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Urriola J, Bollmann S, Tremayne F, Burianová H, Marstaller L, Reutens D. Spikes with and without concurrent high-frequency oscillations: Topographic relationship and neural correlates using EEG-fMRI. Epilepsy Res 2022; 188:107039. [DOI: 10.1016/j.eplepsyres.2022.107039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 09/11/2022] [Accepted: 10/17/2022] [Indexed: 11/03/2022]
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2
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Li X, Zhang H, Lai H, Wang J, Wang W, Yang X. High-Frequency Oscillations and Epileptogenic Network. Curr Neuropharmacol 2022; 20:1687-1703. [PMID: 34503414 PMCID: PMC9881061 DOI: 10.2174/1570159x19666210908165641] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 08/26/2021] [Accepted: 08/31/2021] [Indexed: 11/22/2022] Open
Abstract
Epilepsy is a network disease caused by aberrant neocortical large-scale connectivity spanning regions on the scale of several centimeters. High-frequency oscillations, characterized by the 80-600 Hz signals in electroencephalography, have been proven to be a promising biomarker of epilepsy that can be used in assessing the severity and susceptibility of epilepsy as well as the location of the epileptogenic zone. However, the presence of a high-frequency oscillation network remains a topic of debate as high-frequency oscillations have been previously thought to be incapable of propagation, and the relationship between high-frequency oscillations and the epileptogenic network has rarely been discussed. Some recent studies reported that high-frequency oscillations may behave like networks that are closely relevant to the epileptogenic network. Pathological highfrequency oscillations are network-driven phenomena and elucidate epileptogenic network development; high-frequency oscillations show different characteristics coincident with the epileptogenic network dynamics, and cross-frequency coupling between high-frequency oscillations and other signals may mediate the generation and propagation of abnormal discharges across the network.
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Affiliation(s)
- Xiaonan Li
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
| | | | | | - Jiaoyang Wang
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
| | - Wei Wang
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
| | - Xiaofeng Yang
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China,Address correspondence to this author at the Bioland Laboratory, Guangzhou, China; Tel: 86+ 18515855127; E-mail:
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Ikemoto S, von Ellenrieder N, Gotman J. EEG-fMRI of epileptiform discharges: non-invasive investigation of the whole brain. Epilepsia 2022; 63:2725-2744. [PMID: 35822919 DOI: 10.1111/epi.17364] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 07/08/2022] [Accepted: 07/11/2022] [Indexed: 02/01/2023]
Abstract
Simultaneous EEG-fMRI is a unique and non-invasive method for investigating epileptic activity. Interictal epileptiform discharge-related EEG-fMRI provides cortical and subcortical blood oxygen level-dependent (BOLD) signal changes specific to epileptic discharges. As a result, EEG-fMRI has revealed insights into generators and networks involved in epileptic activity in different types of epilepsy, demonstrating-for instance-the implication of the thalamus in human generalized spike and wave discharges and the role of the Default Mode Network (DMN) in absences and focal epilepsy, and proposed a mechanism for the cortico-subcortical interactions in Lennox-Gastaut syndrome discharges. EEG-fMRI can find deep sources of epileptic activity not available to scalp EEG or MEG and provides critical new information to delineate the epileptic focus when considering surgical treatment or electrode implantation. In recent years, methodological advances, such as artifact removal and automatic detection of events have rendered this method easier to implement, and its clinical potential has since been established by evidence of the impact of BOLD response on clinical decision-making and of the relationship between concordance of BOLD responses with extent of resection and surgical outcome. This review presents the recent developments in EEG-fMRI methodology and EEG-fMRI studies in different types of epileptic disorders as follows: EEG-fMRI acquisition, gradient and pulse artifact removal, statistical analysis, clinical applications, pre-surgical evaluation, altered physiological state in generalized genetic epilepsy, and pediatric EEG-fMRI studies.
