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Vila-Vidal M, Craven-Bartle Corominas F, Gilson M, Zucca R, Principe A, Rocamora R, Deco G, Tauste Campo A. A comparative study between a power and a connectivity sEEG biomarker for seizure-onset zone identification in temporal lobe epilepsy. J Neurosci Methods 2024; 411:110238. [PMID: 39168253 DOI: 10.1016/j.jneumeth.2024.110238] [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: 12/11/2023] [Revised: 07/12/2024] [Accepted: 07/26/2024] [Indexed: 08/23/2024]
Abstract
BACKGROUND Ictal stereo-encephalography (sEEG) biomarkers for seizure onset zone (SOZ) localization can be classified depending on whether they target abnormalities in signal power or functional connectivity between signals, and they may depend on the frequency band and time window at which they are estimated. NEW METHOD This work aimed to compare and optimize the performance of a power and a connectivity-based biomarker to identify SOZ contacts from ictal sEEG recordings. To do so, we used a previously introduced power-based measure, the normalized mean activation (nMA), which quantifies the ictal average power activation. Similarly, we defined the normalized mean strength (nMS), to quantify the ictal mean functional connectivity of every contact with the rest. The optimal frequency bands and time windows were selected based on optimizing AUC and F2-score. RESULTS The analysis was performed on a dataset of 67 seizures from 10 patients with pharmacoresistant temporal lobe epilepsy. Our results suggest that the power-based biomarker generally performs better for the detection of SOZ than the connectivity-based one. However, an equivalent performance level can be achieved when both biomarkers are independently optimized. Optimal performance was achieved in the beta and lower-gamma range for the power biomarker and in the lower- and higher-gamma range for connectivity, both using a 20 or 30 s period after seizure onset. CONCLUSIONS The results of this study highlight the importance of this optimization step over frequency and time windows when comparing different SOZ discrimination biomarkers. This information should be considered when training SOZ classifiers on retrospective patients' data for clinical applications.
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Affiliation(s)
- Manel Vila-Vidal
- Computational Biology and Complex Systems, Department of Physics, Universitat Politècnica de Catalunya, 08028, Barcelona, Spain; Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08005, Barcelona, Spain.
| | - Ferran Craven-Bartle Corominas
- Computational Biology and Complex Systems, Department of Physics, Universitat Politècnica de Catalunya, 08028, Barcelona, Spain
| | - Matthieu Gilson
- Institut de Neurosciences des Systèmes (INS, UMR1106), INSERM-AMU, 13005 Marseille, France
| | - Riccardo Zucca
- Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08005, Barcelona, Spain; Hospital del Mar Medical Research Institute, 08003, Barcelona, Spain; Donders Centre for Neuroscience, Radboud University, Nijmegen, Netherlands
| | - Alessandro Principe
- Hospital del Mar Medical Research Institute, 08003, Barcelona, Spain; Faculty of Health and Life Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain; Epilepsy Monitoring Unit, Department of Neurology, Hospital del Mar, 08003, Barcelona, Spain
| | - Rodrigo Rocamora
- Hospital del Mar Medical Research Institute, 08003, Barcelona, Spain; Faculty of Health and Life Sciences, Universitat Pompeu Fabra, 08003, Barcelona, Spain; Epilepsy Monitoring Unit, Department of Neurology, Hospital del Mar, 08003, Barcelona, Spain.
| | - Gustavo Deco
- Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08005, Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats, 08010, Barcelona, Spain
| | - Adrià Tauste Campo
- Computational Biology and Complex Systems, Department of Physics, Universitat Politècnica de Catalunya, 08028, Barcelona, Spain
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Zillgitt AJ, Mong ER, Manasseh AM, Guider HC, Baki N, Staudt MD. Exploration of epileptic networks in temporal lobe encephaloceles with stereotactic EEG: Electroclinical characteristics and surgical outcomes. Epilepsia Open 2024. [PMID: 39374038 DOI: 10.1002/epi4.13063] [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: 07/08/2024] [Revised: 08/31/2024] [Accepted: 09/17/2024] [Indexed: 10/08/2024] Open
Abstract
OBJECTIVE Temporal lobe encephaloceles (TLEN) have been implicated as a cause of temporal lobe epilepsy (TLE), the treatment which is primarily surgical; however, there is no clear consensus on the optimal surgical approach, because it is unclear whether TLE related to TLEN can be addressed by a restricted encephalocele resection or if a more extensive resection is required. The aim of the current article is to report the clinical and electrophysiological profile of patients with TLE secondary to TLEN who underwent stereotactic electroencephalography (SEEG) implantation to identify the epileptogenic network. METHODS A retrospective review was performed of patients with TLE related to TLEN who underwent SEEG implantation. Medical charts were reviewed for demographic data, the results of noninvasive and invasive investigations, and operative details. Surgical outcomes were based on Engel classification with at least 6 months follow-up. RESULTS Nine patients were identified. The mean age at epilepsy onset was 28 years (range, 15-41 years), and 7/9 patients were female. Scalp EEG revealed interictal epileptiform activity most often maximum in the frontotemporal and/or temporal regions. A discrete TLEN was often not identified on initial imaging, but was identified during re-review or at the time of surgery. Seizure onset zones during SEEG were localized to the mesial temporal structures, the temporal pole, or both. One patient became seizure-free following SEEG and another refused further surgery. Of the 7 patients who underwent epilepsy surgery, 5/7 underwent an anterior temporal lobectomy-surgical outcomes were favorable, with 5/7 achieving Engel I outcomes. SIGNIFICANCE Invasive SEEG monitoring demonstrated ictal onsets may not be restricted to the TLEN, and often the temporal pole and mesial structures are involved at seizure onset. Ictal propagation patterns vary significantly, which may be related to the underlying pathology and explain the variability in semiology. These findings may inform surgical treatment options. PLAIN LANGUAGE SUMMARY Temporal lobe encephaloceles can cause intractable epilepsy, although their presence may be missed on routine imaging. The management of encephaloceles is primarily surgical; however, the optimal surgical approach can be unclear. Invasive monitoring with SEEG may help characterize the epileptogenic network and result in more optimal surgical outcomes.
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Affiliation(s)
- Andrew J Zillgitt
- Department of Neurology, Corewell Health William Beaumont University Hospital Neuroscience Center, Adult Comprehensive Epilepsy Center, Royal Oak, Michigan, USA
| | - Eric R Mong
- Department of Neurosurgery, Corewell Health William Beaumont University Hospital Neuroscience Center, Royal Oak, Michigan, USA
| | - Angelique M Manasseh
- Department of Neurology, Corewell Health William Beaumont University Hospital Neuroscience Center, Adult Comprehensive Epilepsy Center, Royal Oak, Michigan, USA
| | - Hannah C Guider
- Department of Neurology, Corewell Health William Beaumont University Hospital Neuroscience Center, Adult Comprehensive Epilepsy Center, Royal Oak, Michigan, USA
| | - Nour Baki
- Department of Neurology, Corewell Health William Beaumont University Hospital Neuroscience Center, Adult Comprehensive Epilepsy Center, Royal Oak, Michigan, USA
| | - Michael D Staudt
- Department of Neurosurgery, Corewell Health William Beaumont University Hospital Neuroscience Center, Royal Oak, Michigan, USA
- Department of Neurological Surgery, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
- Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
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Jiao M, Xian X, Wang B, Zhang Y, Yang S, Chen S, Sun H, Liu F. XDL-ESI: Electrophysiological Sources Imaging via explainable deep learning framework with validation on simultaneous EEG and iEEG. Neuroimage 2024; 299:120802. [PMID: 39173694 DOI: 10.1016/j.neuroimage.2024.120802] [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: 04/12/2024] [Revised: 08/17/2024] [Accepted: 08/19/2024] [Indexed: 08/24/2024] Open
Abstract
Electroencephalography (EEG) or Magnetoencephalography (MEG) source imaging aims to estimate the underlying activated brain sources to explain the observed EEG/MEG recordings. Solving the inverse problem of EEG/MEG Source Imaging (ESI) is challenging due to its ill-posed nature. To achieve a unique solution, it is essential to apply sophisticated regularization constraints to restrict the solution space. Traditionally, the design of regularization terms is based on assumptions about the spatiotemporal structure of the underlying source dynamics. In this paper, we propose a novel paradigm for ESI via an Explainable Deep Learning framework, termed as XDL-ESI, which connects the iterative optimization algorithm with deep learning architecture by unfolding the iterative updates with neural network modules. The proposed framework has the advantages of (1) establishing a data-driven approach to model the source solution structure instead of using hand-crafted regularization terms; (2) improving the robustness of source solutions by introducing a topological loss that leverages the geometric spatial information applying varying penalties on distinct localization errors; (3) improving the reconstruction efficiency and interpretability as it inherits the advantages from both the iterative optimization algorithms (interpretability) and deep learning approaches (function approximation). The proposed XDL-ESI framework provides an efficient, accurate, and interpretable paradigm to solve the ESI inverse problem with satisfactory performance in both simulated data and real clinical data. Specially, this approach is further validated using simultaneous EEG and intracranial EEG (iEEG).
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Affiliation(s)
- Meng Jiao
- Department of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ, 07030, United States
| | - Xiaochen Xian
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, United States
| | - Boyu Wang
- Department of Computer Science, University of Western Ontario, Ontario, N6A 3K7, Canada
| | - Yu Zhang
- Department of Bioengineering, Lehigh University, Bethlehem, PA, 18015, United States
| | - Shihao Yang
- Department of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ, 07030, United States
| | - Spencer Chen
- Department of Neurosurgery, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, 08901, United States
| | - Hai Sun
- Department of Neurosurgery, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, 08901, United States
| | - Feng Liu
- Department of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ, 07030, United States; Semcer Center for Healthcare Innovation, Stevens Institute of Technology, Hoboken, NJ, 07030, United States.
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Azilinon M, Wang HE, Makhalova J, Zaaraoui W, Ranjeva JP, Bartolomei F, Guye M, Jirsa V. Brain sodium MRI-derived priors support the estimation of epileptogenic zones using personalized model-based methods in epilepsy. Netw Neurosci 2024; 8:673-696. [PMID: 39355432 PMCID: PMC11340996 DOI: 10.1162/netn_a_00371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Accepted: 03/06/2024] [Indexed: 10/03/2024] Open
Abstract
Patients presenting with drug-resistant epilepsy are eligible for surgery aiming to remove the regions involved in the production of seizure activities, the so-called epileptogenic zone network (EZN). Thus the accurate estimation of the EZN is crucial. Data-driven, personalized virtual brain models derived from patient-specific anatomical and functional data are used in Virtual Epileptic Patient (VEP) to estimate the EZN via optimization methods from Bayesian inference. The Bayesian inference approach used in previous VEP integrates priors, based on the features of stereotactic-electroencephalography (SEEG) seizures' recordings. Here, we propose new priors, based on quantitative 23Na-MRI. The 23Na-MRI data were acquired at 7T and provided several features characterizing the sodium signal decay. The hypothesis is that the sodium features are biomarkers of neuronal excitability related to the EZN and will add additional information to VEP estimation. In this paper, we first proposed the mapping from 23Na-MRI features to predict the EZN via a machine learning approach. Then, we exploited these predictions as priors in the VEP pipeline. The statistical results demonstrated that compared with the results from current VEP, the result from VEP based on 23Na-MRI prior has better balanced accuracy, and the similar weighted harmonic mean of the precision and recall.
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Affiliation(s)
- Mikhael Azilinon
- Aix Marseille Université, INSERM, Institut de Neurosciences des Systèmes (INS) UMR 1106, Marseille, France
- Aix Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Timone University Hospital, CEMEREM, Marseille, France
| | - Huifang E Wang
- Aix Marseille Université, INSERM, Institut de Neurosciences des Systèmes (INS) UMR 1106, Marseille, France
| | - Julia Makhalova
- APHM, Timone University Hospital, CEMEREM, Marseille, France
- APHM, Epileptology and Clinical Neurophysiology Department, Timone Hospital, Marseille, France
| | - Wafaa Zaaraoui
- Aix Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Timone University Hospital, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Timone University Hospital, CEMEREM, Marseille, France
| | - Fabrice Bartolomei
- Aix Marseille Université, INSERM, Institut de Neurosciences des Systèmes (INS) UMR 1106, Marseille, France
- APHM, Epileptology and Clinical Neurophysiology Department, Timone Hospital, Marseille, France
| | - Maxime Guye
- Aix Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Timone University Hospital, CEMEREM, Marseille, France
| | - Viktor Jirsa
- Aix Marseille Université, INSERM, Institut de Neurosciences des Systèmes (INS) UMR 1106, Marseille, France
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Lagarde S, Bartolomei F. Sink into the epileptogenic zone: findings from directed SEEG functional connectivity decomposition. Brain 2024; 147:2902-2905. [PMID: 39074199 DOI: 10.1093/brain/awae256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Accepted: 07/25/2024] [Indexed: 07/31/2024] Open
Abstract
This scientific commentary refers to ‘The interictal suppression hypothesis is the dominant differentiator of seizure onset zones in focal epilepsy’ by Doss et al. (https://doi.org/10.1093/brain/awae189).
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Affiliation(s)
- Stanislas Lagarde
- Epileptology and Cerebral Rhythmology Department (member of the ERN EpiCARE Network), APHM, Timone Hospital, 13005 Marseille, France
- INS, Institut de Neurosciences des Systèmes, Aix Marseille University, INSERM, 13005 Marseille, France
| | - Fabrice Bartolomei
- Epileptology and Cerebral Rhythmology Department (member of the ERN EpiCARE Network), APHM, Timone Hospital, 13005 Marseille, France
- INS, Institut de Neurosciences des Systèmes, Aix Marseille University, INSERM, 13005 Marseille, France
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6
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Evans JL, Bramlet MT, Davey C, Bethke E, Anderson AT, Huesmann G, Varatharajah Y, Maldonado A, Amos JR, Sutton BP. SEEG4D: a tool for 4D visualization of stereoelectroencephalography data. Front Neuroinform 2024; 18:1465231. [PMID: 39290351 PMCID: PMC11405301 DOI: 10.3389/fninf.2024.1465231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Accepted: 08/21/2024] [Indexed: 09/19/2024] Open
Abstract
Epilepsy is a prevalent and serious neurological condition which impacts millions of people worldwide. Stereoelectroencephalography (sEEG) is used in cases of drug resistant epilepsy to aid in surgical resection planning due to its high spatial resolution and ability to visualize seizure onset zones. For accurate localization of the seizure focus, sEEG studies combine pre-implantation magnetic resonance imaging, post-implant computed tomography to visualize electrodes, and temporally recorded sEEG electrophysiological data. Many tools exist to assist in merging multimodal spatial information; however, few allow for an integrated spatiotemporal view of the electrical activity. In the current work, we present SEEG4D, an automated tool to merge spatial and temporal data into a complete, four-dimensional virtual reality (VR) object with temporal electrophysiology that enables the simultaneous viewing of anatomy and seizure activity for seizure localization and presurgical planning. We developed an automated, containerized pipeline to segment tissues and electrode contacts. Contacts are aligned with electrical activity and then animated based on relative power. SEEG4D generates models which can be loaded into VR platforms for viewing and planning with the surgical team. Automated contact segmentation locations are within 1 mm of trained raters and models generated show signal propagation along electrodes. Critically, spatial-temporal information communicated through our models in a VR space have potential to enhance sEEG pre-surgical planning.
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Affiliation(s)
- James L Evans
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, United States
| | - Matthew T Bramlet
- University of Illinois College of Medicine, Peoria, IL, United States
- Jump Trading Simulation and Education Center, Peoria, IL, United States
| | - Connor Davey
- Jump Trading Simulation and Education Center, Peoria, IL, United States
| | - Eliot Bethke
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, United States
| | - Aaron T Anderson
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Department of Neurology, Carle Foundation Hospital, Urbana, IL, United States
| | - Graham Huesmann
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Department of Neurology, Carle Foundation Hospital, Urbana, IL, United States
- Department of Molecular and Integrative Physiology, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Carle Illinois College of Medicine, University of Illinois Urbana-Champaign, Urbana, IL, United States
| | - Yogatheesan Varatharajah
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Andres Maldonado
- Department of Neurosurgery, OSF Healthcare, Peoria, IL, United States
| | - Jennifer R Amos
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Carle Illinois College of Medicine, University of Illinois Urbana-Champaign, Urbana, IL, United States
| | - Bradley P Sutton
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Carle Illinois College of Medicine, University of Illinois Urbana-Champaign, Urbana, IL, United States
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Bartolomei F, Bratu IF. Status epilepticus and psychosis: Lessons from SEEG. Epilepsy Behav 2024; 158:109911. [PMID: 38924969 DOI: 10.1016/j.yebeh.2024.109911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 06/16/2024] [Accepted: 06/16/2024] [Indexed: 06/28/2024]
Abstract
Psychotic manifestations are a classic feature of non-convulsive status epilepticus (NCSE) of temporal origin. For several decades now, the various psychiatric manifestations of NCSE have been described, and in particular, the diagnostic challenges they pose. However, studies using stereotactic-EEG (SEEG) recordings are very rare. Only a few cases have been reported, but they demonstrated the anatomical substrate of certain manifestations, including hallucinations, delusions, and emotional changes. The post-ictal origin of some of the manifestations should be emphasized. More generally, SEEG has shown that seizures affecting the temporal and frontal limbic systems can lead to intense emotional experiences and behavioural disturbances.
