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McNicholas OC, Jiménez-Jiménez D, Oliveira JFA, Ferguson L, Bellampalli R, McLaughlin C, Chowdhury FA, Martins Custodio H, Moloney P, Mavrogianni A, Diehl B, Sisodiya SM. The influence of temperature and genomic variation on intracranial EEG measures in people with epilepsy. Brain Commun 2024; 6:fcae269. [PMID: 39258258 PMCID: PMC11383581 DOI: 10.1093/braincomms/fcae269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 06/26/2024] [Accepted: 08/11/2024] [Indexed: 09/12/2024] Open
Abstract
Heatwaves have serious impacts on human health and constitute a key health concern from anthropogenic climate change. People have different individual tolerance for heatwaves or unaccustomed temperatures. Those with epilepsy may be particularly affected by temperature as the electroclinical hallmarks of brain excitability in epilepsy (inter-ictal epileptiform discharges and seizures) are influenced by a range of physiological and non-physiological conditions. Heatwaves are becoming more common and may affect brain excitability. Leveraging spontaneous heatwaves during periods of intracranial EEG recording in participants with epilepsy in a non-air-conditioned telemetry unit at the National Hospital for Neurology and Neurosurgery in London from May to August 2015-22, we examined the impact of heatwaves on brain excitability. In London, a heatwave is defined as three or more consecutive days with daily maximum temperatures ≥28°C. For each participant, we counted inter-ictal epileptiform discharges using four 10-min segments within, and outside of, heatwaves during periods of intracranial EEG recording. Additionally, we counted all clinical and subclinical seizures within, and outside of, heatwaves. We searched for causal rare genetic variants and calculated the epilepsy PRS. Nine participants were included in the study (six men, three women), median age 30 years (range 24-39). During heatwaves, there was a significant increase in the number of inter-ictal epileptiform discharges in three participants. Five participants had more seizures during the heatwave period, and as a group, there were significantly more seizures during the heatwaves. Genetic data, available for eight participants, showed none had known rare, genetically-determined epilepsies, whilst all had high polygenic risk scores for epilepsy. For some people with epilepsy, and not just those with known, rare, temperature-sensitive epilepsies, there is an association between heatwaves and increased brain excitability. These preliminary data require further validation and exploration, as they raise concerns about the impact of heatwaves directly on brain health.
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Affiliation(s)
- Olivia C McNicholas
- Sir Jules Thorn Telemetry Unit, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Diego Jiménez-Jiménez
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Buckinghamshire SL9 0RJ, UK
| | - Joana F A Oliveira
- Sir Jules Thorn Telemetry Unit, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Lauren Ferguson
- Institute for Environmental Design and Engineering, The Bartlett School of Environment, Energy and Resources, University College London, London WC1H 0NN, UK
- Department for Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Ravishankara Bellampalli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Buckinghamshire SL9 0RJ, UK
| | - Charlotte McLaughlin
- Sir Jules Thorn Telemetry Unit, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Fahmida Amin Chowdhury
- Sir Jules Thorn Telemetry Unit, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Helena Martins Custodio
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Buckinghamshire SL9 0RJ, UK
| | - Patrick Moloney
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Buckinghamshire SL9 0RJ, UK
| | - Anna Mavrogianni
- Institute for Environmental Design and Engineering, The Bartlett School of Environment, Energy and Resources, University College London, London WC1H 0NN, UK
| | - Beate Diehl
- Sir Jules Thorn Telemetry Unit, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Buckinghamshire SL9 0RJ, UK
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2
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Junges L, Galvis D, Winsor A, Treadwell G, Richards C, Seri S, Johnson S, Terry JR, Bagshaw AP. The impact of paediatric epilepsy and co-occurring neurodevelopmental disorders on functional brain networks in wake and sleep. PLoS One 2024; 19:e0309243. [PMID: 39186749 PMCID: PMC11346934 DOI: 10.1371/journal.pone.0309243] [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: 10/05/2023] [Accepted: 08/07/2024] [Indexed: 08/28/2024] Open
Abstract
Epilepsy is one of the most common neurological disorders in children. Diagnosing epilepsy in children can be very challenging, especially as it often coexists with neurodevelopmental conditions like autism and ADHD. Functional brain networks obtained from neuroimaging and electrophysiological data in wakefulness and sleep have been shown to contain signatures of neurological disorders, and can potentially support the diagnosis and management of co-occurring neurodevelopmental conditions. In this work, we use electroencephalography (EEG) recordings from children, in restful wakefulness and sleep, to extract functional connectivity networks in different frequency bands. We explore the relationship of these networks with epilepsy diagnosis and with measures of neurodevelopmental traits, obtained from questionnaires used as screening tools for autism and ADHD. We explore differences in network markers between children with and without epilepsy in wake and sleep, and quantify the correlation between such markers and measures of neurodevelopmental traits. Our findings highlight the importance of considering the interplay between epilepsy and neurodevelopmental traits when exploring network markers of epilepsy.