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Affiliation(s)
- Satoru Ikemoto
- Montreal Neurological Institute and Hospital, 3801 Rue University, Montreal, QC, Canada.,The Jikei University School of Medicine, Department of Pediatrics, 3-25-8 Nishi-Shimbashi, Minato-ku, Tokyo, Japan
| | | | - Jean Gotman
- Montreal Neurological Institute and Hospital, 3801 Rue University, Montreal, QC, Canada
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High-frequency oscillations in scalp EEG: A systematic review of methodological choices and clinical findings. Clin Neurophysiol 2022; 137:46-58. [DOI: 10.1016/j.clinph.2021.12.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 12/13/2021] [Accepted: 12/21/2021] [Indexed: 02/08/2023]
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5
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Sun Y, Ren G, Ren J, Wang Q. High-frequency oscillations detected by electroencephalography as biomarkers to evaluate treatment outcome, mirror pathological severity and predict susceptibility to epilepsy. ACTA EPILEPTOLOGICA 2021. [DOI: 10.1186/s42494-021-00063-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
AbstractHigh-frequency oscillations (HFOs) in the electroencephalography (EEG) have been extensively investigated as a potential biomarker of epileptogenic zones. The understanding of the role of HFOs in epilepsy has been advanced considerably over the past decade, and the use of scalp EEG facilitates recordings of HFOs. HFOs were initially applied in large scale in epilepsy surgery and are now being utilized in other applications. In this review, we summarize applications of HFOs in 3 subtopics: (1) HFOs as biomarkers to evaluate epilepsy treatment outcome; (2) HFOs as biomarkers to measure seizure propensity; (3) HFOs as biomarkers to reflect the pathological severity of epilepsy. Nevertheless, knowledge regarding the above clinical applications of HFOs remains limited at present. Further validation through prospective studies is required for its reliable application in the clinical management of individual epileptic patients.
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Wang W, Li H, Yan J, Zhang H, Li X, Zheng S, Wang J, Xing Y, Cheng L, Li D, Lai H, Qu J, Loh HH, Fang F, Yang X. Automatic detection of interictal ripples on scalp EEG to evaluate the effect and prognosis of ACTH therapy in patients with infantile spasms. Epilepsia 2021; 62:2240-2251. [PMID: 34309835 DOI: 10.1111/epi.17018] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 07/12/2021] [Accepted: 07/13/2021] [Indexed: 12/22/2022]
Abstract
OBJECTIVE We aimed to explore the feasibility of using scalp-recorded high-frequency oscillations (HFOs) to evaluate the efficacy and prognosis of adrenocorticotropic hormone (ACTH) treatment in patients with infantile spasms. METHODS Thirty-nine children with infantile spasms were enrolled and divided into seizure-free and non-seizure-free groups after ACTH treatment. Patients who were seizure-free were further divided into relapse and non-relapse subgroups based on the observations made during a 6-month follow-up period. Scalp ripples were detected and compared during the interictal periods before and after 2 weeks of treatment. RESULTS After ACTH treatment, the number and channels of ripples were significantly lower, whereas the percentage decrease in the number, spectral power, and channels of ripples was significantly higher in the seizure-free group than in the non-seizure-free group. In addition, the relapse subgroup showed higher number and spectral power and wider distribution of ripples than did the non-relapse subgroup. Changes in HFOs in terms of number, spectral power, and channel of ripples were closely related to the severity of epilepsy and can indicate disease susceptibility. SIGNIFICANCE Scalp HFOs can be used as an effective biomarker to monitor the effect and evaluate the prognosis of ACTH therapy in patients with infantile spasms.
