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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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Withers CP, Diamond JM, Yang B, Snyder K, Abdollahi S, Sarlls J, Chapeton JI, Theodore WH, Zaghloul KA, Inati SK. Identifying sources of human interictal discharges with travelling wave and white matter propagation. Brain 2023; 146:5168-5181. [PMID: 37527460 PMCID: PMC11046055 DOI: 10.1093/brain/awad259] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 06/30/2023] [Accepted: 07/19/2023] [Indexed: 08/03/2023] Open
Abstract
Interictal epileptiform discharges have been shown to propagate from focal epileptogenic sources as travelling waves or through more rapid white matter conduction. We hypothesize that both modes of propagation are necessary to explain interictal discharge timing delays. We propose a method that, for the first time, incorporates both propagation modes to identify unique potential sources of interictal activity. We retrospectively analysed 38 focal epilepsy patients who underwent intracranial EEG recordings and diffusion-weighted imaging for epilepsy surgery evaluation. Interictal discharges were detected and localized to the most likely source based on relative delays in time of arrival across electrodes, incorporating travelling waves and white matter propagation. We assessed the influence of white matter propagation on distance of spread, timing and clinical interpretation of interictal activity. To evaluate accuracy, we compared our source localization results to earliest spiking regions to predict seizure outcomes. White matter propagation helps to explain the timing delays observed in interictal discharge sequences, underlying rapid and distant propagation. Sources identified based on differences in time of receipt of interictal discharges are often distinct from the leading electrode location. Receipt of activity propagating rapidly via white matter can occur earlier than more local activity propagating via slower cortical travelling waves. In our cohort, our source localization approach was more accurate in predicting seizure outcomes than the leading electrode location. Inclusion of white matter in addition to travelling wave propagation in our model of discharge spread did not improve overall accuracy but allowed for identification of unique and at times distant potential sources of activity, particularly in patients with persistent postoperative seizures. Since distant white matter propagation can occur more rapidly than local travelling wave propagation, combined modes of propagation within an interictal discharge sequence can decouple the commonly assumed relationship between spike timing and distance from the source. Our findings thus highlight the clinical importance of recognizing the presence of dual modes of propagation during interictal discharges, as this may be a cause of clinical mislocalization.
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Affiliation(s)
- C Price Withers
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Joshua M Diamond
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Braden Yang
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kathryn Snyder
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Shervin Abdollahi
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Joelle Sarlls
- NIH MRI Research Facility, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Julio I Chapeton
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - William H Theodore
- Clinical Epilepsy Section, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kareem A Zaghloul
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Sara K Inati
- Neurophysiology of Epilepsy Unit, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
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Luan C, Miller J, Sollars C, Peng J, Singh J. Stereo-Electroencephalography-Recorded Interictal Epileptiform Discharges: Activation Pattern and Its Relationship With Surgical Outcome. Cureus 2023; 15:e41337. [PMID: 37546108 PMCID: PMC10397415 DOI: 10.7759/cureus.41337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/02/2023] [Indexed: 08/08/2023] Open
Abstract
Background Patients with drug-resistant epilepsy commonly undergo stereo-electroencephalography (SEEG) intracranial monitoring for surgical evaluation. Our current practice of defining the epileptogenic zone relies heavily on recognizing the seizure onset zone (SOZ), but the clinical significance of interictal epileptiform discharges (IEDs) is not well established. Methodology We retrospectively identified adult patients who underwent SEEG between January 2019 and May 2022. To study IED activation patterns, we classified IEDs as leading spikes (involved within the SOZ) and distant spikes (outside the SOZ). We calculated each patient's total number of brain subregions generating distant spikes. We correlated them with epilepsy type, duration, and surgical outcome (Engel I: good outcome and Engel II-IV: poor outcome). Results A total of 22 patients were identified during the study period, and 16 underwent surgical intervention (ablation or resection) with one-year post-surgery follow-up. The most common IED morphology was a single spike or sharp followed by periodic spikes or sharps. We found that 87% (n = 19/22) of leading spikes were activated during the first 24 hours of SEEG monitoring, whereas no activation pattern was observed for distant spikes. We found that a higher number of subregions generating distant spikes were associated with poor surgical outcomes (p = 0.002). However, we did not find any significant association between the number of subregions generating distant spikes with epilepsy duration (p = 0.67), temporal or extratemporal-onset epilepsy (p = 0.58), or the presence of an MRI lesion (p = 0.62). Conclusions IEDs involved within the SOZ were found to be activated during the first 24 hours of SEEG monitoring, which could aid in recognizing the pathological spikes and targeted mapping of the irritative zone. We also observed that a higher number of brain subregions generating IEDs outside the SOZ were associated with poor surgical outcomes, but this observation needs to be further studied with larger sample size prospective studies.