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Affiliation(s)
- Leandro Junges
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom
- Institute for Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom
| | - Daniel Galvis
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom
- Institute for Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom
| | - Alice Winsor
- Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Grace Treadwell
- Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
- School of Psychology, Keele University, Staffordshire, United Kingdom
| | - Caroline Richards
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
- Centre for Developmental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Stefano Seri
- Aston Institute of Health and Neurodevelopment, Aston University, Birmingham, United Kingdom
- Department of Clinical Neurophysiology, Birmingham Women’s and Children’s Hospital, Birmingham, United Kingdom
| | - Samuel Johnson
- School of Mathematics, University of Birmingham, Birmingham, United Kingdom
- The Alan Turing Institute, London, United Kingdom
| | - John R. Terry
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom
- Institute for Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom
- Neuronostics Ltd, Engine Shed, Station Approach, Bristol, United Kingdom
| | - Andrew P. Bagshaw
- Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
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3
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Frauscher B, Bartolomei F, Baud MO, Smith RJ, Worrell G, Lundstrom BN. Stimulation to probe, excite, and inhibit the epileptic brain. Epilepsia 2023; 64 Suppl 3:S49-S61. [PMID: 37194746 PMCID: PMC10654261 DOI: 10.1111/epi.17640] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/01/2023] [Accepted: 05/02/2023] [Indexed: 05/18/2023]
Abstract
Direct cortical stimulation has been applied in epilepsy for nearly a century and has experienced a renaissance, given unprecedented opportunities to probe, excite, and inhibit the human brain. Evidence suggests stimulation can increase diagnostic and therapeutic utility in patients with drug-resistant epilepsies. However, choosing appropriate stimulation parameters is not a trivial issue, and is further complicated by epilepsy being characterized by complex brain state dynamics. In this article derived from discussions at the ICTALS 2022 Conference (International Conference on Technology and Analysis for Seizures), we succinctly review the literature on cortical stimulation applied acutely and chronically to the epileptic brain for localization, monitoring, and therapeutic purposes. In particular, we discuss how stimulation is used to probe brain excitability, discuss evidence on the usefulness of stimulation to trigger and stop seizures, review therapeutic applications of stimulation, and finally discuss how stimulation parameters are impacted by brain dynamics. Although research has advanced considerably over the past decade, there are still significant hurdles to optimizing use of this technique. For example, it remains unclear to what extent short timescale diagnostic biomarkers can predict long-term outcomes and to what extent these biomarkers add information to already existing biomarkers from passive electroencephalographic recordings. Further questions include the extent to which closed loop stimulation offers advantages over open loop stimulation, what the optimal closed loop timescales may be, and whether biomarker-informed stimulation can lead to seizure freedom. The ultimate goal of bioelectronic medicine remains not just to stop seizures but rather to cure epilepsy and its comorbidities.