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Affiliation(s)
- Wei Wang
- Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China.,Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Hua Li
- Department of Neurology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Jiaqing Yan
- College of Electrical and Control Engineering, North China University of Technology, Beijing, China
| | - Herui Zhang
- Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Xiaonan Li
- Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China.,Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Su Zheng
- Department of Neurology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Jiaoyang Wang
- Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China.,Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Yue Xing
- Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Lipeng Cheng
- Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China.,Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Donghong Li
- The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Huanling Lai
- Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Junda Qu
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Horace H Loh
- Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Fang Fang
- Department of Neurology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Xiaofeng Yang
- Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China.,Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
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Fan Y, Dong L, Liu X, Wang H, Liu Y. Recent advances in the noninvasive detection of high-frequency oscillations in the human brain. Rev Neurosci 2020; 32:305-321. [PMID: 33661582 DOI: 10.1515/revneuro-2020-0073] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 10/23/2020] [Indexed: 01/10/2023]
Abstract
In recent decades, a significant body of evidence based on invasive clinical research has showed that high-frequency oscillations (HFOs) are a promising biomarker for localization of the seizure onset zone (SOZ), and therefore, have the potential to improve postsurgical outcomes in patients with epilepsy. Emerging clinical literature has demonstrated that HFOs can be recorded noninvasively using methods such as scalp electroencephalography (EEG) and magnetoencephalography (MEG). Not only are HFOs considered to be a useful biomarker of the SOZ, they also have the potential to gauge disease severity, monitor treatment, and evaluate prognostic outcomes. In this article, we review recent clinical research on noninvasively detected HFOs in the human brain, with a focus on epilepsy. Noninvasively detected scalp HFOs have been investigated in various types of epilepsy. HFOs have also been studied noninvasively in other pathologic brain disorders, such as migraine and autism. Herein, we discuss the challenges reported in noninvasive HFO studies, including the scarcity of MEG and high-density EEG equipment in clinical settings, low signal-to-noise ratio, lack of clinically approved automated detection methods, and the difficulty in differentiating between physiologic and pathologic HFOs. Additional studies on noninvasive recording methods for HFOs are needed, especially prospective multicenter studies. Further research is fundamental, and extensive work is needed before HFOs can routinely be assessed in clinical settings; however, the future appears promising.
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Affiliation(s)
- Yuying Fan
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Liping Dong
- Library of China Medical University, Shenyang, China
| | - Xueyan Liu
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Hua Wang
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yunhui Liu
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, China
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Park CJ, Hong SB. High Frequency Oscillations in Epilepsy: Detection Methods and Considerations in Clinical Application. J Epilepsy Res 2019; 9:1-13. [PMID: 31482052 PMCID: PMC6706641 DOI: 10.14581/jer.19001] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Revised: 01/02/2019] [Accepted: 01/04/2019] [Indexed: 01/10/2023] Open
Abstract
High frequency oscillations (HFOs) is a brain activity observed in electroencephalography (EEG) in frequency ranges between 80–500 Hz. HFOs can be classified into ripples (80–200 Hz) and fast ripples (200–500 Hz) by their distinctive characteristics. Recent studies reported that both ripples and fast fipples can be regarded as a new biomarker of epileptogenesis and ictogenesis. Previous studies verified that HFOs are clinically important both in patients with mesial temporal lobe epilepsy and neocortical epilepsy. Also, in epilepsy surgery, patients with higher resection ratio of brain regions with HFOs showed better outcome than a group with lower resection ratio. For clinical application of HFOs, it is important to delineate HFOs accurately and discriminate them from artifacts. There have been technical improvements in detecting HFOs by developing various detection algorithms. Still, there is a difficult issue on discriminating clinically important HFOs among detected HFOs, where both quantitative and subjective approaches are suggested. This paper is a review on published HFO studies focused on clinical findings and detection techniques of HFOs as well as tips for clinical applications.