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Affiliation(s)
- Fabrice Bartolomei
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France; APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France.
| | - Ionuț-Flavius Bratu
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France; APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
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8
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Köksal-Ersöz E, Makhalova J, Yochum M, Bénar CG, Guye M, Bartolomei F, Wendling F, Merlet I. Whole-brain simulation of interictal epileptic discharges for patient-specific interpretation of interictal SEEG data. Neurophysiol Clin 2024; 54:103005. [PMID: 39029213 DOI: 10.1016/j.neucli.2024.103005] [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: 01/24/2024] [Revised: 07/08/2024] [Accepted: 07/09/2024] [Indexed: 07/21/2024] Open
Abstract
In patients with refractory epilepsy, the clinical interpretation of stereoelectroencephalographic (SEEG) signals is crucial to delineate the epileptogenic network that should be targeted by surgery. We propose a pipeline of patient-specific computational modeling of interictal epileptic activity to improve the definition of regions of interest. Comparison between the computationally defined regions of interest and the resected region confirmed the efficiency of the pipeline. This result suggests that computational modeling can be used to reconstruct signals and aid clinical interpretation.
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Affiliation(s)
| | - Julia Makhalova
- Assistance Publique-Hôpitaux de Marseille, Service d'Épileptologie et de Rythmologie Cérébrale, Hôpital La Timone, Marseille, France; Aix Marseille Univ, CNRS, CRMBM UMR 7339, Marseille, France
| | - Maxime Yochum
- Univ Rennes, INSERM, LTSI - UMR 1099, Rennes, France
| | - Christian-G Bénar
- Aix Marseille Univ, CNRS, CRMBM UMR 7339, Marseille, France; Institut de Neurosciences des Systèmes (INS, UMR 1106), Aix Marseille Université, INSERM, Marseille, France
| | - Maxime Guye
- APHM, Hôpital de la Timone, CEMEREM, Marseille, France
| | - Fabrice Bartolomei
- Assistance Publique-Hôpitaux de Marseille, Service d'Épileptologie et de Rythmologie Cérébrale, Hôpital La Timone, Marseille, France; Institut de Neurosciences des Systèmes (INS, UMR 1106), Aix Marseille Université, INSERM, Marseille, France
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Hagiwara K. [Insular lobe epilepsy. Part 2: presurgical evaluation & surgical interventions with stereo-electroencephalography]. Rinsho Shinkeigaku 2024; 64:540-549. [PMID: 39069490 DOI: 10.5692/clinicalneurol.cn-001930-2] [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] [Indexed: 07/30/2024]
Abstract
Identification of insular lobe epilepsy (ILE) presents a major clinical challenge in the diagnosis and treatment of drug-resistant focal epilepsies. ILE has diverse clinical presentations due to the multifaceted functions of the insula. Surface EEG findings do not provide straightforward information to predict this deeply-situated origin of seizures; they are even misleading, masquerading as those of other focal epilepsies, such as temporal and frontal ones. Non-invasive imagings may disclose insular abnormalities, but extra-insular abnormalities can coexist or even stand out. Careful reading and a second-look guided by other clinical information are crucial in order not to miss subtle insulo-opercular abnormalities. Furthermore, a possible insular origin of seizures should be considered in MRI-negative frontal/temporal/parietal epilepsies. Therefore, exploration/exclusion of insular-origin seizures is necessary for a great majority of surgical candidates. As for the stereo-electroencephalography, considered as the gold standard method for intra-cranial EEG investigations with suspicion of ILE, planning of electrode positions/trajectories require sufficient knowledge of the functional localization and anatomo-functional connectivity of the insula. Dense sampling within the insula is required in patients with probable ILE, because the seizure-onset zone can be restricted to a single insular gyrus or even a part of it. It is also crucial to explore extra-insular regions on the basis of non-invasive investigation results while considering their anatomo-functional relationships with the insula. From a surgical perspective, differentiating seizures strictly confined to the insula from those extending to the opercula is of particular importance. Pure insular seizures can be treated with less invasive measures, such as radiofrequency thermocoagulation. To conclude, close attention must be paid to the possibility of ILE throughout the diagnostic workup. The precise identification/exclusion of ILE is a prerequisite to provide appropriate and effective surgical treatment in pharmaco-resistant focal epilepsies.
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Moya Quiros V, Adham A, Convers P, Lesca G, Mauguiere F, Soulier H, Arzimanoglou A, Bayat A, Braakman H, Camdessanche JP, Casenave P, Chaton L, Chaix Y, Chochoi M, Depienne C, Desportes V, De Ridder J, Dinkelacker V, Gardella E, Kluger GJ, Jung J, Lemesle Martin M, Mancardi MM, Mueller M, Poulat AL, Platzer K, Roubertie A, Stokman MF, Vulto-van Silfhout AT, Wiegand G, Mazzola L. Electro-Clinical Features and Functional Connectivity Analysis in SYN1-Related Epilepsy. Ann Neurol 2024. [PMID: 39177219 DOI: 10.1002/ana.27063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Revised: 08/07/2024] [Accepted: 08/07/2024] [Indexed: 08/24/2024]
Abstract
OBJECTIVE There is currently scarce data on the electroclinical characteristics of epilepsy associated with synapsin 1 (SYN1) pathogenic variations. We examined clinical and electro-encephalographic (EEG) features in patients with epilepsy and SYN1 variants, with the aim of identifying a distinctive electroclinical pattern. METHODS In this retrospective multicenter study, we collected and reviewed demographic, genetic, and epilepsy data of 19 male patients with SYN1 variants. Specifically, we analyzed interictal EEG data for all patients, and electro-clinical data from 10 epileptic seizures in 5 patients, using prolonged video-EEG monitoring recordings. Inter-ictal EEG functional connectivity parameters and frequency spectrum of the 10 patients over 12 years of age, were computed and compared with those of 56 age- and sex-matched controls. RESULTS The main electroclinical features of epilepsy in patients with SYN1 were (1) EEG background and organization mainly normal; (2) interictal abnormalities are often rare or not visible on EEG; (3) more than 60% of patients had reflex seizures (cutaneous contact with water and defecation being the main triggers) isolated or associated with spontaneous seizures; (4) electro-clinical semiology of seizures was mainly temporal or temporo-insulo/perisylvian with a notable autonomic component; and (5) ictal EEG showed a characteristic rhythmic theta/delta activity predominating in temporo-perisylvian regions at the beginning of most seizures. Comparing patients with SYN1 to healthy subjects, we observed a shift to lower frequency bands in power spectrum of interictal EEG and an increased connectivity in both temporal regions. INTERPRETATION A distinct epilepsy syndrome emerges in patients with SYN1, with a rather characteristic clinical and EEG pattern suggesting predominant temporo-insular involvement. ANN NEUROL 2024.
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Affiliation(s)
| | - Ahmed Adham
- Physical Medicine and Rehabilitation Department, University Hospital of Saint-Étienne, Saint-Étienne, France
- CEA, LETI, CLINATEC, University Grenoble Alpes, Grenoble, France
| | - Philippe Convers
- Neurology Department, University Hospital, Saint-Etienne, France
- NeuroPain Lab, Lyon Neuroscience Research Centre, CRNL-INSERM U 1028/CNRS UMR 5292, University of Lyon, Lyon, France
| | - Gaetan Lesca
- Department of Genetics, Member of the ERN EpiCARE, Hospices Civils de Lyon, Bron, France
- Institute NeuroMyoGène, Laboratoire Physiopathologie et Génétique du Neurone et du Muscle, CNRS UMR 5261-INSERM U1315, Université de Lyon-Université Claude Bernard Lyon 1, Lyon, France
| | - François Mauguiere
- NeuroPain Lab, Lyon Neuroscience Research Centre, CRNL-INSERM U 1028/CNRS UMR 5292, University of Lyon, Lyon, France
- Department of Functional Neurology and Epileptology, Member of the ERN EpiCARE, Hospices Civils de Lyon, Université de Lyon, Lyon, France
| | - Hugo Soulier
- Neurology Department, University Hospital, Saint-Etienne, France
| | - Alexis Arzimanoglou
- Department of Clinical Epileptology, Sleep Disorders and Functional Pediatric Neurology, coordinating member of the ERN EpiCARE, University Hospitals of Lyon (HCL), Lyon, France
- Sección Epilepsia, Sueño y Neurofisiología, Department of Neurology, coordinating member of the ERN EpiCARE, Hospital Sant Joan de Déu Barcelona, Barcelona, Spain
| | - Allan Bayat
- Institute for Regional Health Services, University of Southern Denmark, Odense, Denmark
- Department of Epilepsy Genetics and Personalized Medicine, Danish Epilepsy Center, Member of the ERN EpiCARE, Dianalund, Denmark
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Hilde Braakman
- Department of Paediatric Neurology, Radboud University Medical Centre, Amalia Children's Hospital, Nijmegen, The Netherlands
| | | | | | - Laurence Chaton
- Department of Neurology, Neurophysiology Unit, CHU Lille, Lille, France
| | - Yves Chaix
- Toulouse NeuroImaging Center, University of Toulouse, INSERM, Université Paul Sabatier, Toulouse, France
- Pediatric Neurology Unit, Children's Hospital, Toulouse-Purpan University Hospital, Toulouse, France
| | - Maxime Chochoi
- Department of Neurology, Neurophysiology Unit, CHU Lille, Lille, France
| | - Christel Depienne
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Vincent Desportes
- Hospices Civils de Lyon, Department of Pediatric Neurology, Member of the ERN EpiCARE, Hôpital Femme Mère Enfant, Lyon, France
| | - Jessie De Ridder
- Department of Neurology, Academic Center for Epileptology, Kempenhaeghe, Heeze, The Netherlands
| | - Vera Dinkelacker
- Department of Neurology, University Hospital Strasbourg, Strasbourg, France
| | - Elena Gardella
- Institute for Regional Health Services, University of Southern Denmark, Odense, Denmark
- Department of Epilepsy Genetics and Personalized Medicine, Danish Epilepsy Center, Member of the ERN EpiCARE, Dianalund, Denmark
| | - Gerhard J Kluger
- Schön Klinik Vogtareuth, Center for Pediatric Neurology, Neurorehabilitation and Epileptology, Collaborating Partner of the ERN EpiCARE, PMU, Vogtareuth, Salzburg, Germany
| | - Julien Jung
- Department of Functional Neurology and Epileptology, Member of the ERN EpiCARE, Hospices Civils de Lyon, Université de Lyon, Lyon, France
- Department of Neurology, University Hospital, Lyon Neuroscience Research Center (CRNL), INSERM U1028, CNRS UMR5292, Lyon, France
| | | | - Maria Margherita Mancardi
- Unit of Child Neuropsychiatry, Epilepsy Center, Member of the ERN EpiCARE, Istituto Giannina Gaslini, Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Markus Mueller
- Department of Epileptology, Krankenhaus Mara, Bethel Epilepsy Center, Bielefeld University, Bielefeld, Germany
| | - Anne-Lise Poulat
- Hospices Civils de Lyon, Department of Pediatric Neurology, Member of the ERN EpiCARE, Hôpital Femme Mère Enfant, Lyon, France
| | - Konrad Platzer
- Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany
| | - Agathe Roubertie
- Department of Pediatric Neurology, INSERM, University Hospital Montpellier, Montpellier, France
| | - Marijn F Stokman
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Gert Wiegand
- Division of Pediatric Neurology, Department of Pediatrics, Asklepios Klinik Nord-Heidberg, Hamburg, Germany
- Department of Pediatric and Adolescent Medicine II (Neuropediatrics, Social Pediatrics), University Medical Centre Schleswig-Holstein, Kiel, Germany
| | - Laure Mazzola
- Neurology Department, University Hospital, Saint-Etienne, France
- NeuroPain Lab, Lyon Neuroscience Research Centre, CRNL-INSERM U 1028/CNRS UMR 5292, University of Lyon, Lyon, France
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11
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Cai T, Lin Y, Wang G, Luo J. Predicting radiofrequency thermocoagulation surgical outcomes in refractory focal epilepsy patients using functional coupled neural mass model. Front Neurol 2024; 15:1402004. [PMID: 39246608 PMCID: PMC11377261 DOI: 10.3389/fneur.2024.1402004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Accepted: 08/12/2024] [Indexed: 09/10/2024] Open
Abstract
Objective The success rate of achieving seizure freedom after radiofrequency thermocoagulation surgery for patients with refractory focal epilepsy is about 20-40%. This study aims to enhance the prediction of surgical outcomes based on preoperative decisions through network model simulation, providing a reference for clinicians to validate and optimize surgical plans. Methods Twelve patients with epilepsy who underwent radiofrequency thermocoagulation were retrospectively reviewed in this study. A coupled model based on model subsets of the neural mass model was constructed by calculating partial directed coherence as the coupling matrix from stereoelectroencephalography (SEEG) signals. Multi-channel time-varying model parameters of excitation and inhibitions were identified by fitting the real SEEG signals with the coupled model. Further incorporating these model parameters, the coupled model virtually removed contacts destroyed in radiofrequency thermocoagulation or selected randomly. Subsequently, the coupled model after virtual surgery was simulated. Results The identified excitatory and inhibitory parameters showed significant difference before and after seizure onset (p < 0.05), and the trends of parameter changes aligned with the seizure process. Additionally, excitatory parameters of epileptogenic contacts were higher than that of non-epileptogenic contacts, and opposite findings were noticed for inhibitory parameters. The simulated signals of postoperative models to predict surgical outcomes yielded an area under the curve (AUC) of 83.33% and an accuracy of 91.67%. Conclusion The multi-channel coupled model proposed in this study with physiological characteristics showed a desirable performance for preoperatively predicting patients' prognoses.
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Affiliation(s)
- Tianxin Cai
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, Sun Yat-sen University, Guangzhou, China
| | - Yaoxin Lin
- Department of Functional Neurosurgery, First People's Hospital of Foshan, Foshan, China
| | - Guofu Wang
- Department of Functional Neurosurgery, First People's Hospital of Foshan, Foshan, China
| | - Jie Luo
- School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, Sun Yat-sen University, Guangzhou, China
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12
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Astner-Rohracher A, Ho A, Archer J, Bartolomei F, Brazdil M, Cacic Hribljan M, Castellano J, Dolezalova I, Fabricius ME, Garcés-Sanchez M, Hammam K, Ikeda A, Ikeda K, Kahane P, Kalamangalam G, Kalss G, Khweileh M, Kobayashi K, Kwan P, Laing JA, Leitinger M, Lhatoo S, Makhalova J, McGonigal A, Mindruta I, Mizera MM, Neal A, Oane I, Parikh P, Perucca P, Pizzo F, Rocamora R, Ryvlin P, San Antonio Arce V, Schuele S, Schulze-Bonhage A, Suller Marti A, Urban A, Villanueva V, Vilella Bertran L, Whatley B, Beniczky S, Trinka E, Zimmermann G, Frauscher B. Prognostic value of the 5-SENSE Score to predict focality of the seizure-onset zone as assessed by stereoelectroencephalography: a prospective international multicentre validation study. BMJ Neurol Open 2024; 6:e000765. [PMID: 39175939 PMCID: PMC11340713 DOI: 10.1136/bmjno-2024-000765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Accepted: 07/01/2024] [Indexed: 08/24/2024] Open
Abstract
Introduction Epilepsy surgery is the only curative treatment for patients with drug-resistant focal epilepsy. Stereoelectroencephalography (SEEG) is the gold standard to delineate the seizure-onset zone (SOZ). However, up to 40% of patients are subsequently not operated as no focal non-eloquent SOZ can be identified. The 5-SENSE Score is a 5-point score to predict whether a focal SOZ is likely to be identified by SEEG. This study aims to validate the 5-SENSE Score, improve score performance by incorporating auxiliary diagnostic methods and evaluate its concordance with expert decisions. Methods and analysis Non-interventional, observational, multicentre, prospective study including 200 patients with drug-resistant epilepsy aged ≥15 years undergoing SEEG for identification of a focal SOZ and 200 controls at 22 epilepsy surgery centres worldwide. The primary objective is to assess the diagnostic accuracy and generalisability of the 5-SENSE in predicting focality in SEEG in a prospective cohort. Secondary objectives are to optimise score performance by incorporating auxiliary diagnostic methods and to analyse concordance of the 5-SENSE Score with the expert decisions made in the multidisciplinary team discussion. Ethics and dissemination Prospective multicentre validation of the 5-SENSE score may lead to its implementation into clinical practice to assist clinicians in the difficult decision of whether to proceed with implantation. This study will be conducted in accordance with the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (2014). We plan to publish the study results in a peer-reviewed full-length original article and present its findings at scientific conferences. Trial registration number NCT06138808.