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Affiliation(s)
- Birgit Frauscher
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
| | - Fabrice Bartolomei
- Institut de Neurosciences des Systèmes, Aix Marseille University, Marseille, France. AP-HM, Service de Neurophysiologie Clinique, Hôpital de la Timone, Marseille, France
| | - Maxime O. Baud
- Sleep-Wake-Epilepsy Center, NeuroTec and Center for Experimental Neurology, Department of Neurology, Inselspital Bern, University Hospital, University of Bern, Bern
| | - Rachel J. Smith
- University of Alabama at Birmingham, Electrical and Computer Engineering Department, Birmingham, Alabama, US. University of Alabama at Birmingham, Neuroengineering Program, Birmingham, Alabama, US
| | - Greg Worrell
- Department of Neurology, Mayo Clinic, Rochester, US
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4
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Nejedly P, Kremen V, Lepkova K, Mivalt F, Sladky V, Pridalova T, Plesinger F, Jurak P, Pail M, Brazdil M, Klimes P, Worrell G. Utilization of temporal autoencoder for semi-supervised intracranial EEG clustering and classification. Sci Rep 2023; 13:744. [PMID: 36639549 PMCID: PMC9839708 DOI: 10.1038/s41598-023-27978-6] [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: 11/23/2022] [Accepted: 01/11/2023] [Indexed: 01/14/2023] Open
Abstract
Manual visual review, annotation and categorization of electroencephalography (EEG) is a time-consuming task that is often associated with human bias and requires trained electrophysiology experts with specific domain knowledge. This challenge is now compounded by development of measurement technologies and devices allowing large-scale heterogeneous, multi-channel recordings spanning multiple brain regions over days, weeks. Currently, supervised deep-learning techniques were shown to be an effective tool for analyzing big data sets, including EEG. However, the most significant caveat in training the supervised deep-learning models in a clinical research setting is the lack of adequate gold-standard annotations created by electrophysiology experts. Here, we propose a semi-supervised machine learning technique that utilizes deep-learning methods with a minimal amount of gold-standard labels. The method utilizes a temporal autoencoder for dimensionality reduction and a small number of the expert-provided gold-standard labels used for kernel density estimating (KDE) maps. We used data from electrophysiological intracranial EEG (iEEG) recordings acquired in two hospitals with different recording systems across 39 patients to validate the method. The method achieved iEEG classification (Pathologic vs. Normal vs. Artifacts) results with an area under the receiver operating characteristic (AUROC) scores of 0.862 ± 0.037, 0.879 ± 0.042, and area under the precision-recall curve (AUPRC) scores of 0.740 ± 0.740, 0.714 ± 0.042. This demonstrates that semi-supervised methods can provide acceptable results while requiring only 100 gold-standard data samples in each classification category. Subsequently, we deployed the technique to 12 novel patients in a pseudo-prospective framework for detecting Interictal epileptiform discharges (IEDs). We show that the proposed temporal autoencoder was able to generalize to novel patients while achieving AUROC of 0.877 ± 0.067 and AUPRC of 0.705 ± 0.154.
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Affiliation(s)
- Petr Nejedly
- 1St Department of Neurology, Faculty of Medicine, Masaryk University, Brno, Czech Republic. .,Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic. .,Department of Neurology, Mayo Clinic, Mayo Systems Electrophysiology Laboratory, Rochester, MN, USA.
| | - Vaclav Kremen
- Department of Neurology, Mayo Clinic, Mayo Systems Electrophysiology Laboratory, Rochester, MN, USA. .,Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague, Prague, Czech Republic.
| | - Kamila Lepkova
- Department of Neurology, Mayo Clinic, Mayo Systems Electrophysiology Laboratory, Rochester, MN, USA.,Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czech Republic
| | - Filip Mivalt
- Department of Neurology, Mayo Clinic, Mayo Systems Electrophysiology Laboratory, Rochester, MN, USA.,Faculty of Electrical Engineering and Communication, Brno University of Technology, Brno, Czech Republic
| | - Vladimir Sladky
- Department of Neurology, Mayo Clinic, Mayo Systems Electrophysiology Laboratory, Rochester, MN, USA
| | - Tereza Pridalova
- Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic.,Department of Neurology, Mayo Clinic, Mayo Systems Electrophysiology Laboratory, Rochester, MN, USA
| | - Filip Plesinger
- Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic
| | - Pavel Jurak
- Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic
| | - Martin Pail
- 1St Department of Neurology, Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic.,International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Milan Brazdil
- 1St Department of Neurology, Faculty of Medicine, Masaryk University, Brno, Czech Republic.,International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic.,CEITEC - Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Petr Klimes
- Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic.,International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Gregory Worrell
- Department of Neurology, Mayo Clinic, Mayo Systems Electrophysiology Laboratory, Rochester, MN, USA.