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Affiliation(s)
- Chae Jung Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Samsung Biomedical Research Institute (SBRI), Seoul, Korea
| | - Seung Bong Hong
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Samsung Biomedical Research Institute (SBRI), Seoul, Korea
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Thomschewski A, Hincapié AS, Frauscher B. Localization of the Epileptogenic Zone Using High Frequency Oscillations. Front Neurol 2019; 10:94. [PMID: 30804887 PMCID: PMC6378911 DOI: 10.3389/fneur.2019.00094] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 01/23/2019] [Indexed: 01/22/2023] Open
Abstract
For patients with drug-resistant focal epilepsy, surgery is the therapy of choice in order to achieve seizure freedom. Epilepsy surgery foremost requires the identification of the epileptogenic zone (EZ), defined as the brain area indispensable for seizure generation. The current gold standard for identification of the EZ is the seizure-onset zone (SOZ). The fact, however that surgical outcomes are unfavorable in 40-50% of well-selected patients, suggests that the SOZ is a suboptimal biomarker of the EZ, and that new biomarkers resulting in better postsurgical outcomes are needed. Research of recent years suggested that high-frequency oscillations (HFOs) are a promising biomarker of the EZ, with a potential to improve surgical success in patients with drug-resistant epilepsy without the need to record seizures. Nonetheless, in order to establish HFOs as a clinical biomarker, the following issues need to be addressed. First, evidence on HFOs as a clinically relevant biomarker stems predominantly from retrospective assessments with visual marking, leading to problems of reproducibility and reliability. Prospective assessments of the use of HFOs for surgery planning using automatic detection of HFOs are needed in order to determine their clinical value. Second, disentangling physiologic from pathologic HFOs is still an unsolved issue. Considering the appearance and the topographic location of presumed physiologic HFOs could be immanent for the interpretation of HFO findings in a clinical context. Third, recording HFOs non-invasively via scalp electroencephalography (EEG) and magnetoencephalography (MEG) is highly desirable, as it would provide us with the possibility to translate the use of HFOs to the scalp in a large number of patients. This article reviews the literature regarding these three issues. The first part of the article focuses on the clinical value of invasively recorded HFOs in localizing the EZ, the detection of HFOs, as well as their separation from physiologic HFOs. The second part of the article focuses on the current state of the literature regarding non-invasively recorded HFOs with emphasis on findings and technical considerations regarding their localization.
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Affiliation(s)
- Aljoscha Thomschewski
- Department of Neurology, Christian Doppler Medical Center, Paracelsus Medical University, Salzburg, Austria
- Department of Psychology, Paris-Lodron University of Salzburg, Salzburg, Austria
| | - Ana-Sofía Hincapié
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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Ikemoto S, Hamano SI, Yokota S, Koichihara R, Hirata Y, Matsuura R. Enhancement and bilateral synchronization of ripples in atypical benign epilepsy of childhood with centrotemporal spikes. Clin Neurophysiol 2018; 129:1920-1925. [DOI: 10.1016/j.clinph.2018.06.023] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Revised: 06/14/2018] [Accepted: 06/20/2018] [Indexed: 11/28/2022]
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11
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Migliorelli C, Alonso JF, Romero S, Nowak R, Russi A, Mañanas MA. Automated detection of epileptic ripples in MEG using beamformer-based virtual sensors. J Neural Eng 2018; 14:046013. [PMID: 28327467 DOI: 10.1088/1741-2552/aa684c] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE In epilepsy, high-frequency oscillations (HFOs) are expressively linked to the seizure onset zone (SOZ). The detection of HFOs in the noninvasive signals from scalp electroencephalography (EEG) and magnetoencephalography (MEG) is still a challenging task. The aim of this study was to automate the detection of ripples in MEG signals by reducing the high-frequency noise using beamformer-based virtual sensors (VSs) and applying an automatic procedure for exploring the time-frequency content of the detected events. APPROACH Two-hundred seconds of MEG signal and simultaneous iEEG were selected from nine patients with refractory epilepsy. A two-stage algorithm was implemented. Firstly, beamforming was applied to the whole head to delimitate the region of interest (ROI) within a coarse grid of MEG-VS. Secondly, a beamformer using a finer grid in the ROI was computed. The automatic detection of ripples was performed using the time-frequency response provided by the Stockwell transform. Performance was evaluated through comparisons with simultaneous iEEG signals. MAIN RESULTS ROIs were located within the seizure-generating lobes in the nine subjects. Precision and sensitivity values were 79.18% and 68.88%, respectively, by considering iEEG-detected events as benchmarks. A higher number of ripples were detected inside the ROI compared to the same region in the contralateral lobe. SIGNIFICANCE The evaluation of interictal ripples using non-invasive techniques can help in the delimitation of the epileptogenic zone and guide placement of intracranial electrodes. This is the first study that automatically detects ripples in MEG in the time domain located within the clinically expected epileptic area taking into account the time-frequency characteristics of the events through the whole signal spectrum. The algorithm was tested against intracranial recordings, the current gold standard. Further studies should explore this approach to enable the localization of noninvasively recorded HFOs to help during pre-surgical planning and to reduce the need for invasive diagnostics.