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Affiliation(s)
| | - Alyssa Ho
- Neurology, Duke University, Durham, North Carolina, USA
| | - John Archer
- Bladin-Berkovic Comprehensive Epilepsy Program, The University of Melbourne Medicine at Austin Health, Heidelberg, Victoria, Australia
| | - Fabrice Bartolomei
- Service de Neurophysiologie Clinique, INSERM U751, CHU Timone, Marseille, France
- Neurology, Aix-Marseille Universite, Marseille, France
| | - Milan Brazdil
- Neurology, Masaryk University Faculty of Medicine, Brno, Czech Republic
| | | | - James Castellano
- Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Irena Dolezalova
- Neurology, Masaryk University Faculty of Medicine, Brno, Czech Republic
| | - Martin Ejler Fabricius
- Clinical Neurophysiology, Rigshospitalet, Kobenhavn, Denmark
- Clinical Medicine, University of Copenhagen Faculty of Health and Medical Sciences, Kobenhavn, Denmark
| | | | - Kahina Hammam
- Neurology, Aix-Marseille Universite, Marseille, France
| | - Akio Ikeda
- Neurology, Kyoto University Graduate School of Medicine Faculty of Medicine, Kyoto, Japan
| | - Kristin Ikeda
- Neurology, Dalhousie University Faculty of Medicine, Halifax, Nova Scotia, Canada
| | - Philippe Kahane
- Neurology, Grenoble Alpes University Hospital, Grenoble, France
| | | | - Gudrun Kalss
- Neurology, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Mays Khweileh
- Neurology, Duke University, Durham, North Carolina, USA
| | - Katsuya Kobayashi
- Neurology, Kyoto University Graduate School of Medicine Faculty of Medicine, Kyoto, Japan
| | - Patrick Kwan
- Department of Neuroscience, Central Clinical School, Monash University Faculty of Medicine Nursing and Health Sciences, Melbourne, Victoria, Australia
| | | | - Markus Leitinger
- Neurology, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Samden Lhatoo
- Neurology, University of Texas McGovern Medical School, Houston, Texas, USA
| | | | - Aileen McGonigal
- Neurosciences, Mater Hospital Brisbane, Brisbane, Queensland, Australia
- UQ Faculty of Medicine, Herston, Queensland, Australia
| | - Iona Mindruta
- Neurology, University of Medicine and Pharmacy Carol Davila Bucharest, Bucuresti, Romania
| | | | - Andrew Neal
- Neurology, Alfred Hospital, Melbourne, Victoria, Australia
| | - Irina Oane
- Neurology, University of Medicine and Pharmacy Carol Davila Bucharest, Bucuresti, Romania
| | - Prachi Parikh
- Neurology, Duke University, Durham, North Carolina, USA
| | | | | | | | - Philippe Ryvlin
- Institute for Child and Adolescent with Epilepsy (IDEE), Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Victoria San Antonio Arce
- Epilepsy Centre, University Hospital Freiburg Department of Neurology, Freiburg im Breisgau, Germany
| | - Stephan Schuele
- Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Andreas Schulze-Bonhage
- Epilepsy Centre, University Hospital Freiburg Department of Neurology, Freiburg im Breisgau, Germany
| | - Ana Suller Marti
- Neurology, Western University Schulich School of Medicine & Dentistry, London, Ontario, Canada
| | - Alexandra Urban
- Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | | | | | - Benjamin Whatley
- Neurology, Dalhousie University Faculty of Medicine, Halifax, Nova Scotia, Canada
| | - Sandor Beniczky
- Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | - Eugen Trinka
- Neurology, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Georg Zimmermann
- Biostatistics and Big Medical Data, Paracelsus Medical Private University, Salzburg, Austria
| | - Birgit Frauscher
- Neurology, Duke University, Durham, North Carolina, USA
- Neurology, Montreal Neurological Institute-Hospital, Montreal, Quebec, Canada
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13
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Li Z, Zhao B, Hu W, Zhang C, Wang X, Liu C, Mo J, Guo Z, Yang B, Yao Y, Shao X, Zhang J, Zhang K. Practical measurements distinguishing physiological and pathological stereoelectroencephalography channels based on high-frequency oscillations in the human brain. Epilepsia Open 2024; 9:1287-1299. [PMID: 38808652 PMCID: PMC11296094 DOI: 10.1002/epi4.12950] [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: 08/30/2023] [Revised: 04/07/2024] [Accepted: 04/11/2024] [Indexed: 05/30/2024] Open
Abstract
OBJECTIVE The present study aimed to identify various distinguishing features for use in the accurate classification of stereoelectroencephalography (SEEG) channels based on high-frequency oscillations (HFOs) inside and outside the epileptogenic zone (EZ). METHODS HFOs were detected in patients with focal epilepsy who underwent SEEG. Subsequently, HFOs within the seizure-onset and early spread zones were defined as pathological HFOs, whereas others were defined as physiological. Three features of HFOs were identified at the channel level, namely, morphological repetition, rhythmicity, and phase-amplitude coupling (PAC). A machine-learning (ML) classifier was then built to distinguish two HFO types at the channel level by application of the above-mentioned features, and the contributions were quantified. Further verification of the characteristics and classifier performance was performed in relation to various conscious states, imaging results, EZ location, and surgical outcomes. RESULTS Thirty-five patients were included in this study, from whom 166 104 pathological HFOs in 255 channels and 53 374 physiological HFOs in 282 channels were entered into the analysis pipeline. The results revealed that the morphological repetitions of pathological HFOs were markedly higher than those of the physiological HFOs; this was also observed for rhythmicity and PAC. The classifier exhibited high accuracy in differentiating between the two forms of HFOs, as indicated by an area under the curve (AUC) of 0.89. Both PAC and rhythmicity contributed significantly to this distinction. The subgroup analyses supported these findings. SIGNIFICANCE The suggested HFO features can accurately distinguish between pathological and physiological channels substantially improving its usefulness in clinical localization. PLAIN LANGUAGE SUMMARY In this study, we computed three quantitative features associated with HFOs in each SEEG channel and then constructed a machine learning-based classifier for the classification of pathological and physiological channels. The classifier performed well in distinguishing the two channel types under different levels of consciousness as well as in terms of imaging results, EZ location, and patient surgical outcomes.
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Affiliation(s)
- Zilin Li
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical InstituteCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of NeurostimulationBeijingChina
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Chang Liu
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Zhihao Guo
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Bowen Yang
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Yuan Yao
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Xiaoqiu Shao
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical InstituteCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of NeurostimulationBeijingChina
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical InstituteCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of NeurostimulationBeijingChina
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14
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Wong GM, McCray A, Hom K, Teti S, Cohen NT, Gaillard WD, Oluigbo CO. Outcomes of stereoelectroencephalography following failed epilepsy surgery in children. Childs Nerv Syst 2024; 40:2471-2482. [PMID: 38652142 DOI: 10.1007/s00381-024-06420-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 04/17/2024] [Indexed: 04/25/2024]
Abstract
INTRODUCTION Stereoelectroencephalography (SEEG) is valuable for delineating the seizure onset zone (SOZ) in pharmacoresistant epilepsy when non-invasive presurgical techniques are inconclusive. Secondary epilepsy surgery after initial failure is challenging and there is limited research on SEEG following failed epilepsy surgery in children. OBJECTIVE The objective of this manuscript is to present the outcomes of children who underwent SEEG after failed epilepsy surgery. METHODS In this single-institution retrospective study, demographics, previous surgery data, SEEG characteristics, management, and follow-up were analyzed for pediatric patients who underwent SEEG after unsuccessful epilepsy surgery between August 2016 and February 2023. RESULTS Fifty three patients underwent SEEG investigation during this period. Of this, 13 patients were identified who had unsuccessful initial epilepsy surgery (24%). Of these 13 patients, six patients (46%) experienced unsuccessful resective epilepsy surgery that targeted the temporal lobe, six patients (46%) underwent surgery involving the frontal lobe, and one patient (8%) had laser interstitial thermal therapy (LITT) of the right insula. SEEG in two thirds of patients (4/6) with initial failed temporal resections revealed expanded SOZ to include the insula. All 13 patients (100%) had a subsequent surgery after SEEG which was either LITT (54%) or surgical resection (46%). After the subsequent surgery, a favorable outcome (Engel class I/II) was achieved by eight patients (62%), while five patients experienced an unfavorable outcome (Engel class III/IV, 38%). Of the six patients with secondary surgical resection, four patients (67%) had favorable outcomes, while of the seven patients with LITT, two patients (29%) had favorable outcomes (Engel I/II). Average follow-up after the subsequent surgery was 37 months ±23 months. CONCLUSION SEEG following initial failed resective epilepsy surgery may help guide next steps at identifying residual epileptogenic cortex and is associated with favorable seizure control outcomes.
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Affiliation(s)
- Georgia M Wong
- Department of Neurological Surgery, Georgetown University School of Medicine, Washington, DC, USA.
| | - Ashley McCray
- Department of Neurosurgery, Children's National Hospital, Washington, DC, 20012, USA
| | - Kara Hom
- Department of Neurology, George Washington University School of Medicine, Washington, DC, USA
| | - Saige Teti
- Department of Neurosurgery, Children's National Hospital, Washington, DC, 20012, USA
| | - Nathan T Cohen
- Department of Neurology, George Washington University School of Medicine, Washington, DC, USA
- Department of Neurology, Children's National Hospital, Washington, DC, USA
| | - William D Gaillard
- Department of Neurology, George Washington University School of Medicine, Washington, DC, USA
- Department of Neurology, Children's National Hospital, Washington, DC, USA
| | - Chima O Oluigbo
- Department of Neurosurgery, Children's National Hospital, Washington, DC, 20012, USA.
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15
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Doss DJ, Johnson GW, Makhoul GS, Rashingkar RV, Shless JS, Bibro CE, Paulo DL, Gummadavelli A, Ball TJ, Reddy SB, Naftel RP, Haas KF, Dawant BM, Constantinidis C, Williams Roberson S, Bick SK, Morgan VL, Englot DJ. Network signatures define consciousness state during focal seizures. Epilepsia 2024. [PMID: 39056406 DOI: 10.1111/epi.18074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 07/12/2024] [Accepted: 07/17/2024] [Indexed: 07/28/2024]
Abstract
OBJECTIVE Epilepsy is a common neurological disorder affecting 1% of the global population. Loss of consciousness in focal impaired awareness seizures (FIASs) and focal-to-bilateral tonic-clonic seizures (FBTCSs) can be devastating, but the mechanisms are not well understood. Although ictal activity and interictal connectivity changes have been noted, the network states of focal aware seizures (FASs), FIASs, and FBTCSs have not been thoroughly evaluated with network measures ictally. METHODS We obtained electrographic data from 74 patients with stereoelectroencephalography (SEEG). Sliding window band power, functional connectivity, and segregation were computed on preictal, ictal, and postictal data. Five-minute epochs of wake, rapid eye movement sleep, and deep sleep were also extracted. Connectivity of subcortical arousal structures was analyzed in a cohort of patients with both SEEG and functional magnetic resonance imaging (fMRI). Given that custom neuromodulation of seizures is predicated on detection of seizure type, a convolutional neural network was used to classify seizure types. RESULTS We found that in the frontoparietal association cortex, an area associated with consciousness, both consciousness-impairing seizures (FIASs and FBTCSs) and deep sleep had increases in slow wave delta (1-4 Hz) band power. However, when network measures were employed, we found that only FIASs and deep sleep exhibited an increase in delta segregation and a decrease in gamma segregation. Furthermore, we found that only patients with FIASs had reduced subcortical-to-neocortical functional connectivity with fMRI versus controls. Finally, our deep learning network demonstrated an area under the curve of .75 for detecting consciousness-impairing seizures. SIGNIFICANCE This study provides novel insights into ictal network measures in FASs, FIASs, and FBTCSs. Importantly, although both FIASs and FBTCSs result in loss of consciousness, our results suggest that ictal network changes in FIASs uniquely resemble those that occur during deep sleep. Our results may inform novel neuromodulation strategies for preservation of consciousness in epilepsy.
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Affiliation(s)
- Derek J Doss
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
| | - Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
| | - Ghassan S Makhoul
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
| | - Rohan V Rashingkar
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jared S Shless
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Camden E Bibro
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Danika L Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Abhijeet Gummadavelli
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Tyler J Ball
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Shilpa B Reddy
- Department of Pediatrics, Vanderbilt Children's Hospital, Nashville, Tennessee, USA
| | - Robert P Naftel
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kevin F Haas
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Benoit M Dawant
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Christos Constantinidis
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee, USA
- Department of Ophthalmology and Visual Sciences, Vanderbilt University, Nashville, Tennessee, USA
| | - Shawniqua Williams Roberson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Sarah K Bick
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee, USA
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16
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Cui CK, Wong WK, Wong CH, Gill D, Fong MWK. Case Report: Focal, generalized, or both: does generalized network involvement preclude successful epilepsy surgery? FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1425329. [PMID: 39055857 PMCID: PMC11269090 DOI: 10.3389/fnetp.2024.1425329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 06/20/2024] [Indexed: 07/28/2024]
Abstract
We present two cases with focal seizures where scalp electroencephalography (EEG) had prominent features of a developmental and epileptic encephalopathy (DEE): Case 1: a 17-year-old male with complex motor seizures whose EEG demonstrated a slow spike-and-wave pattern and generalized paroxysmal fast activity (GPFA). Case 2: a 12-year-old male with startle-induced asymmetric tonic seizures whose EEG also had a slow spike-and-wave pattern. Both patients had intracranial EEG assessment, and focal cortical resections resulted in long-term seizure freedom and resolution of generalized findings. These cases exemplify patients with focal epilepsy with networks that share similarities to generalized epilepsies, and importantly, these features did not preclude curative epilepsy surgery.