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Affiliation(s)
- Cindy Luan
- Neurology, The Ohio State University Wexner Medical Center, Columbus, USA
| | - Jacob Miller
- Biomedical Engineering, The Ohio State University College of Medicine, Columbus, USA
| | - Caleb Sollars
- Neurodiagnostic EEG Lab, The Ohio State University College of Medicine, Columbus, USA
| | - Juan Peng
- Biomedical Informatics, The Ohio State University College of Medicine, Columbus, USA
| | - Jaysingh Singh
- Neurology, The Ohio State University Wexner Medical Center, Columbus, USA
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4
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Janca R, Jezdik P, Ebel M, Kalina A, Kudr M, Jahodova A, Krysl D, Mackova K, Straka B, Marusic P, Krsek P. Distinct patterns of interictal intracranial EEG in focal cortical dysplasia type I and II. Clin Neurophysiol 2023; 151:10-17. [PMID: 37121217 DOI: 10.1016/j.clinph.2023.03.360] [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: 12/28/2022] [Revised: 03/13/2023] [Accepted: 03/21/2023] [Indexed: 05/02/2023]
Abstract
OBJECTIVE Focal cortical dysplasia (FCD) is the most common malformation causing refractory focal epilepsy. Surgical removal of the entire dysplastic cortex is crucial for achieving a seizure-free outcome. Precise presurgical distinctions between FCD types by neuroimaging are difficult, mainly in patients with normal magnetic resonance imaging findings. However, the FCD type is important for planning the extent of surgical approach and counselling. METHODS This study included patients with focal drug-resistant epilepsy and definite histopathological FCD type I or II diagnoses who underwent intracranial electroencephalography (iEEG). We detected interictal epileptiform discharges (IEDs) and their recruitment into repetitive discharges (RDs) to compare electrophysiological patterns characterizing FCD types. RESULTS Patients with FCD type II had a significantly higher IED rate (p < 0.005), a shorter inter-discharge interval within RD episodes (p < 0.003), sleep influence on decreased RD periodicity (p < 0.036), and longer RD episode duration (p < 0.003) than patients with type I. A Bayesian classifier stratified FCD types with 82% accuracy. CONCLUSION Temporal characteristics of IEDs and RDs reflect the histological findings of FCD subtypes and can differentiate FCD types I and II. SIGNIFICANCE Presurgical prediction of FCD type can help to plan a more tailored surgical approach in patients with normal magnetic resonance findings.
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Affiliation(s)
- Radek Janca
- Faculty of Electrical Engineering, Department of Circuit Theory, Czech Technical University in Prague, Technicka 2, 166 27 Prague, Czech Republic.