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Affiliation(s)
- Carolina Migliorelli
- Department of Automatic Control (ESAII), Biomedical Engineering Research Center (CREB), Universitat Politènica de Catalunya (UPC), Barcelona, Spain. Biomedical Research Networking center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
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12
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Frauscher B, Bartolomei F, Kobayashi K, Cimbalnik J, van 't Klooster MA, Rampp S, Otsubo H, Höller Y, Wu JY, Asano E, Engel J, Kahane P, Jacobs J, Gotman J. High-frequency oscillations: The state of clinical research. Epilepsia 2017; 58:1316-1329. [PMID: 28666056 DOI: 10.1111/epi.13829] [Citation(s) in RCA: 211] [Impact Index Per Article: 30.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/25/2017] [Indexed: 01/03/2023]
Abstract
Modern electroencephalographic (EEG) technology contributed to the appreciation that the EEG signal outside the classical Berger frequency band contains important information. In epilepsy, research of the past decade focused particularly on interictal high-frequency oscillations (HFOs) > 80 Hz. The first large application of HFOs was in the context of epilepsy surgery. This is now followed by other applications such as assessment of epilepsy severity and monitoring of antiepileptic therapy. This article reviews the evidence on the clinical use of HFOs in epilepsy with an emphasis on the latest developments. It highlights the growing literature on the association between HFOs and postsurgical seizure outcome. A recent meta-analysis confirmed a higher resection ratio for HFOs in seizure-free versus non-seizure-free patients. Residual HFOs in the postoperative electrocorticogram were shown to predict epilepsy surgery outcome better than preoperative HFO rates. The review further discusses the different attempts to separate physiological from epileptic HFOs, as this might increase the specificity of HFOs. As an example, analysis of sleep microstructure demonstrated a different coupling between HFOs inside and outside the epileptogenic zone. Moreover, there is increasing evidence that HFOs are useful to measure disease activity and assess treatment response using noninvasive EEG and magnetoencephalography. This approach is particularly promising in children, because they show high scalp HFO rates. HFO rates in West syndrome decrease after adrenocorticotropic hormone treatment. Presence of HFOs at the time of rolandic spikes correlates with seizure frequency. The time-consuming visual assessment of HFOs, which prevented their clinical application in the past, is now overcome by validated computer-assisted algorithms. HFO research has considerably advanced over the past decade, and use of noninvasive methods will make HFOs accessible to large numbers of patients. Prospective multicenter trials are awaited to gather information over long recording periods in large patient samples.
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Affiliation(s)
- Birgit Frauscher
- Department of Medicine and Center for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada
| | - Fabrice Bartolomei
- National Institute of Health and Medical Research, Institute of Neurosciences of Systems, Aix Marseille University, Marseille, France
| | - Katsuhiro Kobayashi
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University Hospital, Kita-ku, Okayama, Japan
| | - Jan Cimbalnik
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Maryse A van 't Klooster
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, Erlangen, Germany
| | - Hiroshi Otsubo
- Division of Neurology, Department of Pediatrics, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Yvonne Höller
- Department of Neurology, Christian Doppler Medical Center and Center for Cognitive Neuroscience, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Joyce Y Wu
- Division of Pediatric Neurology, Mattel Children's Hospital at UCLA, Los Angeles, California, U.S.A
| | - Eishi Asano
- Departments of Pediatrics and Neurology, Detroit Medical Center, Children's Hospital of Michigan, Wayne State University, Detroit, Michigan, U.S.A
| | - Jerome Engel
- Departments of Neurology, Neurobiology, and Psychiatry, Brain Research Institute, University of California, Los Angeles, Los Angeles, California, U.S.A
| | - Philippe Kahane
- Department of Neurology, Grenoble-Alpes University Hospital and Grenoble-Alpes University, Grenoble, France
| | - Julia Jacobs
