESI with caution.
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Affiliation(s)
- Bernd J Vorderwülbecke
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Department of Neurology, Epilepsy-Center Berlin-Brandenburg, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
| | - Margherita Carboni
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland.
| | - Sebastien Tourbier
- Connectomics Lab, Department of Radiology, Lausanne University Hospital, Rue du Bugnon 46, 1011 Lausanne, Switzerland.
| | - Denis Brunet
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland.
| | - Martin Seeber
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland.
| | - Laurent Spinelli
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
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Lam AD, Noebels J. Night Watch on the Titanic: Detecting Early Signs of Epileptogenesis in Alzheimer Disease. Epilepsy Curr 2020; 20:369-374. [PMID: 33081517 PMCID: PMC7818196 DOI: 10.1177/1535759720964775] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Aberrant cortical network excitability is an inextricable feature of Alzheimer disease (AD) that can negatively impact memory and accelerate cognitive decline. Surface electroencephalogram spikes and intracranial recordings of nocturnal silent seizures in human AD, coupled with the abnormal neural synchrony that precedes development of behavioral seizures in mouse AD models, build the case for epileptogenesis as an early therapeutic target for AD. Since most individuals with AD do not develop overt seizures, leveraging functional biomarkers of epilepsy risk to stratify a heterogeneous AD patient population for treatment is research priority for successful clinical trial design. Who will benefit from antiseizure interventions, which one, and when should it begin?
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Affiliation(s)
- Alice D. Lam
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Jeffrey Noebels
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA
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Baldini S, Pittau F, Birot G, Rochas V, Tomescu MI, Vulliémoz S, Seeck M. Detection of epileptic activity in presumably normal EEG. Brain Commun 2020; 2:fcaa104. [PMID: 33094282 PMCID: PMC7566453 DOI: 10.1093/braincomms/fcaa104] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Revised: 04/27/2020] [Accepted: 05/15/2020] [Indexed: 11/18/2022] Open
Abstract
Monitoring epileptic activity in the absence of interictal discharges is a major need given the well-established lack of reliability of patients’ reports of their seizures. Up to now, there are no other tools than reviewing the seizure diary; however, seizures may not be remembered or dismissed voluntarily. In the present study, we set out to determine if EEG voltage maps of epileptogenic activity in individual patients can help to identify disease activity, even if their scalp EEG appears normal. Twenty-five patients with pharmacoresistant focal epilepsy were included. For each patient, 6 min of EEG with spikes (yes-spike) and without visually detectable epileptogenic discharges (no-spike) were selected from long-term monitoring recordings (EEG 31–37 channels). For each patient, we identified typical discharges, calculated their average and the corresponding scalp voltage map (‘spike-map’). We then fitted the spike-map for each patient on their (i) EEG epochs with visible spikes, (ii) epochs without any visible spike and (iii) EEGs of 48 controls. The global explained variance was used to estimate the presence of the spike-maps. The individual spike-map occurred more often in the spike-free EEGs of patients compared to EEGs of healthy controls (P = 0.001). Not surprisingly, this difference was higher if the EEGs contained spikes (P < 0.001). In patients, spike-maps were more frequent per second (P < 0.001) but with a shorter mean duration (P < 0.001) than in controls, for both no-spike and yes-spike EEGs. The amount of spike-maps was unrelated to clinical variables, like epilepsy severity, drug load or vigilance state. Voltage maps of spike activity are present very frequently in the scalp EEG of patients, even in presumably normal EEG. We conclude that spike-maps are a robust and potentially powerful marker to monitor subtle epileptogenic activity.