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Affiliation(s)
- Cathy K. Cui
- Westmead Comprehensive Epilepsy Centre, The University of Sydney, Sydney, NSW, Australia
| | - Wui-Kwan Wong
- Westmead Comprehensive Epilepsy Centre, The University of Sydney, Sydney, NSW, Australia
- T. Y. Nelson Department of Neurology and Neurosurgery, The Children’s Hospital at Westmead, Sydney, NSW, Australia
| | - Chong H. Wong
- Westmead Comprehensive Epilepsy Centre, The University of Sydney, Sydney, NSW, Australia
- T. Y. Nelson Department of Neurology and Neurosurgery, The Children’s Hospital at Westmead, Sydney, NSW, Australia
| | - Deepak Gill
- Westmead Comprehensive Epilepsy Centre, The University of Sydney, Sydney, NSW, Australia
- T. Y. Nelson Department of Neurology and Neurosurgery, The Children’s Hospital at Westmead, Sydney, NSW, Australia
| | - Michael W. K. Fong
- Westmead Comprehensive Epilepsy Centre, The University of Sydney, Sydney, NSW, Australia
- T. Y. Nelson Department of Neurology and Neurosurgery, The Children’s Hospital at Westmead, Sydney, NSW, Australia
- Department of Neurology, Comprehensive Epilepsy Center, Yale University School of Medicine, New Haven, CT, United States
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17
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Padmasola GP, Friscourt F, Rigoni I, Vulliémoz S, Schaller K, Michel CM, Sheybani L, Quairiaux C. Involvement of the contralateral hippocampus in ictal-like but not interictal epileptic activities in the kainate mouse model of temporal lobe epilepsy. Epilepsia 2024; 65:2082-2098. [PMID: 38758110 DOI: 10.1111/epi.17970] [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: 09/04/2023] [Revised: 03/19/2024] [Accepted: 03/19/2024] [Indexed: 05/18/2024]
Abstract
OBJECTIVE Animal and human studies have shown that the seizure-generating region is vastly dependent on distant neuronal hubs that can decrease duration and propagation of ongoing seizures. However, we still lack a comprehensive understanding of the impact of distant brain areas on specific interictal and ictal epileptic activities (e.g., isolated spikes, spike trains, seizures). Such knowledge is critically needed, because all kinds of epileptic activities are not equivalent in terms of clinical expression and impact on the progression of the disease. METHODS We used surface high-density electroencephalography and multisite intracortical recordings, combined with pharmacological silencing of specific brain regions in the well-known kainate mouse model of temporal lobe epilepsy. We tested the impact of selective regional silencing on the generation of epileptic activities within a continuum ranging from very transient to more sustained and long-lasting discharges reminiscent of seizures. RESULTS Silencing the contralateral hippocampus completely suppresses sustained ictal activities in the focus, as efficiently as silencing the focus itself, but whereas focus silencing abolishes all focus activities, contralateral silencing fails to control transient spikes. In parallel, we observed that sustained focus epileptiform discharges in the focus are preceded by contralateral firing and more strongly phase-locked to bihippocampal delta/theta oscillations than transient spiking activities, reinforcing the presumed dominant role of the contralateral hippocampus in promoting long-lasting, but not transient, epileptic activities. SIGNIFICANCE Altogether, our work provides suggestive evidence that the contralateral hippocampus is necessary for the interictal to ictal state transition and proposes that crosstalk between contralateral neuronal activity and ipsilateral delta/theta oscillation could be a candidate mechanism underlying the progression from short- to long-lasting epileptic activities.
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Affiliation(s)
- Guru Prasad Padmasola
- Functional Brain Mapping Lab, Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland
| | - Fabien Friscourt
- Functional Brain Mapping Lab, Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland
- Neurosurgery Clinic, Department of Clinical Neuroscience, University Hospital Geneva, Geneva, Switzerland
| | - Isotta Rigoni
- EEG and Epilepsy Unit, Department of Neuroscience, University Hospital and Faculty of Medicine of Geneva, University of Geneva, Geneva, Switzerland
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, Department of Neuroscience, University Hospital and Faculty of Medicine of Geneva, University of Geneva, Geneva, Switzerland
| | - Karl Schaller
- Neurosurgery Clinic, Department of Clinical Neuroscience, University Hospital Geneva, Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Lab, Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland
| | - Laurent Sheybani
- Neurology Clinic, Department of Clinical Neuroscience, University Hospital Geneva, Geneva, Switzerland
- Department of Clinical and Experimental Epilepsy, Queen's Square Institute of Neurology, London, UK
| | - Charles Quairiaux
- Functional Brain Mapping Lab, Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland
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18
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Pati S, Agashe S, Kheder A, Riley K, Gavvala J, McGovern R, Suresh S, Chaitanya G, Thompson S. Stereoelectroencephalography of the Deep Brain: Basal Ganglia and Thalami. J Clin Neurophysiol 2024; 41:423-429. [PMID: 38935656 DOI: 10.1097/wnp.0000000000001097] [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] [Indexed: 06/29/2024] Open
Abstract
SUMMARY Stereoelectroencephalography (SEEG) has emerged as a transformative tool in epilepsy surgery, shedding light on the complex network dynamics involved in focal epilepsy. This review explores the role of SEEG in elucidating the role of deep brain structures, namely the basal ganglia and thalamus, in epilepsy. SEEG advances understanding of their contribution to seizure generation, propagation, and control by permitting precise and minimally invasive sampling of these brain regions. The basal ganglia, comprising the subthalamic nucleus, globus pallidus, substantia nigra, and striatum, have gained recognition for their involvement in both focal and generalized epilepsy. Electrophysiological recordings reveal hyperexcitability and increased synchrony within these structures, reinforcing their role as critical nodes within the epileptic network. Furthermore, low-frequency and high-frequency stimulation of the basal ganglia have demonstrated potential in modulating epileptogenic networks. Concurrently, the thalamus, a key relay center, has garnered prominence in epilepsy research. Disrupted thalamocortical connectivity in focal epilepsy underscores its significance in seizure maintenance. The thalamic subnuclei, including the anterior nucleus, centromedian, and medial pulvinar, present promising neuromodulatory targets, suggesting pathways for personalized epilepsy therapies. The prospect of multithalamic SEEG and thalamic SEEG stimulation trials has the potential to revolutionize epilepsy management, offering tailored solutions for challenging cases. SEEG's ability to unveil the dynamics of deep brain structures in epilepsy promises enhanced and personalized epilepsy care in our new era of precision medicine. Until deep brain SEEG is accepted as a standard of care, a rigorous informed consent process remains paramount for patients for whom such an exploration is proposed.
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Affiliation(s)
- Sandipan Pati
- Texas Comprehensive Epilepsy Program, Department of Neurology, The University of Texas Health Science Center at Houston, Texas, U.S.A
| | - Shruti Agashe
- Department of Neurology, Duke Comprehensive Epilepsy Center, Duke University, Durham, North Carolina, U.S.A
| | - Ammar Kheder
- Department of Neurology, Children's Healthcare of Atlanta, Emory University, Atlanta, Georgia, U.S.A
| | - Kristen Riley
- Department of Neurosurgery, Heersink School of Medicine, University of Alabama at Birmingham, Alabama, U.S.A
| | - Jay Gavvala
- Texas Comprehensive Epilepsy Program, Department of Neurology, The University of Texas Health Science Center at Houston, Texas, U.S.A
| | - Robert McGovern
- Department of Neurosurgery, University of Minnesota, Minnesota, U.S.A.; and
| | - Surya Suresh
- Texas Comprehensive Epilepsy Program, Department of Neurology, The University of Texas Health Science Center at Houston, Texas, U.S.A
| | - Ganne Chaitanya
- Texas Comprehensive Epilepsy Program, Department of Neurology, The University of Texas Health Science Center at Houston, Texas, U.S.A
| | - Stephen Thompson
- Neurology Division of the Department of Medicine, Hamilton Health Sciences and McMaster University, Canada
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19
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Jacobs J, Klotz KA, Pizzo F, Federico P. Beyond Stereo-EEG: Is It Worth Combining Stereo-EEG With Other Diagnostic Methods? J Clin Neurophysiol 2024; 41:444-449. [PMID: 38935658 DOI: 10.1097/wnp.0000000000001086] [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: 06/29/2024] Open
Abstract
SUMMARY Stereo-EEG is a widely used method to improve the diagnostic precision of presurgical workup in patients with refractory epilepsy. Its ability to detect epileptic activity and identify epileptic networks largely depends on the chosen implantation strategy. Even in an ideal situation, electrodes record activity generated in <10% of the brain and contacts only record from brain tissue in their immediate proximity. In this article, the authors discuss how recording stereo-EEG simultaneously with other diagnostic methods can improve its diagnostic value in clinical and research settings. It can help overcome the limited spatial coverage of intracranial recording and better understand the sources of epileptic activity. Simultaneous scalp EEG is the most widely available method, often used to understand large epileptic networks, seizure propagation, and EEG activity occurring on the contralateral hemisphere. Simultaneous magnetoencephalography allows for more precise source localization and identification of deep sources outside the stereo-EEG coverage. Finally, simultaneous functional MRI can highlight metabolic changes following epileptic activity and help understand the widespread network changes associated with interictal activity. This overview highlights advantages and methodological challenges for all these methods. Clinical use and research applications are presented for each approach.
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Affiliation(s)
- Julia Jacobs
- University of Calgary, Calgary, Alberta, Canada
- University Medical Center Freiburg, University of Freiburg, Freiburg, Germany; and
| | | | - Francesca Pizzo
- Epileptology Department, INSERM, Aix Marseille Universite; Marseille, France
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20
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Penas DR, Hashemi M, Jirsa VK, Banga JR. Parameter estimation in a whole-brain network model of epilepsy: Comparison of parallel global optimization solvers. PLoS Comput Biol 2024; 20:e1011642. [PMID: 38990984 PMCID: PMC11265693 DOI: 10.1371/journal.pcbi.1011642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 07/23/2024] [Accepted: 06/18/2024] [Indexed: 07/13/2024] Open
Abstract
The Virtual Epileptic Patient (VEP) refers to a computer-based representation of a patient with epilepsy that combines personalized anatomical data with dynamical models of abnormal brain activities. It is capable of generating spatio-temporal seizure patterns that resemble those recorded with invasive methods such as stereoelectro EEG data, allowing for the evaluation of clinical hypotheses before planning surgery. This study highlights the effectiveness of calibrating VEP models using a global optimization approach. The approach utilizes SaCeSS, a cooperative metaheuristic algorithm capable of parallel computation, to yield high-quality solutions without requiring excessive computational time. Through extensive benchmarking on synthetic data, our proposal successfully solved a set of different configurations of VEP models, demonstrating better scalability and superior performance against other parallel solvers. These results were further enhanced using a Bayesian optimization framework for hyperparameter tuning, with significant gains in terms of both accuracy and computational cost. Additionally, we added a scalable uncertainty quantification phase after model calibration, and used it to assess the variability in estimated parameters across different problems. Overall, this study has the potential to improve the estimation of pathological brain areas in drug-resistant epilepsy, thereby to inform the clinical decision-making process.
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Affiliation(s)
- David R. Penas
- Computational Biology Lab, MBG-CSIC (Spanish National Research Council), Pontevedra, Spain
| | - Meysam Hashemi
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Viktor K. Jirsa
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Julio R. Banga
- Computational Biology Lab, MBG-CSIC (Spanish National Research Council), Pontevedra, Spain
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21
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Millán AP, van Straaten ECW, Stam CJ, Nissen IA, Idema S, Van Mieghem P, Hillebrand A. Individualized epidemic spreading models predict epilepsy surgery outcomes: A pseudo-prospective study. Netw Neurosci 2024; 8:437-465. [PMID: 38952815 PMCID: PMC11142635 DOI: 10.1162/netn_a_00361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 01/18/2024] [Indexed: 07/03/2024] Open
Abstract
Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients, but up to 50% of patients continue to have seizures one year after the resection. In order to aid presurgical planning and predict postsurgical outcome on a patient-by-patient basis, we developed a framework of individualized computational models that combines epidemic spreading with patient-specific connectivity and epileptogeneity maps: the Epidemic Spreading Seizure and Epilepsy Surgery framework (ESSES). ESSES parameters were fitted in a retrospective study (N = 15) to reproduce invasive electroencephalography (iEEG)-recorded seizures. ESSES reproduced the iEEG-recorded seizures, and significantly better so for patients with good (seizure-free, SF) than bad (nonseizure-free, NSF) outcome. We illustrate here the clinical applicability of ESSES with a pseudo-prospective study (N = 34) with a blind setting (to the resection strategy and surgical outcome) that emulated presurgical conditions. By setting the model parameters in the retrospective study, ESSES could be applied also to patients without iEEG data. ESSES could predict the chances of good outcome after any resection by finding patient-specific model-based optimal resection strategies, which we found to be smaller for SF than NSF patients, suggesting an intrinsic difference in the network organization or presurgical evaluation results of NSF patients. The actual surgical plan overlapped more with the model-based optimal resection, and had a larger effect in decreasing modeled seizure propagation, for SF patients than for NSF patients. Overall, ESSES could correctly predict 75% of NSF and 80.8% of SF cases pseudo-prospectively. Our results show that individualised computational models may inform surgical planning by suggesting alternative resections and providing information on the likelihood of a good outcome after a proposed resection. This is the first time that such a model is validated with a fully independent cohort and without the need for iEEG recordings.
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Affiliation(s)
- Ana P. Millán
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and MEG Center, Amsterdam, The Netherlands
- Institute “Carlos I” for Theoretical and Computational Physics, and Electromagnetism and Matter Physics Department, University of Granada, Granada, Spain
| | - Elisabeth C. W. van Straaten
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and MEG Center, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Cornelis J. Stam
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and MEG Center, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Ida A. Nissen
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and MEG Center, Amsterdam, The Netherlands
| | - Sander Idema
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurosurgery, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Cancer Biology and Immonology, Amsterdam, The Netherlands
| | - Piet Van Mieghem
- Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
| | - Arjan Hillebrand
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology and MEG Center, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
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22
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Bourdillon P, Ren L, Halgren M, Paulk AC, Salami P, Ulbert I, Fabó D, King JR, Sjoberg KM, Eskandar EN, Madsen JR, Halgren E, Cash SS. Differential cortical layer engagement during seizure initiation and spread in humans. Nat Commun 2024; 15:5153. [PMID: 38886376 PMCID: PMC11183216 DOI: 10.1038/s41467-024-48746-8] [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: 11/22/2022] [Accepted: 05/10/2024] [Indexed: 06/20/2024] Open
Abstract
Despite decades of research, we still do not understand how spontaneous human seizures start and spread - especially at the level of neuronal microcircuits. In this study, we used laminar arrays of micro-electrodes to simultaneously record the local field potentials and multi-unit neural activities across the six layers of the neocortex during focal seizures in humans. We found that, within the ictal onset zone, the discharges generated during a seizure consisted of current sinks and sources only within the infra-granular and granular layers. Outside of the seizure onset zone, ictal discharges reflected current flow in the supra-granular layers. Interestingly, these patterns of current flow evolved during the course of the seizure - especially outside the seizure onset zone where superficial sinks and sources extended into the deeper layers. Based on these observations, a framework describing cortical-cortical dynamics of seizures is proposed with implications for seizure localization, surgical targeting, and neuromodulation techniques to block the generation and propagation of seizures.
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Affiliation(s)
- Pierre Bourdillon
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Department of Neurosurgery, Hospital Foundation Adolphe de Rothschild, Paris, France.
- Integrative Neuroscience and Cognition Center, Paris Cité University, Paris, France.
| | - Liankun Ren
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Mila Halgren
- Brain and Cognitive Sciences Department and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Angelique C Paulk
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Pariya Salami
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - István Ulbert
- HUN-REN, Research Center for Natural Sciences, Institute of Cognitive Neuroscience and Psychology, Budapest, Hungary
- Faculty of Information Technology and Bionics, Péter Pázmány Catholic University, Budapest, Hungary
- Department of Neurosurgery and Neurointervention, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Dániel Fabó
- Department of Neurosurgery and Neurointervention, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Jean-Rémi King
- Laboratoire des Systèmes Perceptifs, Département d'études cognitives, École normale supérieure, PSL University, CNRS, Paris, France
| | - Kane M Sjoberg
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Harvard College, Cambridge, MA, 02138, USA
| | - Emad N Eskandar
- Department of Neurological Surgery, Albert Einstein College of Medicine - Montefiore Medical Center, Bronx, NY, USA
| | - Joseph R Madsen
- Department of Neurosurgery, Boston Children Hospital, Harvard Medical School, Boston, MA, USA
| | - Eric Halgren
- Departments of Radiology and, Neurosciences, University of California, San Diego, San Diego, CA, USA
| | - Sydney S Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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23
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Ravat P, Jain N, Thakkar M, Kalika M, Ravat S. Ictal kissing: Review of literature and report of 5 cases. Epileptic Disord 2024; 26:350-356. [PMID: 38558114 DOI: 10.1002/epd2.20208] [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: 02/22/2023] [Revised: 02/08/2024] [Accepted: 02/08/2024] [Indexed: 04/04/2024]
Abstract
Ictal kissing (IK) is a rare type of automatism observed during epileptic seizures. Despite its uncommon occurrence, understanding the underlying mechanisms, the role of emotions, and the level of consciousness during seizures with IK is essential in providing a comprehensive understanding of epilepsy. We describe five cases (.13%) of IK after performing a retrospective analysis of 3794 long-term, ictal video-EEGs from an epilepsy monitoring unit in Mumbai, India. Our patients with drug-resistant epilepsy showed IK had a wide epileptogenic zone. We discuss the current hypotheses on the mechanisms behind IK, the involvement of temporal lobe structures, and the implications of awareness during seizures. The review concludes by suggesting future directions for research to elucidate the complex phenomenon of IK further.