- Department of Neuropediatrics and Muscular Diseases, University Medical Center Freiburg, Freiburg, Germany
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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von Ellenrieder N, Dan J, Frauscher B, Gotman J. Sparse asynchronous cortical generators can produce measurable scalp EEG signals. Neuroimage 2016; 138:123-133. [PMID: 27262240 DOI: 10.1016/j.neuroimage.2016.05.067] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2016] [Revised: 04/19/2016] [Accepted: 05/26/2016] [Indexed: 11/19/2022] Open
Abstract
We investigate to what degree the synchronous activation of a smooth patch of cortex is necessary for observing EEG scalp activity. We perform extensive simulations to compare the activity generated on the scalp by different models of cortical activation, based on intracranial EEG findings reported in the literature. The spatial activation is modeled as a cortical patch of constant activation or as random sets of small generators (0.1 to 3cm(2) each) concentrated in a cortical region. Temporal activation models for the generation of oscillatory activity are either equal phase or random phase across the cortical patches. The results show that smooth or random spatial activation profiles produce scalp electric potential distributions with the same shape. Also, in the generation of oscillatory activity, multiple cortical generators with random phase produce scalp activity attenuated on average only 2 to 4 times compared to generators with equal phase. Sparse asynchronous cortical generators can produce measurable scalp EEG. This is a possible explanation for seemingly paradoxical observations of simultaneous disorganized intracranial activity and scalp EEG signals. Thus, the standard interpretation of scalp EEG might constitute an oversimplification of the underlying brain activity.
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Affiliation(s)
- Nicolás von Ellenrieder
- Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada.
| | - Jonathan Dan
- Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada; École Polytechnique, Université Libre de Bruxelles, 50 Avenue F. D. Roosevelt, 1050 Bruxelles, Belgium
| | - Birgit Frauscher
- Department of Medicine, Center for Neuroscience Studies, Queen's University, 18 Stuart Street, Kingston, Ontario, K7L 3N6, Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada
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von Ellenrieder N, Pellegrino G, Hedrich T, Gotman J, Lina JM, Grova C, Kobayashi E. Detection and Magnetic Source Imaging of Fast Oscillations (40-160 Hz) Recorded with Magnetoencephalography in Focal Epilepsy Patients. Brain Topogr 2016; 29:218-31. [PMID: 26830767 PMCID: PMC4754324 DOI: 10.1007/s10548-016-0471-9] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Accepted: 01/16/2016] [Indexed: 02/03/2023]
Abstract
We present a framework to detect fast oscillations (FOs) in magnetoencephalography (MEG) and to perform magnetic source imaging (MSI) to determine the location and extent of their generators in the cortex. FOs can be of physiologic origin associated to sensory processing and memory consolidation. In epilepsy, FOs are of pathologic origin and biomarkers of the epileptogenic zone. Seventeen patients with focal epilepsy previously confirmed with identified FOs in scalp electroencephalography (EEG) were
evaluated. To handle data deriving from large number of sensors (275 axial gradiometers) we used an automatic detector with high sensitivity. False positives were discarded by two human experts. MSI of the FOs was performed with the wavelet based maximum entropy on the mean method. We found FOs in 11/17 patients, in only one patient the channel with highest FO rate was not concordant with the epileptogenic region and might correspond to physiologic oscillations. MEG FOs rates were very low: 0.02–4.55 per minute. Compared to scalp EEG, detection sensitivity was lower, but the specificity higher in MEG. MSI of FOs showed concordance or partial concordance with proven generators of seizures and epileptiform activity in 10/11 patients. We have validated the proposed framework for the non-invasive study of FOs with MEG. The excellent overall concordance with other clinical gold standard evaluation tools indicates that MEG FOs can provide relevant information to guide implantation for intracranial EEG pre-surgical evaluation and for surgical treatment, and demonstrates the important added value of choosing appropriate FOs detection and source localization methods.