| | - Petr Jezdik
- Faculty of Electrical Engineering, Department of Circuit Theory, Czech Technical University in Prague, Technicka 2, 166 27 Prague, Czech Republic
| | - Matyas Ebel
- Department of Paediatric Neurology, Motol Epilepsy Center, Second Faculty of Medicine, Charles University and Motol University Hospital, V Uvalu 84, 15006, Prague, Czech Republic(2)
| | - Adam Kalina
- Department of Neurology, Motol Epilepsy Center, Second Faculty of Medicine, Charles University and Motol University Hospital, V Uvalu 84, 15006 Prague, Czech Republic(2)
| | - Martin Kudr
- Department of Paediatric Neurology, Motol Epilepsy Center, Second Faculty of Medicine, Charles University and Motol University Hospital, V Uvalu 84, 15006, Prague, Czech Republic(2)
| | - Alena Jahodova
- Department of Paediatric Neurology, Motol Epilepsy Center, Second Faculty of Medicine, Charles University and Motol University Hospital, V Uvalu 84, 15006, Prague, Czech Republic(2)
| | - David Krysl
- Department of Neurology, Motol Epilepsy Center, Second Faculty of Medicine, Charles University and Motol University Hospital, V Uvalu 84, 15006 Prague, Czech Republic(2)
| | - Katerina Mackova
- Faculty of Electrical Engineering, Department of Circuit Theory, Czech Technical University in Prague, Technicka 2, 166 27 Prague, Czech Republic
| | - Barbora Straka
- Department of Paediatric Neurology, Motol Epilepsy Center, Second Faculty of Medicine, Charles University and Motol University Hospital, V Uvalu 84, 15006, Prague, Czech Republic(2)
| | - Petr Marusic
- Department of Neurology, Motol Epilepsy Center, Second Faculty of Medicine, Charles University and Motol University Hospital, V Uvalu 84, 15006 Prague, Czech Republic(2)
| | - Pavel Krsek
- Department of Paediatric Neurology, Motol Epilepsy Center, Second Faculty of Medicine, Charles University and Motol University Hospital, V Uvalu 84, 15006, Prague, Czech Republic(2)
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Diamond JM, Withers CP, Chapeton JI, Rahman S, Inati SK, Zaghloul KA. Interictal discharges in the human brain are travelling waves arising from an epileptogenic source. Brain 2023; 146:1903-1915. [PMID: 36729683 PMCID: PMC10411927 DOI: 10.1093/brain/awad015] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 12/27/2022] [Accepted: 01/08/2023] [Indexed: 02/03/2023] Open
Abstract
While seizure activity may be electrographically widespread, increasing evidence has suggested that ictal discharges may in fact represent travelling waves propagated from a focal seizure source. Interictal epileptiform discharges (IEDs) are an electrographic manifestation of excessive hypersynchronization of cortical activity that occur between seizures and are considered a marker of potentially epileptogenic tissue. The precise relationship between brain regions demonstrating IEDs and those involved in seizure onset, however, remains poorly understood. Here, we hypothesize that IEDs likewise reflect the receipt of travelling waves propagated from the same regions which give rise to seizures. Forty patients from our institution who underwent invasive monitoring for epilepsy, proceeded to surgery and had at least one year of follow-up were included in our study. Interictal epileptiform discharges were detected using custom software, validated by a clinical epileptologist. We show that IEDs reach electrodes in sequences with a consistent temporal ordering, and this ordering matches the timing of receipt of ictal discharges, suggesting that both types of discharges spread as travelling waves. We use a novel approach for localization of ictal discharges, in which time differences of discharge receipt at nearby electrodes are used to compute source location; similar algorithms have been used in acoustics and geophysics. We find that interictal discharges co-localize with ictal discharges. Moreover, interictal discharges tend to localize to the resection territory in patients with good surgical outcome and outside of the resection territory in patients with poor outcome. The seizure source may originate at, and also travel to, spatially distinct IED foci. Our data provide evidence that interictal discharges may represent travelling waves of pathological activity that are similar to their ictal counterparts, and that both ictal and interictal discharges emerge from common epileptogenic brain regions. Our findings have important clinical implications, as they suggest that seizure source localizations may be derived from interictal discharges, which are much more frequent than seizures.