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5
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Lai N, Cheng H, Li Z, Wang X, Ruan Y, Qi Y, Yang L, Fei F, Dai S, Chen L, Zheng Y, Xu C, Fang J, Wang S, Chen Z, Wang Y. Interictal-period-activated neuronal ensemble in piriform cortex retards further seizure development. Cell Rep 2022; 41:111798. [PMID: 36516780 DOI: 10.1016/j.celrep.2022.111798] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 07/23/2022] [Accepted: 11/16/2022] [Indexed: 12/15/2022] Open
Abstract
Epileptic networks are characterized as having two states, seizures or more prolonged interictal periods. However, cellular mechanisms underlying the contribution of interictal periods to ictal events remain unclear. Here, we use an activity-dependent labeling technique combined with genetically encoded effectors to characterize and manipulate neuronal ensembles recruited by focal seizures (FS-Ens) and interictal periods (IP-Ens) in piriform cortex, a region that plays a key role in seizure generation. Ca2+ activities and histological evidence reveal a disjointed correlation between the two ensembles during FS dynamics. Optogenetic activation of FS-Ens promotes further seizure development, while IP-Ens protects against it. Interestingly, both ensembles are functionally involved in generalized seizures (GS) due to circuit rearrangement. IP-Ens bidirectionally modulates FS but not GS by controlling coherence with hippocampus. This study indicates that the interictal state may represent a seizure-preventing environment, and the interictal-activated ensemble may serve as a potential therapeutic target for epilepsy.
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Affiliation(s)
- Nanxi Lai
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Heming Cheng
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Zhisheng Li
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Xia Wang
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yeping Ruan
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Yingbei Qi
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Lin Yang
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Fan Fei
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Sijie Dai
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Liying Chen
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yang Zheng
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Cenglin Xu
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Jiajia Fang
- Department of Neurology, Fourth Affiliated Hospital, School of Medicine, Zhejiang University, Yiwu 322000, China
| | - Shuang Wang
- Epilepsy Center, Department of Neurology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China
| | - Zhong Chen
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China; Epilepsy Center, Department of Neurology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China.
| | - Yi Wang
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China; Epilepsy Center, Department of Neurology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China.
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Wang ZJ, Noh BH, Kim ES, Yang D, Yang S, Kim NY, Hur YJ, Kim HD. Brain network analysis of interictal epileptiform discharges from ECoG to identify epileptogenic zone in pediatric patients with epilepsy and focal cortical dysplasia type II: A retrospective study. Front Neurol 2022; 13:901633. [PMID: 35989902 PMCID: PMC9388828 DOI: 10.3389/fneur.2022.901633] [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: 03/22/2022] [Accepted: 07/19/2022] [Indexed: 11/13/2022] Open
Abstract
Objective For patients with drug-resistant focal epilepsy, intracranial monitoring remains the gold standard for surgical intervention. Focal cortical dysplasia (FCD) is the most common cause of pharmacoresistant focal epilepsy in pediatric patients who usually develop seizures in early childhood. Timely removal of the epileptogenic zone (EZ) is necessary to achieve lasting seizure freedom and favorable developmental and cognitive outcomes to improve the quality of life. We applied brain network analysis to investigate potential biomarkers for the diagnosis of EZ that will aid in the resection for pediatric focal epilepsy patients with FCD type II. Methods Ten pediatric patients with focal epilepsy diagnosed as FCD type II and that had a follow-up after resection surgery (Engel class I [n = 9] and Engel class II [n = 1]) were retrospectively included. Time-frequency analysis of phase transfer entropy, graph theory analysis, and power spectrum compensation were combined to calculate brain network parameters based on interictal epileptiform discharges from ECoG. Results Clustering coefficient, local efficiency, node out-degree, and node out-strength with higher values are the most reliable biomarkers for the delineation of EZ, and the differences between EZ and margin zone (MZ), and EZ and normal zone (NZ) were significant (p < 0.05; Mann-Whitney U-test, two-tailed). In particular, the difference between MZ and NZ was significant for patients with frontal FCD (MZ > NZ; p < 0.05) but was not significant for patients with extra-frontal FCD. Conclusions Brain network analysis, based on the combination of time-frequency analysis of phase transfer entropy, graph theory analysis, and power spectrum compensation, can aid in the diagnosis of EZ for pediatric focal epilepsy patients with FCD type II.