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Affiliation(s)
- Nicolás von Ellenrieder
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada.,Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, 3775 University Street, Montreal, QC, H3A 2B4, Canada.,LEICI, CONICET - Universidad Nacional de La Plata, Calle 116 y 48, 1900, La Plata, Argentina
| | - Giovanni Pellegrino
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, 3775 University Street, Montreal, QC, H3A 2B4, Canada
| | - Tanguy Hedrich
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, 3775 University Street, Montreal, QC, H3A 2B4, Canada
| | - Jean Gotman
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada
| | - Jean-Marc Lina
- Département de Génie Électrique, École de Technologie Supérieure, 1100 Notre-Dame Street West, Montreal, QC, H3C 1K3, Canada.,Centre de Recherches Mathematiques, Univeristé de Montréal, 2920 Chemin de la tour, Montreal, QC, H3T 1J4, Canada.,Center for Advanced Research on Sleep Medecine, Centre de Rech. de l'Hôpital du Sacré-Cœur de Montréal, 5400 W Gouin Blvd, Montreal, QC, H4J 1J5, Canada
| | - Christophe Grova
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada.,Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, 3775 University Street, Montreal, QC, H3A 2B4, Canada.,Physics Department and PERFORM Centre, Concordia University, 7141 Sherbrooke Street West, Montreal, QC, H4B 1R6, Canada
| | - Eliane Kobayashi
- Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada.
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15
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van Klink NEC, Bauer PR, Zijlmans M. Making sense of ripples in generalized epilepsy. Clin Neurophysiol 2016; 127:1759-61. [PMID: 26777056 DOI: 10.1016/j.clinph.2015.12.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Revised: 12/14/2015] [Accepted: 12/15/2015] [Indexed: 11/25/2022]
Affiliation(s)
- N E C van Klink
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, University Medical Center Utrecht, The Netherlands
| | - P R Bauer
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands; NIHR University College London Hospitals Biomedical Research Centre, UCL Institute of Neurology, London, United Kingdom
| | - M Zijlmans
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, University Medical Center Utrecht, The Netherlands; Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands.
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16
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Pizzo F, Ferrari-Marinho T, Amiri M, Frauscher B, Dubeau F, Gotman J. When spikes are symmetric, ripples are not: Bilateral spike and wave above 80 Hz in focal and generalized epilepsy. Clin Neurophysiol 2015; 127:1794-802. [PMID: 26762951 DOI: 10.1016/j.clinph.2015.11.451] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2015] [Revised: 10/24/2015] [Accepted: 11/27/2015] [Indexed: 11/25/2022]
Abstract
OBJECTIVE To evaluate scalp ripples distribution in secondary bilateral synchrony as a tool to lateralize the epileptic focus and to differentiate focal from generalized epilepsy. METHODS Seventeen EEG recordings with bilateral synchronous discharges of focal (focal group-FG: 10) and generalized (generalized group-GG: 7) epilepsy patients were selected for spikes and ripples marking; the spike-normalized ripple rate was calculated in each hemisphere (right/left - anterior/posterior) and a ripple-dominant hemisphere (the one with the highest rate) was identified. Concordance in FG between the ripple dominant hemisphere and the hemisphere of clinical lateralization was evaluated. The ripple-dominant/ripple-nondominant spike-normalized ripple rate ratio was studied to compare groups. RESULTS In FG the hemisphere of clinical lateralization and the ripple-dominant hemisphere were 100% concordant. In GG only 3/7 patients showed ripples (vs 10/10 FG), all with anterior dominance. No difference in hemisphere ripple dominance between groups was found. CONCLUSIONS Ripples in secondary bilateral synchrony help to lateralize the epileptic focus but do not help to differentiate between focal and generalized epilepsy. This is the first report of visually identified ripples in idiopathic generalized epilepsy. SIGNIFICANCE Ripples confirm the clinical lateralization of the epileptic focus in secondary bilateral synchrony but cannot distinguish between focal and generalized epilepsy.
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Affiliation(s)
- Francesca Pizzo
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada; Epilepsy Unit, Careggi Hospital, University of Florence, Florence, Italy.
| | - Taissa Ferrari-Marinho
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada; Department of Clinical Neurophysiology, Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Mina Amiri
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Francois Dubeau
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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