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Affiliation(s)
- Joshua M Diamond
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - C Price Withers
- Clinical Epilepsy Section, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Julio I Chapeton
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Shareena Rahman
- Office of the Clinical Director, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Sara K Inati
- Clinical Epilepsy Section, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kareem A Zaghloul
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
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Conrad EC, Revell AY, Greenblatt AS, Gallagher RS, Pattnaik AR, Hartmann N, Gugger JJ, Shinohara RT, Litt B, Marsh ED, Davis KA. Spike patterns surrounding sleep and seizures localize the seizure-onset zone in focal epilepsy. Epilepsia 2023; 64:754-768. [PMID: 36484572 PMCID: PMC10045742 DOI: 10.1111/epi.17482] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 12/08/2022] [Accepted: 12/08/2022] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Interictal spikes help localize seizure generators as part of surgical planning for drug-resistant epilepsy. However, there are often multiple spike populations whose frequencies change over time, influenced by brain state. Understanding state changes in spike rates will improve our ability to use spikes for surgical planning. Our goal was to determine the effect of sleep and seizures on interictal spikes, and to use sleep and seizure-related changes in spikes to localize the seizure-onset zone (SOZ). METHODS We performed a retrospective analysis of intracranial electroencephalography (EEG) data from patients with focal epilepsy. We automatically detected interictal spikes and we classified different time periods as awake or asleep based on the ratio of alpha to delta power, with a secondary analysis using the recently published SleepSEEG algorithm. We analyzed spike rates surrounding sleep and seizures. We developed a model to localize the SOZ using state-dependent spike rates. RESULTS We analyzed data from 101 patients (54 women, age range 16-69). The normalized alpha-delta power ratio accurately classified wake from sleep periods (area under the curve = .90). Spikes were more frequent in sleep than wakefulness and in the post-ictal compared to the pre-ictal state. Patients with temporal lobe epilepsy had a greater wake-to-sleep and pre- to post-ictal spike rate increase compared to patients with extra-temporal epilepsy. A machine-learning classifier incorporating state-dependent spike rates accurately identified the SOZ (area under the curve = .83). Spike rates tended to be higher and better localize the seizure-onset zone in non-rapid eye movement (NREM) sleep than in wake or REM sleep. SIGNIFICANCE The change in spike rates surrounding sleep and seizures differs between temporal and extra-temporal lobe epilepsy. Spikes are more frequent and better localize the SOZ in sleep, particularly in NREM sleep. Quantitative analysis of spikes may provide useful ancillary data to localize the SOZ and improve surgical planning.
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Affiliation(s)
- Erin C. Conrad
- Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - Andrew Y. Revell
- Medical Scientist Training Program, University of Pennsylvania, Philadelphia, PA
| | | | - Ryan S. Gallagher
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Akash R. Pattnaik
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
| | - Nicole Hartmann
- Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - James J. Gugger
- Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - Russell T. Shinohara
- Department of Biostatistics, Epidemiology, & Informatics, University of Pennsylvania, Philadelphia, PA
- Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA
| | - Brian Litt
- Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - Eric D. Marsh
- Department of Neurology, University of Pennsylvania, Philadelphia, PA
- Division of Child Neurology, Department of Biostatistics, University of Pennsylvania, Epidemiology, & Informatics, Philadelphi Department of Biostatistics, University of Pennsylvania, Epidemiology, & Informatics, Philadelphi Pediatric Epilepsy Program, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Kathryn A. Davis
- Department of Neurology, University of Pennsylvania, Philadelphia, PA
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Conrad EC, Shinohara RT, Gugger JJ, Revell AY, Das S, Stein JM, Marsh ED, Davis KA, Litt B. Implanting intracranial electrodes does not affect spikes or network connectivity in nearby or connected brain regions. Netw Neurosci 2022; 6:834-849. [PMID: 36607198 PMCID: PMC9810371 DOI: 10.1162/netn_a_00248] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 04/01/2022] [Indexed: 01/10/2023] Open
Abstract
To determine the effect of implanting electrodes on electrographic features of nearby and connected brain regions in patients with drug-resistant epilepsy, we analyzed intracranial EEG recordings from 10 patients with drug-resistant epilepsy who underwent implant revision (placement of additional electrodes) during their hospitalization. We performed automated spike detection and measured EEG functional networks. We analyzed the original electrodes that remained in place throughout the full EEG recording, and we measured the change in spike rates and network connectivity in these original electrodes in response to implanting new electrodes. There was no change in overall spike rate pre- to post-implant revision (t(9) = 0.1, p = 0.95). The peri-revision change in the distribution of spike rate and connectivity across electrodes was no greater than chance (Monte Carlo method, spikes: p = 0.40, connectivity: p = 0.42). Electrodes closer to or more functionally connected to the revision site had no greater change in spike rate or connectivity than more distant or less connected electrodes. Changes in electrographic features surrounding electrode implantation are no greater than baseline fluctuations occurring throughout the intracranial recording. These findings argue against an implant effect on spikes or network connectivity in nearby or connected brain regions.