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Affiliation(s)
- Parthvi Ravat
- Department of Neurology, Seth GS Medical College and KEM Hospital, Acharya Donde Marg, Mumbai, 400012, Maharashtra, India
| | - Neeraj Jain
- Department of Neurology, Seth GS Medical College and KEM Hospital, Acharya Donde Marg, Mumbai, 400012, Maharashtra, India
| | - Mayur Thakkar
- Department of Neurology, Seth GS Medical College and KEM Hospital, Acharya Donde Marg, Mumbai, 400012, Maharashtra, India
| | - Mayuri Kalika
- Department of Neurology, Seth GS Medical College and KEM Hospital, Acharya Donde Marg, Mumbai, 400012, Maharashtra, India
| | - Sangeeta Ravat
- Department of Neurology, Seth GS Medical College and KEM Hospital, Acharya Donde Marg, Mumbai, 400012, Maharashtra, India
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24
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Di Giacomo R, Burini A, Chiarello D, Pelliccia V, Deleo F, Garbelli R, de Curtis M, Tassi L, Gnatkovsky V. Ictal fast activity chirps as markers of the epileptogenic zone. Epilepsia 2024; 65:e97-e103. [PMID: 38686942 DOI: 10.1111/epi.17995] [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: 11/13/2023] [Revised: 04/11/2024] [Accepted: 04/11/2024] [Indexed: 05/02/2024]
Abstract
The identification of the epileptogenic zone (EZ) boundaries is crucial for effective focal epilepsy surgery. We verify the value of a neurophysiological biomarker of focal ictogenesis, characterized by a low-voltage fast-activity ictal pattern (chirp) recorded with intracerebral electrodes during invasive presurgical monitoring (stereoelectroencephalography [SEEG]). The frequency content of SEEG signals was retrospectively analyzed with semiautomatic software in 176 consecutive patients with focal epilepsies that either were cryptogenic or presented with discordant anatomoelectroclinical findings. Fast activity seizure patterns with the spectrographic features of chirps were confirmed by computer-assisted analysis in 95.4% of patients who presented with heterogeneous etiologies and diverse lobar location of the EZ. Statistical analysis demonstrated (1) correlation between seizure outcome and concordance of sublobar regions included in the EZ defined by visual analysis and chirp-generating regions, (2) high concordance in contact-by contact analysis of 68 patients with Engel class Ia outcome, and (3) that discordance between chirp location and the visually outlined EZ correlated with worse seizure outcome. Seizure outcome analysis confirms the fast activity chirp pattern is a reproducible biomarker of the EZ in a heterogeneous group of patients undergoing SEEG.
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Affiliation(s)
- Roberta Di Giacomo
- Epilepsy Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Alessandra Burini
- Epilepsy Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
- Clinical Neurology, Department of Medicine (DAME), University of Udine, Udine, Italy
| | - Daniela Chiarello
- "Claudio Munari" Epilepsy Surgery Center, Niguarda Hospital, Milan, Italy
| | - Veronica Pelliccia
- "Claudio Munari" Epilepsy Surgery Center, Niguarda Hospital, Milan, Italy
| | - Francesco Deleo
- Epilepsy Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Rita Garbelli
- Epilepsy Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Marco de Curtis
- Epilepsy Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Laura Tassi
- "Claudio Munari" Epilepsy Surgery Center, Niguarda Hospital, Milan, Italy
| | - Vadym Gnatkovsky
- Epilepsy Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
- Department of Epileptology, Universitätsklinikum Bonn, Bonn, Germany
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25
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Traub-Weidinger T, Arbizu J, Barthel H, Boellaard R, Borgwardt L, Brendel M, Cecchin D, Chassoux F, Fraioli F, Garibotto V, Guedj E, Hammers A, Law I, Morbelli S, Tolboom N, Van Weehaeghe D, Verger A, Van Paesschen W, von Oertzen TJ, Zucchetta P, Semah F. EANM practice guidelines for an appropriate use of PET and SPECT for patients with epilepsy. Eur J Nucl Med Mol Imaging 2024; 51:1891-1908. [PMID: 38393374 PMCID: PMC11139752 DOI: 10.1007/s00259-024-06656-3] [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: 11/01/2023] [Accepted: 02/13/2024] [Indexed: 02/25/2024]
Abstract
Epilepsy is one of the most frequent neurological conditions with an estimated prevalence of more than 50 million people worldwide and an annual incidence of two million. Although pharmacotherapy with anti-seizure medication (ASM) is the treatment of choice, ~30% of patients with epilepsy do not respond to ASM and become drug resistant. Focal epilepsy is the most frequent form of epilepsy. In patients with drug-resistant focal epilepsy, epilepsy surgery is a treatment option depending on the localisation of the seizure focus for seizure relief or seizure freedom with consecutive improvement in quality of life. Beside examinations such as scalp video/electroencephalography (EEG) telemetry, structural, and functional magnetic resonance imaging (MRI), which are primary standard tools for the diagnostic work-up and therapy management of epilepsy patients, molecular neuroimaging using different radiopharmaceuticals with single-photon emission computed tomography (SPECT) and positron emission tomography (PET) influences and impacts on therapy decisions. To date, there are no literature-based praxis recommendations for the use of Nuclear Medicine (NM) imaging procedures in epilepsy. The aims of these guidelines are to assist in understanding the role and challenges of radiotracer imaging for epilepsy; to provide practical information for performing different molecular imaging procedures for epilepsy; and to provide an algorithm for selecting the most appropriate imaging procedures in specific clinical situations based on current literature. These guidelines are written and authorized by the European Association of Nuclear Medicine (EANM) to promote optimal epilepsy imaging, especially in the presurgical setting in children, adolescents, and adults with focal epilepsy. They will assist NM healthcare professionals and also specialists such as Neurologists, Neurophysiologists, Neurosurgeons, Psychiatrists, Psychologists, and others involved in epilepsy management in the detection and interpretation of epileptic seizure onset zone (SOZ) for further treatment decision. The information provided should be applied according to local laws and regulations as well as the availability of various radiopharmaceuticals and imaging modalities.
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Affiliation(s)
- Tatjana Traub-Weidinger
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Javier Arbizu
- Department of Nuclear Medicine, University of Navarra Clinic, Pamplona, Spain
| | - Henryk Barthel
- Department of Nuclear Medicine, Leipzig University Medical Centre, Leipzig, Germany
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Lise Borgwardt
- Department of Clinical Physiology and Nuclear Medicine, University of Copenhagen, Blegdamsvej 9, DK-2100, RigshospitaletCopenhagen, Denmark
| | - Matthias Brendel
- Department of Nuclear Medicine, Ludwig Maximilian-University of Munich, Munich, Germany
- DZNE-German Center for Neurodegenerative Diseases, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Diego Cecchin
- Nuclear Medicine Unit, Department of Medicine-DIMED, University-Hospital of Padova, Padova, Italy
| | - Francine Chassoux
- Université Paris-Saclay, CEA, CNRS, Inserm, BioMaps, 91401, Orsay, France
| | - Francesco Fraioli
- Institute of Nuclear Medicine, University College London (UCL), London, UK
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
- NIMTLab, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Center for Biomedical Imaging (CIBM), Geneva, Switzerland
| | - Eric Guedj
- APHM, CNRS, Centrale Marseille, Institut Fresnel, Timone Hospital, CERIMED, Nuclear Medicine Department, Aix Marseille Univ, Marseille, France
| | - Alexander Hammers
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London & Guy's and St Thomas' PET Centre, King's College London, London, UK
| | - Ian Law
- Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet, University of Copenhagen, Blegdamsvej 9, DK-2100, Copenhagen, Denmark
| | - Silvia Morbelli
- Nuclear Medicine Unit, IRCCS Ospedale Policlinico San Martino, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Nelleke Tolboom
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | | | - Antoine Verger
- Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU Nancy, Université de Lorraine, IADI, INSERM U1254, Nancy, France
| | - Wim Van Paesschen
- Laboratory for Epilepsy Research, KU Leuven and Department of Neurology, University Hospitals, Leuven, Belgium
| | - Tim J von Oertzen
- Depts of Neurology 1&2, Kepler University Hospital, Johannes Kepler University, Linz, Austria
| | - Pietro Zucchetta
- Nuclear Medicine Unit, Department of Medicine-DIMED, University-Hospital of Padova, Padova, Italy
| | - Franck Semah
- Nuclear Medicine Department, University Hospital, Inserm, CHU Lille, U1172-LilNCog-Lille, F-59000, Lille, France.
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Mardones MD, Rostam KD, Nickerson MC, Gupta K. Canonical Wnt activator Chir99021 prevents epileptogenesis in the intrahippocampal kainate mouse model of temporal lobe epilepsy. Exp Neurol 2024; 376:114767. [PMID: 38522659 PMCID: PMC11058011 DOI: 10.1016/j.expneurol.2024.114767] [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: 12/20/2023] [Revised: 02/29/2024] [Accepted: 03/21/2024] [Indexed: 03/26/2024]
Abstract
The Wnt signaling pathway mediates the development of dentate granule cell neurons in the hippocampus. These neurons are central to the development of temporal lobe epilepsy and undergo structural and physiological remodeling during epileptogenesis, which results in the formation of epileptic circuits. The pathways responsible for granule cell remodeling during epileptogenesis have yet to be well defined, and represent therapeutic targets for the prevention of epilepsy. The current study explores Wnt signaling during epileptogenesis and for the first time describes the effect of Wnt activation using Wnt activator Chir99021 as a novel anti-epileptogenic therapeutic approach. Focal mesial temporal lobe epilepsy was induced by intrahippocampal kainate (IHK) injection in wild-type and POMC-eGFP transgenic mice. Wnt activator Chir99021 was administered daily, beginning 3 h after seizure induction, and continued up to 21-days. Immature granule cell morphology was quantified in the ipsilateral epileptogenic zone and the contralateral peri-ictal zone 14 days after IHK, targeting the end of the latent period. Bilateral hippocampal electrocorticographic recordings were performed for 28-days, 7-days beyond treatment cessation. Hippocampal behavioral tests were performed after completion of Chir99021 treatment. Consistent with previous studies, IHK resulted in the development of epilepsy after a 14 day latent period in this well-described mouse model. Activation of the canonical Wnt pathway with Chir99021 significantly reduced bilateral hippocampal seizure number and duration. Critically, this effect was retained after treatment cessation, suggesting a durable antiepileptogenic change in epileptic circuitry. Morphological analyses demonstrated that Wnt activation prevented pathological remodeling of the primary dendrite in both the epileptogenic zone and peri-ictal zone, changes in which may serve as a biomarker of epileptogenesis and anti-epileptogenic treatment response in pre-clinical studies. These findings were associated with improved object location memory with Chir99021 treatment after IHK. This study provides novel evidence that canonical Wnt activation prevents epileptogenesis in the IHK mouse model of mesial temporal lobe epilepsy, preventing pathological remodeling of dentate granule cells. Wnt signaling may therefore play a key role in mesial temporal lobe epileptogenesis, and Wnt modulation may represent a novel therapeutic strategy in the prevention of epilepsy.
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Affiliation(s)
- Muriel D Mardones
- Indiana University, Stark Neurosciences Research Institute, W 15th St, Indianapolis, IN 46202, United States of America; Indiana University, Department of Neurosurgery, W 16th St, Indianapolis, IN 46202, United States of America.
| | - Kevin D Rostam
- Indiana University, Stark Neurosciences Research Institute, W 15th St, Indianapolis, IN 46202, United States of America.
| | - Margaret C Nickerson
- Indiana University, Stark Neurosciences Research Institute, W 15th St, Indianapolis, IN 46202, United States of America.
| | - Kunal Gupta
- Medical College of Wisconsin, Department of Neurosurgery, 8701 Watertown Plank Rd, Milwaukee, WI 53226, United States of America; Medical College of Wisconsin, Neuroscience Research Center, 8701 Watertown Plank Rd, Milwaukee, WI 53226, United States of America; Indiana University, Stark Neurosciences Research Institute, W 15th St, Indianapolis, IN 46202, United States of America; Indiana University, Department of Neurosurgery, W 16th St, Indianapolis, IN 46202, United States of America.
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Ahmedt-Aristizabal D, Armin MA, Hayder Z, Garcia-Cairasco N, Petersson L, Fookes C, Denman S, McGonigal A. Deep learning approaches for seizure video analysis: A review. Epilepsy Behav 2024; 154:109735. [PMID: 38522192 DOI: 10.1016/j.yebeh.2024.109735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 02/06/2024] [Accepted: 03/03/2024] [Indexed: 03/26/2024]
Abstract
Seizure events can manifest as transient disruptions in the control of movements which may be organized in distinct behavioral sequences, accompanied or not by other observable features such as altered facial expressions. The analysis of these clinical signs, referred to as semiology, is subject to observer variations when specialists evaluate video-recorded events in the clinical setting. To enhance the accuracy and consistency of evaluations, computer-aided video analysis of seizures has emerged as a natural avenue. In the field of medical applications, deep learning and computer vision approaches have driven substantial advancements. Historically, these approaches have been used for disease detection, classification, and prediction using diagnostic data; however, there has been limited exploration of their application in evaluating video-based motion detection in the clinical epileptology setting. While vision-based technologies do not aim to replace clinical expertise, they can significantly contribute to medical decision-making and patient care by providing quantitative evidence and decision support. Behavior monitoring tools offer several advantages such as providing objective information, detecting challenging-to-observe events, reducing documentation efforts, and extending assessment capabilities to areas with limited expertise. The main applications of these could be (1) improved seizure detection methods; (2) refined semiology analysis for predicting seizure type and cerebral localization. In this paper, we detail the foundation technologies used in vision-based systems in the analysis of seizure videos, highlighting their success in semiology detection and analysis, focusing on work published in the last 7 years. We systematically present these methods and indicate how the adoption of deep learning for the analysis of video recordings of seizures could be approached. Additionally, we illustrate how existing technologies can be interconnected through an integrated system for video-based semiology analysis. Each module can be customized and improved by adapting more accurate and robust deep learning approaches as these evolve. Finally, we discuss challenges and research directions for future studies.
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Affiliation(s)
- David Ahmedt-Aristizabal
- Imaging and Computer Vision Group, CSIRO Data61, Australia; SAIVT Laboratory, Queensland University of Technology, Australia.
| | | | - Zeeshan Hayder
- Imaging and Computer Vision Group, CSIRO Data61, Australia.
| | - Norberto Garcia-Cairasco
- Physiology Department and Neuroscience and Behavioral Sciences Department, Ribeirão Preto Medical School, University of São Paulo, Brazil.
| | - Lars Petersson
- Imaging and Computer Vision Group, CSIRO Data61, Australia.
| | - Clinton Fookes
- SAIVT Laboratory, Queensland University of Technology, Australia.
| | - Simon Denman
- SAIVT Laboratory, Queensland University of Technology, Australia.
| | - Aileen McGonigal
- Neurosciences Centre, Mater Hospital, Australia; Queensland Brain Institute, The University of Queensland, Australia.
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Wendling F, Koksal-Ersoz E, Al-Harrach M, Yochum M, Merlet I, Ruffini G, Bartolomei F, Benquet P. Multiscale neuro-inspired models for interpretation of EEG signals in patients with epilepsy. Clin Neurophysiol 2024; 161:198-210. [PMID: 38520800 DOI: 10.1016/j.clinph.2024.03.006] [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: 09/15/2023] [Revised: 03/06/2024] [Accepted: 03/11/2024] [Indexed: 03/25/2024]
Abstract
OBJECTIVE The aim is to gain insight into the pathophysiological mechanisms underlying interictal epileptiform discharges observed in electroencephalographic (EEG) and stereo-EEG (SEEG, depth electrodes) recordings performed during pre-surgical evaluation of patients with drug-resistant epilepsy. METHODS We developed novel neuro-inspired computational models of the human cerebral cortex at three different levels of description: i) microscale (detailed neuron models), ii) mesoscale (neuronal mass models) and iii) macroscale (whole brain models). Although conceptually different, micro- and mesoscale models share some similar features, such as the typology of neurons (pyramidal cells and three types of interneurons), their spatial arrangement in cortical layers, and their synaptic connectivity (excitatory and inhibitory). The whole brain model consists of a large-scale network of interconnected neuronal masses, with connectivity based on the human connectome. RESULTS For these three levels of description, the fine-tuning of free parameters and the quantitative comparison with real data allowed us to reproduce interictal epileptiform discharges with a high degree of fidelity and to formulate hypotheses about the cell- and network-related mechanisms underlying the generation of fast ripples and SEEG-recorded epileptic spikes and spike-waves. CONCLUSIONS The proposed models provide valuable insights into the pathophysiological mechanisms underlying the generation of epileptic events. The knowledge gained from these models effectively complements the clinical analysis of SEEG data collected during the evaluation of patients with epilepsy. SIGNIFICANCE These models are likely to play a key role in the mechanistic interpretation of epileptiform activity.