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Affiliation(s)
- Sara Baldini
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Francesca Pittau
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Gwenael Birot
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Vincent Rochas
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Miralena I Tomescu
- Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Serge Vulliémoz
- 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
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Issa NP, Tao JX. Placing BETS on a spectrum of small sharp spikes. Clin Neurophysiol 2020; 131:2910-2911. [PMID: 33023819 DOI: 10.1016/j.clinph.2020.09.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 09/10/2020] [Indexed: 10/23/2022]
Affiliation(s)
- Naoum P Issa
- Adult Epilepsy Center, Department of Neurology 5841 S. Maryland Ave., MC 2030 University of Chicago, Chicago, IL 60637, USA.
| | - James X Tao
- Adult Epilepsy Center, Department of Neurology 5841 S. Maryland Ave., MC 2030 University of Chicago, Chicago, IL 60637, USA
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Jabran Y, Mahmoudzadeh M, Martinez N, Heberlé C, Wallois F, Bourel-Ponchel E. Temporal and Spatial Dynamics of Different Interictal Epileptic Discharges: A Time-Frequency EEG Approach in Pediatric Focal Refractory Epilepsy. Front Neurol 2020; 11:941. [PMID: 33013634 PMCID: PMC7506028 DOI: 10.3389/fneur.2020.00941] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Accepted: 07/20/2020] [Indexed: 11/13/2022] Open
Abstract
Objective: Characterization of the spatial and temporal dynamics of interictal epileptic discharges (IED) using time-frequency analysis (TFA) and electrical-source localization (ESL). Methods: TFA was performed on IED (spikes, spike waves, and polyspike waves) recorded by high-density-EEG (HD-EEG) in 19 refractory focal epileptic children. Temporal modulations related to IEDs were analyzed in a time window around the IED peaks [−1,000 to 1,000 ms]. Spatial modulations were analyzed by ESL in the time-frequency and time domains. Results: IED were associated with complex power spectral modulations. We observed increases in power spectrum (IPS) patterns specific to IED type. For spikes, the TFA pattern consisted of an IPS (−100 to +100 ms, 4–50 Hz). For spike waves, the IPS was followed by a second IPS (+100 to +400 ms, 4–10 Hz), corresponding to the slow wave. IPS patterns were preceded (−400 to −100 ms, 4–40 Hz), and followed (+100 to +400 ms) by a decrease in the power spectrum (DPS) (n = 8). For 14 out of 19 patients, at least one ESL method was concordant with the epileptogenic area. For the remaining five patients, all of them had temporal epilepsies. ESL in the time-frequency domain (DPS/IPS) provided concordant (n = 6) or complementary (n = 4) information to the ESL in the time domain concerning the epileptogenic zone. ESL in time-frequency domain (DPS/IPS) was the only method to provide concordant information concerning the epileptogenic zone in three patients. Significance: TFA demonstrates complex time-frequency modulations of the neuronal networks around IED, suggesting that the pathological mechanisms are initiated well before onset of the classical hyper-synchronization of the IED. Combining time and time-frequency analysis of the ESL provides complementary information to define the epileptogenic zone in refractory focal epilepsy.