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Affiliation(s)
- Zhi Ji Wang
- Division of Pediatric Neurology, Department of Pediatrics, Severance Children's Hospital, Epilepsy Research Institute, Yonsei University College of Medicine, Seoul, South Korea
- Radio Frequency Integrated Circuit (RFIC), Kwangwoon University, Seoul, South Korea
| | - Byoung Ho Noh
- Department of Pediatrics, Kangwon National University Hospital, Chuncheon-si, South Korea
| | - Eun Seong Kim
- Radio Frequency Integrated Circuit (RFIC), Kwangwoon University, Seoul, South Korea
| | - Donghwa Yang
- Division of Pediatric Neurology, Department of Pediatrics, Severance Children's Hospital, Epilepsy Research Institute, Yonsei University College of Medicine, Seoul, South Korea
- Division of Pediatric Neurology, Department of Pediatrics, National Health Insurance Service Ilsan Hospital, Goyang-si, South Korea
| | - Shan Yang
- Radio Frequency Integrated Circuit (RFIC), Kwangwoon University, Seoul, South Korea
| | - Nam Young Kim
- Radio Frequency Integrated Circuit (RFIC), Kwangwoon University, Seoul, South Korea
| | - Yun Jung Hur
- Department of Pediatrics, Haeundae Paik Hospital, Inje University College of Medicine, Busan, South Korea
| | - Heung Dong Kim
- Division of Pediatric Neurology, Department of Pediatrics, Severance Children's Hospital, Epilepsy Research Institute, Yonsei University College of Medicine, Seoul, South Korea
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Cheng C, Liu Y, You B, Zhou Y, Gao F, Yang L, Dai Y. Multilevel Feature Learning Method for Accurate Interictal Epileptiform Spike Detection. IEEE Trans Neural Syst Rehabil Eng 2022; 30:2506-2516. [PMID: 35877795 DOI: 10.1109/tnsre.2022.3193666] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Interictal epileptiform spike (referred to as spike) detected from electroencephalograms lasting only 20- to 200-ms can provide a reliable evidence-based indicator for clinical seizure type diagnosis. Recent feature representation approaches focus either on the concrete-level or on abstract-level information mining of the spike, thus demonstrating suboptimal detection performance. Additionally, existing abstract-level information mining methods of the spike based deep learning networks have not realized the effective feature representation of long-term dependent distinguished information within similar waveform cycles caused by morphological heterogeneity, which affects detection performance. Thus, a multilevel feature learning method for accurate spike detection was proposed in this study. Specifically, the spatio-temporal-frequency multidomain information in concrete-level first are inferred the common mimetic properties of the spike using the multidomain feature extractors. Then, the effective feature representation of long-term dependent distinguished information within similar waveform cycles caused by morphological heterogeneity is suitably captured using the temporal convolutional network. Finally, the spatio-temporal-frequency multidomain long-term dependent feature representation of spike is calculated using the element-wise manner to fuse the feature representation in concrete- and abstract-levels. The experimental results indicate that the proposed method can achieve an accuracy of 90.62±1.38%, sensitivity of 90.38±1.52%, specificity of 91.00±1.60%, precision of 90.33±4.71%, and the false detection rate per minute is 0.148±0.020m-1, which are higher than when using the feature representation in the concrete- or abstract-level alone. Additionally, the detection results indicate that the proposed method avoids the subjectivity and inefficiency of visual inspection, and it enables a highly accurate detection of the spike.