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Affiliation(s)
| | | | | | | | | | | | - Fabrice Bartolomei
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology Department, Marseille, France; Univ Aix Marseille, INSERM, INS, Inst Neurosci Syst, Marseille, France
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Marchi A, Guex R, Denis M, El Youssef N, Pizzo F, Bénar CG, Bartolomei F. Neurofeedback and epilepsy: Renaissance of an old self-regulation method? Rev Neurol (Paris) 2024; 180:314-325. [PMID: 38485630 DOI: 10.1016/j.neurol.2024.02.386] [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: 02/28/2024] [Accepted: 02/28/2024] [Indexed: 04/28/2024]
Abstract
Neurofeedback is a brain-computer interface tool enabling the user to self-regulate their neuronal activity, and ultimately, induce long-term brain plasticity, making it an interesting instrument to cure brain disorders. Although this method has been used successfully in the past as an adjunctive therapy in drug-resistant epilepsy, this approach remains under-explored and deserves more rigorous scientific inquiry. In this review, we present early neurofeedback protocols employed in epilepsy and provide a critical overview of the main clinical studies. We also describe the potential neurophysiological mechanisms through which neurofeedback may produce its therapeutic effects. Finally, we discuss how to innovate and standardize future neurofeedback clinical trials in epilepsy based on evidence from recent research studies.
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Affiliation(s)
- A Marchi
- Epileptology and Cerebral Rhythmology, Timone Hospital, AP-HM, Marseille, France.
| | - R Guex
- Inserm, INS, institut de neuroscience des systèmes, Aix-Marseille University, Marseille, France
| | - M Denis
- Epileptology and Cerebral Rhythmology, Timone Hospital, AP-HM, Marseille, France
| | - N El Youssef
- Epileptology and Cerebral Rhythmology, Timone Hospital, AP-HM, Marseille, France
| | - F Pizzo
- Epileptology and Cerebral Rhythmology, Timone Hospital, AP-HM, Marseille, France; Inserm, INS, institut de neuroscience des systèmes, Aix-Marseille University, Marseille, France
| | - C-G Bénar
- Inserm, INS, institut de neuroscience des systèmes, Aix-Marseille University, Marseille, France
| | - F Bartolomei
- Epileptology and Cerebral Rhythmology, Timone Hospital, AP-HM, Marseille, France; Inserm, INS, institut de neuroscience des systèmes, Aix-Marseille University, Marseille, France
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Chang X, Hao P, Zhang S, Dang Y, Liu A, Zheng N, Dong Z, Zhao H. Multi-scale analysis of acupuncture mechanisms for motor and sensory cortex activity based on SEEG data. Cereb Cortex 2024; 34:bhae127. [PMID: 38652551 DOI: 10.1093/cercor/bhae127] [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: 01/08/2024] [Revised: 03/08/2024] [Accepted: 03/09/2024] [Indexed: 04/25/2024] Open
Abstract
Acupuncture, a traditional Chinese therapy, is gaining attention for its impact on the brain. While existing electroencephalogram and functional magnetic resonance image research has made significant contributions, this paper utilizes stereo-electroencephalography data for a comprehensive exploration of neurophysiological effects. Employing a multi-scale approach, channel-level analysis reveals notable $\delta $-band activity changes during acupuncture. At the brain region level, acupuncture modulated connectivity between the paracentral lobule and the precentral gyrus. Whole-brain analysis indicates acupuncture's influence on network organization, and enhancing $E_{glob}$ and increased interaction between the motor and sensory cortex. Brain functional reorganization is an important basis for functional recovery or compensation after central nervous system injury. The use of acupuncture to stimulate peripheral nerve trunks, muscle motor points, acupoints, etc., in clinical practice may contribute to the reorganization of brain function. This multi-scale perspective provides diverse insights into acupuncture's effects. Remarkably, this paper pioneers the introduction of stereo-electroencephalography data, advancing our understanding of acupuncture's mechanisms and potential therapeutic benefits in clinical settings.
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Affiliation(s)
- Xiaoyu Chang
- School of Comeputer and Artificial Intelligence, Beijing Technology and Business University, Beijing, No. 11/33, Fucheng Road, Haidian District, 100048 Beijing, China
| | - Pengliang Hao
- Central Medical Branch of PLA General Hospital, Chinese PLA General Hospital, 21 Andeli North Street, Dongcheng District, 100120 Beijing, China
| | - Shuhua Zhang
- Department of Neurology, International Headache Centre, Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, 100853 Beijing, China
| | - Yuanyuan Dang
- Department of Neurosurgery, the First Medical Center of Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, 100853 Beijing, China
| | - Aijun Liu
- Department of Neurosurgery, the First Medical Center of Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, 100853 Beijing, China
| | - Nan Zheng
- State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, 100190 Beijing, China
| | - Zhao Dong
- Department of Neurology, International Headache Centre, Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, 100853 Beijing, China
| | - Hulin Zhao
- Department of Neurosurgery, the First Medical Center of Chinese PLA General Hospital, 28 Fuxing Road, Haidian District, 100853 Beijing, China
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Zanello M, Garnier E, Carron R, Jegou A, Lagarde S, Makhalova J, Medina S, Bénar CG, Bartolomei F, Pizzo F. Stereo-EEG-based ictal functional connectivity in patients with periventricular nodular heterotopia-related epilepsy. Epilepsia 2024; 65:e47-e54. [PMID: 38345420 DOI: 10.1111/epi.17891] [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: 10/17/2023] [Revised: 01/09/2024] [Accepted: 01/09/2024] [Indexed: 04/16/2024]
Abstract
Nodular heterotopia (NH)-related drug-resistant epilepsy is challenging due to the deep location of the NH and the complexity of the underlying epileptogenic network. Using ictal stereo-electroencephalography (SEEG) and functional connectivity (FC) analyses in 14 patients with NH-related drug-resistant epilepsy, we aimed to determine the leading structure during seizures. For this purpose, we compared node IN and OUT strength between bipolar channels inside the heterotopia and inside gray matter, at the group level and at the individual level. At seizure onset, the channels within NH belonging to the epileptogenic and/or propagation network showed higher node OUT-strength than the channels within the gray matter (p = .03), with higher node OUT-strength than node IN-strength (p = .03). These results are in favor of a "leading" role of NH during seizure onset when involved in the epileptogenic- or propagation-zone network (50% of patients). However, when looking at the individual level, no significant difference between NH and gray matter was found, except for one patient (in two of three seizures). This result confirms the heterogeneity and the complexity of the epileptogenic network organization in NH and the need for SEEG exploration to characterize more precisely patient-specific epileptogenic network organization.
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Affiliation(s)
- Marc Zanello
- Service de Neurochirurgie, GHU Paris Psychiatrie et Neurosciences, Hôpital Sainte-Anne, Paris, France
- Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, IMA-BRAIN, Université Paris Cité, Paris, France
| | - Elodie Garnier
- INSERM, INS, Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
| | - Romain Carron
- INSERM, INS, Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
- APHM, Timone Hospital, Stereotactic and Functional Neurosurgery, Marseille, France
| | - Aude Jegou
- INSERM, INS, Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
| | - Stanislas Lagarde
- INSERM, INS, Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
| | - Julia Makhalova
- INSERM, INS, Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- APHM La Timone, CEMEREM, Marseille, France
| | - Samuel Medina
- INSERM, INS, Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
| | - Christian-G Bénar
- INSERM, INS, Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
| | - Fabrice Bartolomei
- INSERM, INS, Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
| | - Francesca Pizzo
- INSERM, INS, Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
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Stergiadis C, Kazis D, Klados MA. Epileptic tissue localization using graph-based networks in the high frequency oscillation range of intracranial electroencephalography. Seizure 2024; 117:28-35. [PMID: 38308906 DOI: 10.1016/j.seizure.2024.01.015] [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: 11/20/2023] [Revised: 01/08/2024] [Accepted: 01/24/2024] [Indexed: 02/05/2024] Open
Abstract
PURPOSE High frequency oscillations (HFOs) are an emerging biomarker of epilepsy. However, very few studies have investigated the functional connectivity of interictal iEEG signals in the frequency range of HFOs. Here, we study the corresponding functional networks using graph theory, and we assess their predictive value for automatic electrode classification in a cohort of 20 drug resistant patients. METHODS Coherence-based connectivity analysis was performed on the iEEG recordings, and six different local graph measures were computed in both sub-bands of the HFO frequency range (80-250 Hz and 250-500 Hz). Correlation analysis was implemented between the local graph measures and the ripple and fast ripple rates. Finally, the WEKA software was employed for training and testing different predictive models on the aforementioned local graph measures. RESULTS The ripple rate was significantly correlated with five out of six local graph measures in the functional network. For fast ripples, their rate was also significantly (but negatively) correlated with most of the local metrics. The results from WEKA showed that the Logistic Regression algorithm was able to classify highly HFO-contaminated electrodes with an accuracy of 82.5 % for ripples and 75.4 % for fast ripples. CONCLUSION Functional connectivity networks in the HFO band could represent an alternative to the direct use of distinct HFO events, while also providing important insights about hub epileptic areas that can represent possible surgical targets. Automatic electrode classification through FC-based classifiers can help bypass the burden of manual HFO annotation, providing at the same time similar amount of information about the epileptic tissue.
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Affiliation(s)
- Christos Stergiadis
- Department of Electronic Engineering, University of York, York, YO10 5DD, UK
| | - Dimitrios Kazis
- 3rd Neurological Department, Aristotle University of Thessaloniki Faculty of Health Sciences, Exohi, 57010 Thessaloniki, Greece
| | - Manousos A Klados
- Department of Psychology, University of York Europe Campus, CITY College 24, Proxenou Koromila Street, 546 22 Thessaloniki, Greece; Neuroscience Research Center (NEUREC), University of York Europe Campus, City College, Thessaloniki, Greece.
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Cohen Z, Steinbrenner M, Piper RJ, Tangwiriyasakul C, Richardson MP, Sharp DJ, Violante IR, Carmichael DW. Transcranial electrical stimulation during functional magnetic resonance imaging in patients with genetic generalized epilepsy: a pilot and feasibility study. Front Neurosci 2024; 18:1354523. [PMID: 38572149 PMCID: PMC10989273 DOI: 10.3389/fnins.2024.1354523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 02/13/2024] [Indexed: 04/05/2024] Open
Abstract
Objective A third of patients with epilepsy continue to have seizures despite receiving adequate antiseizure medication. Transcranial direct current stimulation (tDCS) might be a viable adjunct treatment option, having been shown to reduce epileptic seizures in patients with focal epilepsy. Evidence for the use of tDCS in genetic generalized epilepsy (GGE) is scarce. We aimed to establish the feasibility of applying tDCS during fMRI in patients with GGE to study the acute neuromodulatory effects of tDCS, particularly on sensorimotor network activity. Methods Seven healthy controls and three patients with GGE received tDCS with simultaneous fMRI acquisition while watching a movie. Three tDCS conditions were applied: anodal, cathodal and sham. Periods of 60 s without stimulation were applied between each stimulation condition. Changes in sensorimotor cortex connectivity were evaluated by calculating the mean degree centrality across eight nodes of the sensorimotor cortex defined by the Automated Anatomical Labeling atlas (primary motor cortex (precentral left and right), supplementary motor area (left and right), mid-cingulum (left and right), postcentral gyrus (left and right)), across each of the conditions, for each participant. Results Simultaneous tDCS-fMRI was well tolerated in both healthy controls and patients without adverse effects. Anodal and cathodal stimulation reduced mean degree centrality of the sensorimotor network (Friedman's ANOVA with Dunn's multiple comparisons test; adjusted p = 0.02 and p = 0.03 respectively). Mean degree connectivity of the sensorimotor network during the sham condition was not different to the rest condition (adjusted p = 0.94). Conclusion Applying tDCS during fMRI was shown to be feasible and safe in a small group of patients with GGE. Anodal and cathodal stimulation caused a significant reduction in network connectivity of the sensorimotor cortex across participants. This initial research supports the feasibility of using fMRI to guide and understand network modulation by tDCS that might facilitate its clinical application in GGE in the future.
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Affiliation(s)
- Zachary Cohen
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Mirja Steinbrenner
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Rory J. Piper
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- University College London Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Chayanin Tangwiriyasakul
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Mark P. Richardson
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
| | - David J. Sharp
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom
| | - Ines R. Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - David W. Carmichael
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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Karimi-Rouzbahani H, McGonigal A. Generalisability of epileptiform patterns across time and patients. Sci Rep 2024; 14:6293. [PMID: 38491096 PMCID: PMC10942983 DOI: 10.1038/s41598-024-56990-7] [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: 01/20/2024] [Accepted: 03/13/2024] [Indexed: 03/18/2024] Open
Abstract
The complexity of localising the epileptogenic zone (EZ) contributes to surgical resection failures in achieving seizure freedom. The distinct patterns of epileptiform activity during interictal and ictal phases, varying across patients, often lead to suboptimal localisation using electroencephalography (EEG) features. We posed two key questions: whether neural signals reflecting epileptogenicity generalise from interictal to ictal time windows within each patient, and whether epileptiform patterns generalise across patients. Utilising an intracranial EEG dataset from 55 patients, we extracted a large battery of simple to complex features from stereo-EEG (SEEG) and electrocorticographic (ECoG) neural signals during interictal and ictal windows. Our features (n = 34) quantified many aspects of the signals including statistical moments, complexities, frequency-domain and cross-channel network attributes. Decision tree classifiers were then trained and tested on distinct time windows and patients to evaluate the generalisability of epileptogenic patterns across time and patients, respectively. Evidence strongly supported generalisability from interictal to ictal time windows across patients, particularly in signal power and high-frequency network-based features. Consistent patterns of epileptogenicity were observed across time windows within most patients, and signal features of epileptogenic regions generalised across patients, with higher generalisability in the ictal window. Signal complexity features were particularly contributory in cross-patient generalisation across patients. These findings offer insights into generalisable features of epileptic neural activity across time and patients, with implications for future automated approaches to supplement other EZ localisation methods.
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Affiliation(s)
- Hamid Karimi-Rouzbahani
- Neurosciences Centre, Mater Hospital, South Brisbane, 4101, Australia.
- Mater Research Institute, University of Queensland, South Brisbane, 4101, Australia.
- Queensland Brain Institute, University of Queensland, St Lucia, 4072, Australia.
| | - Aileen McGonigal
- Neurosciences Centre, Mater Hospital, South Brisbane, 4101, Australia
- Mater Research Institute, University of Queensland, South Brisbane, 4101, Australia
- Queensland Brain Institute, University of Queensland, St Lucia, 4072, Australia
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Marx B, Medina-Villalon S, Bartolomei F, Lagarde S. How Can a Focal Seizure Lead to a Dacrystic Behavior? A Case Analyzed with Functional Connectivity in Stereoelectroencephalography. Clin EEG Neurosci 2024; 55:272-277. [PMID: 37340756 DOI: 10.1177/15500594231182808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/22/2023]
Abstract
We present a case of a patient with focal non-motor emotional seizures with dacrystic expression in the context of drug-resistant magnetic resonance imaging negative epilepsy. The pre-surgical evaluation suggested a hypothesis of a right fronto-temporal epileptogenic zone. Stereoelectroencephalography recorded dacrystic seizures arising from the right anterior operculo-insular (pars orbitalis) area with secondary propagation to temporal and parietal cortices during the dacrystic behavior. We analyzed functional connectivity during the ictal dacrystic behavior and found an increase of the functional connectivity within a large right fronto-temporo-insular network, broadly similar to the "emotional excitatory" network. It suggests that focal seizure, potentially, from various origins but leading to disorganization of these physiological networks may generate dacrystic behavior.