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Affiliation(s)
- Younes Jabran
- INSERM UMR 1105, Research Group on Multimodal Analysis of Brain Function, University of Picardie Jules Verne, Amiens, France
| | - Mahdi Mahmoudzadeh
- INSERM UMR 1105, Research Group on Multimodal Analysis of Brain Function, University of Picardie Jules Verne, Amiens, France
| | - Nicolas Martinez
- INSERM UMR 1105, Research Group on Multimodal Analysis of Brain Function, University of Picardie Jules Verne, Amiens, France
| | - Claire Heberlé
- INSERM UMR 1105, Pediatric Neurophysiology Unit, Amiens University Hospital, Amiens, France
| | - Fabrice Wallois
- INSERM UMR 1105, Research Group on Multimodal Analysis of Brain Function, University of Picardie Jules Verne, Amiens, France.,INSERM UMR 1105, Pediatric Neurophysiology Unit, Amiens University Hospital, Amiens, France
| | - Emilie Bourel-Ponchel
- INSERM UMR 1105, Research Group on Multimodal Analysis of Brain Function, University of Picardie Jules Verne, Amiens, France.,INSERM UMR 1105, Pediatric Neurophysiology Unit, Amiens University Hospital, Amiens, France
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Fahimi Hnazaee M, Wittevrongel B, Khachatryan E, Libert A, Carrette E, Dauwe I, Meurs A, Boon P, Van Roost D, Van Hulle MM. Localization of deep brain activity with scalp and subdural EEG. Neuroimage 2020; 223:117344. [PMID: 32898677 DOI: 10.1016/j.neuroimage.2020.117344] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 07/27/2020] [Accepted: 08/31/2020] [Indexed: 01/11/2023] Open
Abstract
To what extent electrocorticography (ECoG) and electroencephalography (scalp EEG) differ in their capability to locate sources of deep brain activity is far from evident. Compared to EEG, the spatial resolution and signal-to-noise ratio of ECoG is superior but its spatial coverage is more restricted, as is arguably the volume of tissue activity effectively measured from. Moreover, scalp EEG studies are providing evidence of locating activity from deep sources such as the hippocampus using high-density setups during quiet wakefulness. To address this question, we recorded a multimodal dataset from 4 patients with refractory epilepsy during quiet wakefulness. This data comprises simultaneous scalp, subdural and depth EEG electrode recordings. The latter was located in the hippocampus or insula and provided us with our "ground truth" for source localization of deep activity. We applied independent component analysis (ICA) for the purpose of separating the independent sources in theta, alpha and beta frequency band activity. In all patients subdural- and scalp EEG components were observed which had a significant zero-lag correlation with one or more contacts of the depth electrodes. Subsequent dipole modeling of the correlating components revealed dipole locations that were significantly closer to the depth electrodes compared to the dipole location of non-correlating components. These findings support the idea that components found in both recording modalities originate from neural activity in close proximity to the depth electrodes. Sources localized with subdural electrodes were ~70% closer to the depth electrode than sources localized with EEG with an absolute improvement of around ~2cm. In our opinion, this is not a considerable improvement in source localization accuracy given that, for clinical purposes, ECoG electrodes were implanted in close proximity to the depth electrodes. Furthermore, the ECoG grid attenuates the scalp EEG, due to the electrically isolating silastic sheets in which the ECoG electrodes are embedded. Our results on dipole modeling show that the deep source localization accuracy of scalp EEG is comparable to that of ECoG. SIGNIFICANCE STATEMENT: Deep and subcortical regions play an important role in brain function. However, as joint recordings at multiple spatial scales to study brain function in humans are still scarce, it is still unresolved to what extent ECoG and EEG differ in their capability to locate sources of deep brain activity. To the best of our knowledge, this is the first study presenting a dataset of simultaneously recorded EEG, ECoG and depth electrodes in the hippocampus or insula, with a focus on non-epileptiform activity (quiet wakefulness). Furthermore, we are the first study to provide experimental findings on the comparison of source localization of deep cortical structures between invasive and non-invasive brain activity measured from the cortical surface.