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8
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Buluş E, Abanoz Y, Gülen Abanoz Y, Yeni SN. The Effect of Cognitive Tasks During Electroencephalography Recording in Patients With Reflex Seizures. Clin EEG Neurosci 2022; 53:54-60. [PMID: 33356510 DOI: 10.1177/1550059420983622] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
OBJECTIVE We aimed to research the effect of cognitive tasks on interictal electroencephalographic (EEG) recordings in patients with epilepsy who had reported cognitive functions as a seizure trigger. We investigated the usefulness of cognitive function tasks as a method of activation in standard-awake EEG in daily practice. METHODS Standard-awake EEG with cognitive activation tasks consisting of verbal and arithmetic tasks was administered to 35 (11.7%) of 299 patients with epilepsy who reported cognitive functions as a reflex seizure stimulus. During the background EEG, patients were divided into 2 groups: group 1 (17 patients) with interictal epileptiform discharges (IEDs), and group 2 (18 patients) without IEDs. RESULTS IEDs were activated by a verbal task in 11.4% of patients and by an arithmetic task in 5.7%. All activated patients were in the genetic/idiopathic generalized epilepsy (IGE) group. In group 1, IEDs were activated in 17.6% of patients by a verbal task and in 5.9% by an arithmetic task. Both verbal and arithmetic tasks showed provocative effect in one patient in group 2. Hyperventilation was the most effective activation method, followed by cognitive activation tasks and photic stimulation. The provocative effects of verbal and arithmetic tasks were comparable to those of photic stimulation. CONCLUSION Cognitive tasks might activate the IEDs in patients reporting cognitive functions as a seizure trigger, particularly in IGE. Brief and standardized cognitive activation tasks should be developed and applied as a method of activation during standard-awake EEG recordings to increase the diagnostic yield of EEG.
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Affiliation(s)
- Eser Buluş
- School of Medicine, Department of Neurology, Koç University, Istanbul, Turkey
| | - Yasin Abanoz
- Neurology Clinic, Istanbul, Turkey.,Advanced Vocational School, Department of Electroneurophysiology, Doğuş University, Istanbul, Turkey
| | - Yeşim Gülen Abanoz
- Neurology Clinic, Istanbul, Turkey.,Advanced Vocational School, Department of Electroneurophysiology, Doğuş University, Istanbul, Turkey
| | - Seher Naz Yeni
- School of Medicine, Department of Neurology, Istanbul University-Cerrahpaşa, Istanbul, Turkey
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9
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Georgopoulou V, Spruyt K, Garganis K, Kosmidis MH. Altered Sleep-Related Consolidation and Neurocognitive Comorbidity in CECTS. Front Hum Neurosci 2021; 15:563807. [PMID: 34163335 PMCID: PMC8215163 DOI: 10.3389/fnhum.2021.563807] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 04/21/2021] [Indexed: 12/03/2022] Open
Abstract
Our aim is to use neurophysiological sleep-related consolidation (SRC) phenomena to identify putative pathophysiological mechanisms in CECTS linked to diffuse neurocognitive deficits. We argue that there are numerous studies on the association between seizure aspects and neurocognitive functioning but not as many on interictal variables and neurocognitive deficits. We suggest two additional foci. First, the interictal presentation in CECTS and second, neuronal oscillations involved in SRC processes. Existing data on mechanisms through which interictal epileptiform spikes (IES) impact upon SRC indicate that they have the potential to: (a) perturb cross-regional coupling of neuronal oscillations, (b) mimic consolidation processes, (c) alter the precision of the spatiotemporal coupling of oscillations, and (d) variably impact upon SRC performance. Sleep spindles merit systematic study in CECTS in order to clarify: (a) the state of the slow oscillations (SOs) with which they coordinate, (b) the precision of slow oscillation-spindle coupling, and (c) whether their developmental trajectories differ from those of healthy children. We subsequently review studies on the associations between IES load during NREM sleep and SRC performance in childhood epilepsy. We then use sleep consolidation neurophysiological processes and their interplay with IES to help clarify the diffuse neurocognitive deficits that have been empirically documented in CECTS. We claim that studying SRC in CECTS will help to clarify pathophysiological mechanisms toward diverse neurocognitive deficits. Future developments could include close links between the fields of epilepsy and sleep, as well as new therapeutic neurostimulation targets. At the clinical level, children diagnosed with CECTS could benefit from close monitoring with respect to epilepsy, sleep and neurocognitive functions.