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Affiliation(s)
- Barbara Marx
- APHM, Timone Hospital, Epileptology Department, Member of the ERN EpiCARE, Marseille, France
| | - Samuel Medina-Villalon
- APHM, Timone Hospital, Epileptology Department, Member of the ERN EpiCARE, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Fabrice Bartolomei
- APHM, Timone Hospital, Epileptology Department, Member of the ERN EpiCARE, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Stanislas Lagarde
- APHM, Timone Hospital, Epileptology Department, Member of the ERN EpiCARE, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
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Baldini S, Duma GM, Danieli A, Antoniazzi L, Vettorel A, Baggio M, Da Rold M, Bonanni P. Electroencephalographic microstates as a potential neurophysiological marker differentiating bilateral from unilateral temporal lobe epilepsy. Epilepsia 2024; 65:664-674. [PMID: 38265624 DOI: 10.1111/epi.17893] [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: 08/04/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 01/25/2024]
Abstract
OBJECTIVE Electroencephalographic (EEG) microstate abnormalities have been documented in different neurological disorders. We aimed to assess whether EEG microstates are altered also in patients with temporal epilepsy (TLE) and whether they show different activations in patients with unilateral TLE (UTLE) and bilateral TLE (BTLE). METHODS Nineteen patients with UTLE, 12 with BTLE, and 15 healthy controls were enrolled. Resting state high-density electroencephalography (128 channels) was recorded for 15 min with closed eyes. We obtained a set of stable scalp maps representing the EEG activity, named microstates, from which we acquired the following variables: global explained variance (GEV), mean duration (MD), time coverage (TC), and frequency of occurrence (FO). Two-way repeated measures analysis of variance was used to compare groups, and Spearman correlation was performed to study the maps in association with the clinical and neuropsychological data. RESULTS Patients with BTLE and UTLE showed differences in most of the parameters (GEV, MD, TC, FO) of the four microstate maps (A-D) compared to controls. Patients with BTLE showed a significant increase in all parameters for the microstates in Map-A and a decrease in Map-D compared to UTLE and controls. We observed a correlation between Map-A, disease duration, and spatial short-term memory, whereas microstate Map-D was correlated with the global intelligence score and short-term memory performance. SIGNIFICANCE A global alteration of the neural dynamics was observed in patients with TLE compared to controls. A different pattern of EEG microstate abnormalities was identified in BTLE compared to UTLE, which might represent a distinctive biomarker.
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Affiliation(s)
- Sara Baldini
- Clinical Unit of Neurology, Department of Medical Sciences, University Hospital and Health Services of Trieste, University of Trieste, Trieste, Italy
| | - Gian Marco Duma
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Eugenio Medea, Epilepsy Unit, Conegliano, TV, Italy
| | - Alberto Danieli
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Eugenio Medea, Epilepsy Unit, Conegliano, TV, Italy
| | - Lisa Antoniazzi
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Eugenio Medea, Epilepsy Unit, Conegliano, TV, Italy
| | | | - Martina Baggio
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Eugenio Medea, Epilepsy Unit, Conegliano, TV, Italy
| | | | - Paolo Bonanni
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Eugenio Medea, Epilepsy Unit, Conegliano, TV, Italy
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Kobayashi K, Taylor KN, Shahabi H, Krishnan B, Joshi A, Mackow MJ, Feldman L, Zamzam O, Medani T, Bulacio J, Alexopoulos AV, Najm I, Bingaman W, Leahy RM, Nair DR. Effective connectivity relates seizure outcome to electrode placement in responsive neurostimulation. Brain Commun 2024; 6:fcae035. [PMID: 38390255 PMCID: PMC10882982 DOI: 10.1093/braincomms/fcae035] [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: 09/12/2022] [Revised: 09/06/2023] [Accepted: 02/19/2024] [Indexed: 02/24/2024] Open
Abstract
Responsive neurostimulation is a closed-loop neuromodulation therapy for drug resistant focal epilepsy. Responsive neurostimulation electrodes are placed near ictal onset zones so as to enable detection of epileptiform activity and deliver electrical stimulation. There is no standard approach for determining the optimal placement of responsive neurostimulation electrodes. Clinicians make this determination based on presurgical tests, such as MRI, EEG, magnetoencephalography, ictal single-photon emission computed tomography and intracranial EEG. Currently functional connectivity measures are not being used in determining the placement of responsive neurostimulation electrodes. Cortico-cortical evoked potentials are a measure of effective functional connectivity. Cortico-cortical evoked potentials are generated by direct single-pulse electrical stimulation and can be used to investigate cortico-cortical connections in vivo. We hypothesized that the presence of high amplitude cortico-cortical evoked potentials, recorded during intracranial EEG monitoring, near the eventual responsive neurostimulation contact sites is predictive of better outcomes from its therapy. We retrospectively reviewed 12 patients in whom cortico-cortical evoked potentials were obtained during stereoelectroencephalography evaluation and subsequently underwent responsive neurostimulation therapy. We studied the relationship between cortico-cortical evoked potentials, the eventual responsive neurostimulation electrode locations and seizure reduction. Directional connectivity indicated by cortico-cortical evoked potentials can categorize stereoelectroencephalography electrodes as either receiver nodes/in-degree (an area of greater inward connectivity) or projection nodes/out-degree (greater outward connectivity). The follow-up period for seizure reduction ranged from 1.3-4.8 years (median 2.7) after responsive neurostimulation therapy started. Stereoelectroencephalography electrodes closest to the eventual responsive neurostimulation contact site tended to show larger in-degree cortico-cortical evoked potentials, especially for the early latency cortico-cortical evoked potentials period (10-60 ms period) in six out of 12 patients. Stereoelectroencephalography electrodes closest to the responsive neurostimulation contacts (≤5 mm) also had greater significant out-degree in the early cortico-cortical evoked potentials latency period than those further away (≥10 mm) (P < 0.05). Additionally, significant correlation was noted between in-degree cortico-cortical evoked potentials and greater seizure reduction with responsive neurostimulation therapy at its most effective period (P < 0.05). These findings suggest that functional connectivity determined by cortico-cortical evoked potentials may provide additional information that could help guide the optimal placement of responsive neurostimulation electrodes.
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Affiliation(s)
- Katsuya Kobayashi
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Kenneth N Taylor
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Hossein Shahabi
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Balu Krishnan
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Anand Joshi
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Michael J Mackow
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Lauren Feldman
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Omar Zamzam
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Takfarinas Medani
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Juan Bulacio
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | | | - Imad Najm
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - William Bingaman
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Richard M Leahy
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Dileep R Nair
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
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Ferrero JJ, Hassan AR, Yu Z, Zhao Z, Ma L, Wu C, Shao S, Kawano T, Engel J, Doyle W, Devinsky O, Khodagholy D, Gelinas JN. Closed-loop electrical stimulation to prevent focal epilepsy progression and long-term memory impairment. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.09.579660. [PMID: 38405990 PMCID: PMC10888806 DOI: 10.1101/2024.02.09.579660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Interictal epileptiform discharges (IEDs) are ubiquitously expressed in epileptic networks and disrupt cognitive functions. It is unclear whether addressing IED-induced dysfunction could improve epilepsy outcomes as most therapeutics target seizures. We show in a model of progressive hippocampal epilepsy that IEDs produce pathological oscillatory coupling which is associated with prolonged, hypersynchronous neural spiking in synaptically connected cortex and expands the brain territory capable of generating IEDs. A similar relationship between IED-mediated oscillatory coupling and temporal organization of IEDs across brain regions was identified in human subjects with refractory focal epilepsy. Spatiotemporally targeted closed-loop electrical stimulation triggered on hippocampal IED occurrence eliminated the abnormal cortical activity patterns, preventing spread of the epileptic network and ameliorating long-term spatial memory deficits in rodents. These findings suggest that stimulation-based network interventions that normalize interictal dynamics may be an effective treatment of epilepsy and its comorbidities, with a low barrier to clinical translation. One-Sentence Summary Targeted closed-loop electrical stimulation prevents spread of the epileptic network and ameliorates long-term spatial memory deficits.
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Bratu IF, Makhalova J, Garnier E, Villalon SM, Jegou A, Bonini F, Lagarde S, Pizzo F, Trébuchon A, Scavarda D, Carron R, Bénar C, Bartolomei F. Permutation entropy-derived parameters to estimate the epileptogenic zone network. Epilepsia 2024; 65:389-401. [PMID: 38041564 DOI: 10.1111/epi.17849] [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: 10/07/2023] [Revised: 11/30/2023] [Accepted: 11/30/2023] [Indexed: 12/03/2023]
Abstract
OBJECTIVE Quantification of the epileptogenic zone network (EZN) most frequently implies analysis of seizure onset. However, important information can also be obtained from the postictal period, characterized by prominent changes in the EZN. We used permutation entropy (PE), a measure of signal complexity, to analyze the peri-ictal stereoelectroencephalography (SEEG) signal changes with emphasis on the postictal state. We sought to determine the best PE-derived parameter (PEDP) for identifying the EZN. METHODS Several PEDPs were computed retrospectively on SEEG-recorded seizures of 86 patients operated on for drug-resistant epilepsy: mean baseline preictal entropy, minimum ictal entropy, maximum postictal entropy, the ratio between the maximum postictal and the minimum ictal entropy, and the ratio between the maximum postictal and the baseline preictal entropy. The performance of each biomarker was assessed by comparing the identified epileptogenic contacts or brain regions against the EZN defined by clinical analysis incorporating the Epileptogenicity Index and the connectivity epileptogenicity index methods (EZNc), using the receiver-operating characteristic and precision-recall. RESULTS The ratio between the maximum postictal and the minimum ictal entropy (defined as the Permutation Entropy Index [PEI]) proved to be the best-performing PEDP to identify the EZNC . It demonstrated the highest area under the curve (AUC) and F1 score at the contact level (AUC 0.72; F1 0.39) and at the region level (AUC 0.78; F1 0.47). PEI values gradually decreased between the EZN, the propagation network, and the non-involved regions. PEI showed higher performance in patients with slow seizure-onset patterns than in those with fast seizure-onset patterns. The percentage of resected epileptogenic regions defined by PEI was significantly correlated with surgical outcome. SIGNIFICANCE PEI is a promising tool to improve the delineation of the EZN. PEI combines ease and robustness in a routine clinical setting with high sensitivity for seizures without fast activity at seizure onset.
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Affiliation(s)
- Ionuț-Flavius Bratu
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Julia Makhalova
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
- APHM, Timone Hospital, CEMEREM, Marseille, France
| | - Elodie Garnier
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Samuel Medina Villalon
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Aude Jegou
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Francesca Bonini
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Stanislas Lagarde
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Francesca Pizzo
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Agnès Trébuchon
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Didier Scavarda
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- APHM Paediatric Neurosurgery Department, Marseille, France
| | - Romain Carron
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- APHM Functional Neurosurgery Department, Marseille, France
| | - Christian Bénar
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Fabrice Bartolomei
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
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Frauscher B, Mansilla D, Abdallah C, Astner-Rohracher A, Beniczky S, Brazdil M, Gnatkovsky V, Jacobs J, Kalamangalam G, Perucca P, Ryvlin P, Schuele S, Tao J, Wang Y, Zijlmans M, McGonigal A. Learn how to interpret and use intracranial EEG findings. Epileptic Disord 2024; 26:1-59. [PMID: 38116690 DOI: 10.1002/epd2.20190] [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: 07/18/2023] [Revised: 10/21/2023] [Accepted: 11/29/2023] [Indexed: 12/21/2023]
Abstract
Epilepsy surgery is the therapy of choice for many patients with drug-resistant focal epilepsy. Recognizing and describing ictal and interictal patterns with intracranial electroencephalography (EEG) recordings is important in order to most efficiently leverage advantages of this technique to accurately delineate the seizure-onset zone before undergoing surgery. In this seminar in epileptology, we address learning objective "1.4.11 Recognize and describe ictal and interictal patterns with intracranial recordings" of the International League against Epilepsy curriculum for epileptologists. We will review principal considerations of the implantation planning, summarize the literature for the most relevant ictal and interictal EEG patterns within and beyond the Berger frequency spectrum, review invasive stimulation for seizure and functional mapping, discuss caveats in the interpretation of intracranial EEG findings, provide an overview on special considerations in children and in subdural grids/strips, and review available quantitative/signal analysis approaches. To be as practically oriented as possible, we will provide a mini atlas of the most frequent EEG patterns, highlight pearls for its not infrequently challenging interpretation, and conclude with two illustrative case examples. This article shall serve as a useful learning resource for trainees in clinical neurophysiology/epileptology by providing a basic understanding on the concepts of invasive intracranial EEG.
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Affiliation(s)
- B Frauscher
- Department of Neurology, Duke University Medical Center and Department of Biomedical Engineering, Duke Pratt School of Engineering, Durham, North Carolina, USA
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Québec, Canada
| | - D Mansilla
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Québec, Canada
- Neurophysiology Unit, Institute of Neurosurgery Dr. Asenjo, Santiago, Chile
| | - C Abdallah
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Québec, Canada
| | - A Astner-Rohracher
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - S Beniczky
- Danish Epilepsy Centre, Dianalund, Denmark
- Aarhus University, Aarhus, Denmark
| | - M Brazdil
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Member of the ERN-EpiCARE, Brno, Czechia
- Behavioral and Social Neuroscience Research Group, Central European Institute of Technology, Masaryk University, Brno, Czechia
| | - V Gnatkovsky
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - J Jacobs
- Department of Paediatrics and Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - G Kalamangalam
- Department of Neurology, University of Florida, Gainesville, Florida, USA
- Wilder Center for Epilepsy Research, University of Florida, Gainesville, Florida, USA
| | - P Perucca
- Epilepsy Research Centre, Department of Medicine (Austin Health), University of Melbourne, Melbourne, Victoria, Australia
- Bladin-Berkovic Comprehensive Epilepsy Program, Department of Neurology, Austin Health, Melbourne, Victoria, Australia
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Department of Neurology, Alfred Health, Melbourne, Victoria, Australia
- Department of Neurology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - P Ryvlin
- Department of Clinical Neurosciences, CHUV, Lausanne University Hospital, Lausanne, Switzerland
| | - S Schuele
- Department of Neurology, Feinberg School of Medicine, Northwestern Memorial Hospital, Chicago, Illinois, USA
| | - J Tao
- Department of Neurology, The University of Chicago, Chicago, Illinois, USA
| | - Y Wang
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
- Wilder Center for Epilepsy Research, University of Florida, Gainesville, Florida, USA
| | - M Zijlmans
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands
| | - A McGonigal
- Department of Neurosciences, Mater Misericordiae Hospital, Brisbane, Queensland, Australia
- Mater Research Institute, Faculty of Medicine, University of Queensland, St Lucia, Queensland, Australia
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41
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Gugger JJ, Walter AE, Diaz‐Arrastia R, Huang J, Jack CR, Reid R, Kucharska‐Newton AM, Gottesman RF, Schneider ALC, Johnson EL. Association between structural brain MRI abnormalities and epilepsy in older adults. Ann Clin Transl Neurol 2024; 11:342-354. [PMID: 38155477 PMCID: PMC10863905 DOI: 10.1002/acn3.51955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 10/21/2023] [Accepted: 11/11/2023] [Indexed: 12/30/2023] Open
Abstract
OBJECTIVE To determine the association between brain MRI abnormalities and incident epilepsy in older adults. METHODS Men and women (ages 45-64 years) from the Atherosclerosis Risk in Communities study were followed up from 1987 to 2018 with brain MRI performed between 2011 and 2013. We identified cases of incident late-onset epilepsy (LOE) with onset of seizures occurring after the acquisition of brain MRI. We evaluated the relative pattern of cortical thickness, subcortical volume, and white matter integrity among participants with incident LOE after MRI in comparison with participants without seizures. We examined the association between MRI abnormalities and incident LOE using Cox proportional hazards regression. Models were adjusted for demographics, hypertension, diabetes, smoking, stroke, and dementia status. RESULTS Among 1251 participants with brain MRI data, 27 (2.2%) developed LOE after MRI over a median of 6.4 years (25-75 percentile 5.8-6.9) of follow-up. Participants with incident LOE after MRI had higher levels of cortical thinning and white matter microstructural abnormalities before seizure onset compared to those without seizures. In longitudinal analyses, greater number of abnormalities was associated with incident LOE after controlling for demographic factors, risk factors for cardiovascular disease, stroke, and dementia (gray matter: hazard ratio [HR]: 2.3, 95% confidence interval [CI]: 1.0-4.9; white matter diffusivity: HR: 3.0, 95% CI: 1.2-7.3). INTERPRETATION This study demonstrates considerable gray and white matter pathology among individuals with LOE, which is present prior to the onset of seizures and provides important insights into the role of neurodegeneration, both of gray and white matter, and the risk of LOE.