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Affiliation(s)
| | - Benjamin Wittevrongel
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven, Belgium
| | - Elvira Khachatryan
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven, Belgium
| | - Arno Libert
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven, Belgium
| | - Evelien Carrette
- Faculty of Medicine and Health Sciences, Ghent University Hospital, Ghent, Belgium
| | - Ine Dauwe
- Faculty of Medicine and Health Sciences, Ghent University Hospital, Ghent, Belgium
| | - Alfred Meurs
- Faculty of Medicine and Health Sciences, Ghent University Hospital, Ghent, Belgium
| | - Paul Boon
- Faculty of Medicine and Health Sciences, Ghent University Hospital, Ghent, Belgium
| | - Dirk Van Roost
- Faculty of Medicine and Health Sciences, Ghent University Hospital, Ghent, Belgium
| | - Marc M Van Hulle
- Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven, Belgium
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Jacques C, Jonas J, Maillard L, Colnat-Coulbois S, Rossion B, Koessler L. Fast periodic visual stimulation to highlight the relationship between human intracerebral recordings and scalp electroencephalography. Hum Brain Mapp 2020; 41:2373-2388. [PMID: 32237021 PMCID: PMC7268031 DOI: 10.1002/hbm.24952] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Revised: 01/23/2020] [Accepted: 02/03/2020] [Indexed: 12/13/2022] Open
Abstract
Despite being of primary importance for fundamental research and clinical studies, the relationship between local neural population activity and scalp electroencephalography (EEG) in humans remains largely unknown. Here we report simultaneous scalp and intracerebral EEG responses to face stimuli in a unique epileptic patient implanted with 27 intracerebral recording contacts in the right occipitotemporal cortex. The patient was shown images of faces appearing at a frequency of 6 Hz, which elicits neural responses at this exact frequency. Response quantification at this frequency allowed to objectively relate the neural activity measured inside and outside the brain. The patient exhibited typical 6 Hz responses on the scalp at the right occipitotemporal sites. Moreover, there was a clear spatial correspondence between these scalp responses and intracerebral signals in the right lateral inferior occipital gyrus, both in amplitude and in phase. Nevertheless, the signal measured on the scalp and inside the brain at nearby locations showed a 10-fold difference in amplitude due to electrical insulation from the head. To further quantify the relationship between the scalp and intracerebral recordings, we used an approach correlating time-varying signals at the stimulation frequency across scalp and intracerebral channels. This analysis revealed a focused and right-lateralized correspondence between the scalp and intracerebral recordings that were specific to the face stimulation is more broadly distributed in various control situations. These results demonstrate the interest of a frequency tagging approach in characterizing the electrical propagation from brain sources to scalp EEG sensors and in identifying the cortical sources of brain functions from these recordings.
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Affiliation(s)
- Corentin Jacques
- Psychological Sciences Research Institute and Institute of Neuroscience, Université Catholique de Louvain (UCLouvain), Louvain-la-Neuve, Belgium
- Center for Developmental Psychiatry, Department of Neurosciences, KULeuven, Belgium
| | - Jacques Jonas
- Université de Lorraine, CNRS, CRAN, F-54000, Nancy, France
- Université de Lorraine, CHRU-Nancy, Service de Neurologie, F-54000, Nancy, France
| | - Louis Maillard
- Université de Lorraine, CNRS, CRAN, F-54000, Nancy, France
- Université de Lorraine, CHRU-Nancy, Service de Neurologie, F-54000, Nancy, France
| | - Sophie Colnat-Coulbois
- Université de Lorraine, CNRS, CRAN, F-54000, Nancy, France
- Université de Lorraine, CHRU-Nancy, Service de Neurochirurgie, F-54000, Nancy, France
| | - Bruno Rossion
- Psychological Sciences Research Institute and Institute of Neuroscience, Université Catholique de Louvain (UCLouvain), Louvain-la-Neuve, Belgium
- Université de Lorraine, CNRS, CRAN, F-54000, Nancy, France
- Université de Lorraine, CHRU-Nancy, Service de Neurologie, F-54000, Nancy, France
| | - Laurent Koessler
- Université de Lorraine, CNRS, CRAN, F-54000, Nancy, France
- Université de Lorraine, CHRU-Nancy, Service de Neurologie, F-54000, Nancy, France
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50
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Rikir E, Maillard LG, Abdallah C, Gavaret M, Bartolomei F, Vignal JP, Colnat-Coulbois S, Koessler L. Respective Contribution of Ictal and Inter-ictal Electrical Source Imaging to Epileptogenic Zone Localization. Brain Topogr 2020; 33:384-402. [DOI: 10.1007/s10548-020-00768-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 04/07/2020] [Indexed: 10/24/2022]
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