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Affiliation(s)
- Victoria Georgopoulou
- 2nd Centre for Educational and Counseling Support of Eastern Thessaloniki, Ministry of Education, Thessaloniki, Greece.,Department of Educational and Social Policy, University of Macedonia, Thessaloniki, Greece
| | - Karen Spruyt
- INSERM, Claude Bernard University, School of Medicine, Lyon, France
| | | | - Mary H Kosmidis
- Lab of Cognitive Neuroscience, School of Psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece
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Bernard C. Circadian/multidien Molecular Oscillations and Rhythmicity of Epilepsy (MORE). Epilepsia 2020; 62 Suppl 1:S49-S68. [PMID: 33063860 DOI: 10.1111/epi.16716] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 09/15/2020] [Accepted: 09/15/2020] [Indexed: 12/26/2022]
Abstract
The occurrence of seizures at specific times of the day has been consistently observed for centuries in individuals with epilepsy. Electrophysiological recordings provide evidence that seizures have a higher probability of occurring at a given time during the night and day cycle in individuals with epilepsy here referred to as the seizure rush hour. Which mechanisms underlie such circadian rhythmicity of seizures? Why don't they occur every day at the same time? Which mechanisms may underlie their occurrence outside the rush hour? In this commentary, I present a hypothesis: MORE - Molecular Oscillations and Rhythmicity of Epilepsy, a conceptual framework to study and understand the mechanisms underlying the circadian rhythmicity of seizures and their probabilistic nature. The core of the hypothesis is the existence of ~24-hour oscillations of gene and protein expression throughout the body in different cells and organs. The orchestrated molecular oscillations control the rhythmicity of numerous body events, such as feeding and sleep. The concept developed here is that molecular oscillations may favor seizure genesis at preferred times, generating the condition for a seizure rush hour. However, the condition is not sufficient, as other factors are necessary for a seizure to occur. Studying these molecular oscillations may help us understand seizure genesis mechanisms and find new therapeutic targets and predictive biomarkers. The MORE hypothesis can be generalized to comorbidities and the slower multidien (week/month period) rhythmicity of seizures, a phenomenon addressed in another article in this issue of Epilepsia.
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Affiliation(s)
- Christophe Bernard
- Inserm, INS, Institut de Neurosciences des Systèmes, Aix Marseille Univ, Marseille, France
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Abstract
We aimed to explore the link between NREM sleep and epilepsy. Based on human and experimental data we propose that a sleep-related epileptic transformation of normal neurological networks underlies epileptogenesis. Major childhood epilepsies as medial temporal lobe epilepsy (MTLE), absence epilepsy (AE) and human perisylvian network (PN) epilepsies - made us good models to study. These conditions come from an epileptic transformation of the affected functional systems. This approach allows a system-based taxonomy instead of the outworn generalized-focal classification. MTLE links to the memory-system, where epileptic transformation results in a switch of normal sharp wave-ripples to epileptic spikes and pathological high frequency oscillations, compromising sleep-related memory consolidation. Absence epilepsy (AE) and juvenile myoclonic epilepsy (JME) belong to the corticothalamic system. The burst-firing mode of NREM sleep normally producing sleep-spindles turns to an epileptic working mode ejecting bilateral synchronous spike-waves. There seems to be a progressive transition from AE to JME. Shared absences and similar bilateral synchronous discharges show the belonging of the two conditions, while the continuous age windows - AE affecting schoolchildren, JME the adolescents - and the increased excitability in JME compared to AE supports the notion of progression. In perisylvian network epilepsies - idiopathic focal childhood epilepsies and electrical status epilepticus in sleep including Landau-Kleffner syndrome - centrotemporal spikes turn epileptic, with the potential to cause cognitive impairment. Postinjury epilepsies modeled by the isolated cortex model highlight the shared way of epileptogenesis suggesting the derailment of NREM sleep-related homeostatic plasticity as a common step. NREM sleep provides templates for plasticity derailing to epileptic variants under proper conditions. This sleep-origin explains epileptiform discharges' link and similarity with NREM sleep slow oscillations, spindles and ripples. Normal synaptic plasticity erroneously overgrowing homeostatic processes may derail toward an epileptic working-mode manifesting the involved system's features. The impact of NREM sleep is unclear in epileptogenesis occurring in adolescence and adulthood, when plasticity is lower. The epileptic process interferes with homeostatic synaptic plasticity and may cause cognitive impairment. Its type and degree depends on the affected network's function. We hypothesize a vicious circle between sleep end epilepsy. The epileptic derailment of normal plasticity interferes with sleep cognitive functions. Sleep and epilepsy interconnect by the pathology of plasticity.
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Affiliation(s)
- Péter Halász
- Szentágothai János School of Ph.D Studies, Clinical Neurosciences, Semmelweis University, Budapest, Hungary
| | - Anna Szűcs
- Institute of Behavioral Sciences, Semmelweis University, Budapest, Hungary
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