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Affiliation(s)
- James J. Gugger
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Alexa E. Walter
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Ramon Diaz‐Arrastia
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Juebin Huang
- Department of NeurologyUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | | | - Robert Reid
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | - Anna M. Kucharska‐Newton
- Department of EpidemiologyUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Rebecca F. Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research ProgramBethesdaMarylandUSA
| | - Andrea L. C. Schneider
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
- Department of Biostatistics, Epidemiology, and InformaticsUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Emily L. Johnson
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
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Bröhl T, Rings T, Pukropski J, von Wrede R, Lehnertz K. The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 3:1338864. [PMID: 38293249 PMCID: PMC10825060 DOI: 10.3389/fnetp.2023.1338864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 12/19/2023] [Indexed: 02/01/2024]
Abstract
Epilepsy is now considered a network disease that affects the brain across multiple levels of spatial and temporal scales. The paradigm shift from an epileptic focus-a discrete cortical area from which seizures originate-to a widespread epileptic network-spanning lobes and hemispheres-considerably advanced our understanding of epilepsy and continues to influence both research and clinical treatment of this multi-faceted high-impact neurological disorder. The epileptic network, however, is not static but evolves in time which requires novel approaches for an in-depth characterization. In this review, we discuss conceptual basics of network theory and critically examine state-of-the-art recording techniques and analysis tools used to assess and characterize a time-evolving human epileptic brain network. We give an account on current shortcomings and highlight potential developments towards an improved clinical management of epilepsy.
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Affiliation(s)
- Timo Bröhl
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
| | - Thorsten Rings
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
| | - Jan Pukropski
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Randi von Wrede
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Klaus Lehnertz
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
- Interdisciplinary Center for Complex Systems, University of Bonn, Bonn, Germany
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Sperling MR, Wu C, Kang J, Makhalova J, Bartolomei F, Southwell D. The Temporal Lobe Club: Newer Approaches to Treat Temporal Lobe Epilepsy. Epilepsy Curr 2024; 24:10-15. [PMID: 38327532 PMCID: PMC10846515 DOI: 10.1177/15357597231213161] [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] [Indexed: 02/09/2024] Open
Abstract
This brief review summarizes presentations at the Temporal Lobe Club Special Interest Group session held in December 2022 at the American Epilepsy Society meeting. The session addressed newer methods to treat temporal epilepsy, including methods currently in clinical use and techniques under investigation. Brief summaries are provided for each of 4 lectures. Dr Chengyuan Wu discussed ablative techniques such as laser interstitial thermal ablation, radiofrequency ablation, focused ultrasound; Dr Joon Kang reviewed neuromodulation techniques including electrical stimulation and focused ultrasound; Dr Julia Makhalova discussed network effects of the aforementioned techniques; and Dr Derek Southwell reviewed inhibitory interneuron transplantation. These summaries are intended to provide a brief overview and references are provided for the reader to learn more about each topic.
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Affiliation(s)
| | - Chengyuan Wu
- Department of Neurological Surgery, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joon Kang
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Julia Makhalova
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
- APHM, Timone Hospital, CEMEREM, Marseille, France
| | - Fabrice Bartolomei
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, France
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Derek Southwell
- Department of Neurosurgery, Duke University, Durham, NC, USA
- Department of Neurobiology, Duke University, Durham, NC, USA
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Rigoni I, Padmasola GP, Sheybani L, Schaller K, Quairiaux C, Vulliemoz S. Reproducible network changes occur in a mouse model of temporal lobe epilepsy but do not correlate with disease severity. Neurobiol Dis 2024; 190:106382. [PMID: 38114050 DOI: 10.1016/j.nbd.2023.106382] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 11/27/2023] [Accepted: 12/13/2023] [Indexed: 12/21/2023] Open
Abstract
Studying the development of brain network disruptions in epilepsy is challenged by the paucity of data before epilepsy onset. Here, we used the unilateral, kainate mouse model of hippocampal epilepsy to investigate brain network changes before and after epilepsy onset and their stability across time. Using 32 epicranial electrodes distributed over the mouse hemispheres, we analyzed EEG epochs free from epileptic activity in 15 animals before and 28 days after hippocampal injection (group 1) and in 20 animals on two consecutive days (d28 and d29, group 2). Statistical dependencies between electrodes were characterized with the debiased-weighted phase lag index. We analyzed: a) graph metric changes from baseline to chronic stage (d28) in group 1; b) their reliability across d28 and d29, in group 2; c) their correlation with epileptic activity (EA: seizure, spike and fast-ripple rates), averaged over d28 and d29, in group 2. During the chronic stage, intra-hemispheric connections of the non-injected hemisphere strengthened, yielding an asymmetrical network in low (4-8 Hz) and high theta (8-12 Hz) bands. The contralateral hemisphere also became more integrated and segregated within the high theta band. Both network topology and EEG markers of EA were stable over consecutive days but not correlated with each other. Altogether, we show reproducible large-scale network modifications after the development of focal epilepsy. These modifications are mostly specific to the non-injected hemisphere. The absence of correlation with epileptic activity does not allow to specifically ascribe these network changes to mechanisms supporting EA or rather compensatory inhibition but supports the notion that epilepsy extends beyond the sole repetition of EA and impacts network that might not be involved in EA generation.
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Affiliation(s)
- Isotta Rigoni
- EEG and Epilepsy unit, Department of Neuroscience, University Hospital and Faculty of Medicine of Geneva, University of Geneva, Geneva, Switzerland.
| | - Guru Prasad Padmasola
- Department of Basic Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Laurent Sheybani
- EEG and Epilepsy unit, Department of Neuroscience, University Hospital and Faculty of Medicine of Geneva, University of Geneva, Geneva, Switzerland; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Karl Schaller
- Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Charles Quairiaux
- Department of Basic Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy unit, Department of Neuroscience, University Hospital and Faculty of Medicine of Geneva, University of Geneva, Geneva, Switzerland
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45
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Murray-Douglass A, Papacostas J, Ovington A, Wensley I, Campbell R, Gillinder L. Stereoelectroencephalography: a review of complications and outcomes in a new Australian centre. Intern Med J 2024; 54:35-42. [PMID: 38165070 DOI: 10.1111/imj.16284] [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: 01/25/2023] [Accepted: 11/01/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND Surgical management of refractory focal epilepsy requires preoperative localisation of the epileptogenic zone (EZ). To augment noninvasive studies, stereoelectroencephalography (SEEG) is being increasingly adopted as a form of intracranial monitoring. AIMS This study aimed to determine the rate of complications for patients undergoing SEEG and to report the success of SEEG with regard to EZ detection and seizure outcome following definitive surgery. METHODS A retrospective cohort design investigated all cases of SEEG at our institution. Surgical, anaesthetic and medical complications with subsequent epilepsy surgery and seizure outcome data were extracted from medical records. Multivariate logistic regression was used to investigate the relationship between both the number of electrodes per patient and the duration of SEEG recording with the rate of complications. RESULTS Sixty-four patients with 66 implantations were included. Headache was the most common complication (n = 54, 82%). There were no major surgical or medical complications. Two anaesthetic complications occurred. EZ localisation was successful in 63 cases (95%). Curative intent surgery was performed in 39 patients (59%) and 23 patients achieved an Engel class I outcome (59% of those undergoing surgery). The number of electrodes and duration of recording were not associated with complications. CONCLUSIONS No patients in our series experienced major surgical or medical complications and we have highlighted the challenges associated with neuroanaesthesia in SEEG. Our complication rates and seizure outcomes are equivalent to published literature indicating that this technique can be successfully established in newer centres using careful case selection. Standardised reporting of SEEG complications should be adopted.
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Affiliation(s)
| | - Jason Papacostas
- Mater Neurosciences Centre, Mater Hospital, Brisbane, Queensland, Australia
| | - Anne Ovington
- Mater Neurosciences Centre, Mater Hospital, Brisbane, Queensland, Australia
| | - Isaac Wensley
- Mater Neurosciences Centre, Mater Hospital, Brisbane, Queensland, Australia
| | - Robert Campbell
- Mater Neurosciences Centre, Mater Hospital, Brisbane, Queensland, Australia
| | - Lisa Gillinder
- Mater Neurosciences Centre, Mater Hospital, Brisbane, Queensland, Australia
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Hines K, Wu C. Epilepsy Networks and Their Surgical Relevance. Brain Sci 2023; 14:31. [PMID: 38248246 PMCID: PMC10813558 DOI: 10.3390/brainsci14010031] [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: 11/09/2023] [Revised: 12/22/2023] [Accepted: 12/24/2023] [Indexed: 01/23/2024] Open
Abstract
Surgical epilepsy is a rapidly evolved field. As the understanding and concepts of epilepsy shift towards a network disorder, surgical outcomes may shed light on numerous components of these systems. This review documents the evolution of the understanding of epilepsy networks and examines the data generated by resective, ablative, neuromodulation, and invasive monitoring surgeries in epilepsy patients. As these network tools are better integrated into epilepsy practice, they may eventually inform surgical decisions and improve clinical outcomes.
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Affiliation(s)
- Kevin Hines
- Department of Neurosurgery, Thomas Jefferson University Hospital, Philadelphia, PA 19107, USA;
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Dou Y, Xia J, Fu M, Cai Y, Meng X, Zhan Y. Identification of epileptic networks with graph convolutional network incorporating oscillatory activities and evoked synaptic responses. Neuroimage 2023; 284:120439. [PMID: 37939889 DOI: 10.1016/j.neuroimage.2023.120439] [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: 05/11/2023] [Revised: 10/01/2023] [Accepted: 10/31/2023] [Indexed: 11/10/2023] Open
Abstract
Stereoelectroencephalography (SEEG) offers unique neural data from in-depth brain structures with fine temporal resolutions to better investigate the origin of epileptic brain activities. Although oscillatory patterns from different frequency bands and functional connectivity computed from the SEEG datasets are employed to study the epileptic zones, direct electrical stimulation-evoked electrophysiological recordings of synaptic responses, namely cortical-cortical evoked potentials (CCEPs), from the same SEEG electrodes are not explored for the localization of epileptic zones. Here we proposed a two-stream model with unsupervised learning and graph convolutional network tailored to the SEEG and CCEP datasets in individual patients to perform localization of epileptic zones. We compared our localization results with the clinically marked electrode sites determined for surgical resections. Our model had good classification capability when compared to other state-of-the-art methods. Furthermore, based on our prediction results we performed group-level brain-area mapping analysis for temporal, frontal and parietal epilepsy patients and found that epileptic and non-epileptic brain networks were distinct in patients with different types of focal epilepsy. Our unsupervised data-driven model provides personalized localization analysis for the epileptic zones. The epileptic and non-epileptic brain areas disclosed by the prediction model provide novel insights into the network-level pathological characteristics of epilepsy.
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Affiliation(s)
- Yonglin Dou
- The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jing Xia
- The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; CAS Key Laboratory of Brain Connectome and Manipulation, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Mengmeng Fu
- Department of Neurosurgery, Shenzhen University General Hospital, Shenzhen University, Shenzhen, China
| | - Yunpeng Cai
- Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Xianghong Meng
- Department of Neurosurgery, Shenzhen University General Hospital, Shenzhen University, Shenzhen, China.
| | - Yang Zhan
- The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; CAS Key Laboratory of Brain Connectome and Manipulation, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen 518055, China.
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Duma GM, Pellegrino G, Rabuffo G, Danieli A, Antoniazzi L, Vitale V, Scotto Opipari R, Bonanni P, Sorrentino P. Altered spread of waves of activities at large scale is influenced by cortical thickness organization in temporal lobe epilepsy: a magnetic resonance imaging-high-density electroencephalography study. Brain Commun 2023; 6:fcad348. [PMID: 38162897 PMCID: PMC10754317 DOI: 10.1093/braincomms/fcad348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/11/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024] Open
Abstract
Temporal lobe epilepsy is a brain network disorder characterized by alterations at both the structural and the functional levels. It remains unclear how structure and function are related and whether this has any clinical relevance. In the present work, we adopted a novel methodological approach investigating how network structural features influence the large-scale dynamics. The functional network was defined by the spatio-temporal spreading of aperiodic bursts of activations (neuronal avalanches), as observed utilizing high-density electroencephalography in patients with temporal lobe epilepsy. The structural network was modelled as the region-based thickness covariance. Loosely speaking, we quantified the similarity of the cortical thickness of any two brain regions, both across groups and at the individual level, the latter utilizing a novel approach to define the subject-wise structural covariance network. In order to compare the structural and functional networks (at the nodal level), we studied the correlation between the probability that a wave of activity would propagate from a source to a target region and the similarity of the source region thickness as compared with other target brain regions. Building on the recent evidence that large-waves of activities pathologically spread through the epileptogenic network in temporal lobe epilepsy, also during resting state, we hypothesize that the structural cortical organization might influence such altered spatio-temporal dynamics. We observed a stable cluster of structure-function correlation in the bilateral limbic areas across subjects, highlighting group-specific features for left, right and bilateral temporal epilepsy. The involvement of contralateral areas was observed in unilateral temporal lobe epilepsy. We showed that in temporal lobe epilepsy, alterations of structural and functional networks pair in the regions where seizures propagate and are linked to disease severity. In this study, we leveraged on a well-defined model of neurological disease and pushed forward personalization approaches potentially useful in clinical practice. Finally, the methods developed here could be exploited to investigate the relationship between structure-function networks at subject level in other neurological conditions.
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Affiliation(s)
- Gian Marco Duma
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Giovanni Pellegrino
- Epilepsy Program, Schulich School of Medicine and Dentistry, Western University, London N6A5C1, Canada
| | - Giovanni Rabuffo
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille 13005, France
| | - Alberto Danieli
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Lisa Antoniazzi
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Valerio Vitale
- Department of Neuroscience, Neuroradiology Unit, San Bortolo Hospital, Vicenza 36100, Italy
| | | | - Paolo Bonanni
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Pierpaolo Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille 13005, France
- Department of Biomedical Sciences, University of Sassari, Sassari 07100, Italy
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Lainscsek C, Salami P, Carvalho VR, Mendes EMAM, Fan M, Cash SS, Sejnowski TJ. Network-motif delay differential analysis of brain activity during seizures. CHAOS (WOODBURY, N.Y.) 2023; 33:123136. [PMID: 38156987 PMCID: PMC10757649 DOI: 10.1063/5.0165904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 11/28/2023] [Indexed: 01/03/2024]
Abstract
Delay Differential Analysis (DDA) is a nonlinear method for analyzing time series based on principles from nonlinear dynamical systems. DDA is extended here to incorporate network aspects to improve the dynamical characterization of complex systems. To demonstrate its effectiveness, DDA with network capabilities was first applied to the well-known Rössler system under different parameter regimes and noise conditions. Network-motif DDA, based on cortical regions, was then applied to invasive intracranial electroencephalographic data from drug-resistant epilepsy patients undergoing presurgical monitoring. The directional network motifs between brain areas that emerge from this analysis change dramatically before, during, and after seizures. Neural systems provide a rich source of complex data, arising from varying internal states generated by network interactions.
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Affiliation(s)
| | - Pariya Salami
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA
| | | | - Eduardo M. A. M. Mendes
- Laboratório de Modelagem, Análise e Controle de Sistemas Não Lineares, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6627, 31270-901 Belo Horizonte, MG, Brazil
| | - Miaolin Fan
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA
| | - Sydney S. Cash
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA
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Thompson SA. Kindling in humans: Does secondary epileptogenesis occur? Epilepsy Res 2023; 198:107155. [PMID: 37301727 DOI: 10.1016/j.eplepsyres.2023.107155] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 04/01/2022] [Accepted: 04/25/2023] [Indexed: 06/12/2023]
Abstract
The relevance of secondary epileptogenesis for human epilepsy remains a controversial subject decades after it was first described in animal models. Whether or not a previously normal brain region can become independently epileptogenic through a kindling-like process has not, and cannot, be definitely proven in humans. Rather than reliance on direct experimental evidence, attempts to answering this question must depend on observational data. In this review, observations based largely upon contemporary surgical series will advance the case for secondary epileptogenesis in humans. As will be argued, hypothalamic hamartoma-related epilepsy provides the strongest case for this process; all the stages of secondary epileptogenesis can be observed. Hippocampal sclerosis (HS) is another pathology where the question of secondary epileptogenesis frequently arises, and observations from bitemporal and dual pathology series are explored. The verdict here is far more difficult to reach, in large part because of the scarcity of longitudinal cohorts; moreover, recent experimental data have challenged the claim that HS is acquired consequent to recurrent seizures. Synaptic plasticity more than seizure-induced neuronal injury is the likely mechanism of secondary epileptogenesis. Postoperative running-down phenomenon provides the best evidence that a kindling-like process occurs in some patients, evidenced by its reversal. Finally, a network perspective of secondary epileptogenesis is considered, as well as the possible role for subcortical surgical interventions.
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Affiliation(s)
- Stephen A Thompson
- Department of Medicine (Neurology), McMaster University, Hamilton, ON, Canada.
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