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Affiliation(s)
- Erin C. Conrad
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T. Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - James J. Gugger
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew Y. Revell
- Medical Scientist Training Program, University of Pennsylvania, Philadelphia, PA, USA
| | - Sandhitsu Das
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Joel M. Stein
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Eric D. Marsh
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
- Division of Child Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kathryn A. Davis
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Brian Litt
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
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8
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Heers M, Böttcher S, Kalina A, Katletz S, Altenmüller DM, Baroumand AG, Strobbe G, van Mierlo P, von Oertzen TJ, Marusic P, Schulze-Bonhage A, Beniczky S, Dümpelmann M. Detection of interictal epileptiform discharges in an extended scalp EEG array and high-density EEG - A prospective multicenter study. Epilepsia 2022; 63:1619-1629. [PMID: 35357698 DOI: 10.1111/epi.17246] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/29/2022] [Accepted: 03/29/2022] [Indexed: 12/01/2022]
Abstract
OBJECTIVES High counts of averaged interictal epileptiform discharges (IEDs) are key components of accurate interictal electric source imaging (ESI) in patients with focal epilepsy. Automated detections may be time-efficient, but they need to identify the correct IED types. Thus, we compared semiautomated and automated detection of IED types in long-term video EEG monitoring (LTM) using an extended scalp EEG array and short-term high-density EEG (hdEEG) with visual detection of IED types and the seizure onset zone (SOZ). METHODS We prospectively recruited consecutive patients from four epilepsy centers who underwent both LTM with 40 electrodes scalp EEG and short-term hdEEG with 256 electrodes. Only patients with a single circumscribed SOZ in LTM were included. In LTM and hdEEG, IED types were identified visually, semiautomatically and automatically. Concordances of semiautomated and automated detections in LTM and hdEEG as well as visual detections in hdEEG were compared against visually detected IED types and the SOZ in LTM. RESULTS Fifty-two out of 62 patients with LTM and hdEEG were included. The most frequent IED types per patient, detected semiautomatically and automatically in LTM and visually in hdEEG, were significantly concordant with the most frequently visually identified IED type in LTM and the SOZ. Semiautomated and automated detections of IED types in hdEEG were significantly concordant with visually identified IED types in LTM only when IED types with more than 50 detected single IEDs were selected. The threshold of 50 detected IED in hdEEG was reached in half of the patients. For all IED types per patient, agreement between visual and semiautomated detections in LTM was high. SIGNIFICANCE Semiautomated and automated detections of IED types in LTM show significant agreement with visually detected IED types and the SOZ. In short-term hdEEG, semiautomated detections of IED types are concordant with visually detected IED types and the SOZ in LTM if high IED counts were detected.
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Affiliation(s)
- Marcel Heers
- Epilepsy Center, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.,Member of European Reference Network EpiCARE
| | - Sebastian Böttcher
- Epilepsy Center, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.,Member of European Reference Network EpiCARE
| | - Adam Kalina
- Member of European Reference Network EpiCARE.,Department of Neurology, Charles University, Second Faculty of Medicine, Motol University Hospital, Prague, Czech Republic
| | - Stefan Katletz
- Member of European Reference Network EpiCARE.,Department of Neurology 1, Kepler Universitätsklinikum, Johannes Kepler University Linz, Linz, Austria
| | - Dirk-Matthias Altenmüller
- Epilepsy Center, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.,Member of European Reference Network EpiCARE
| | - Amir G Baroumand
- Epilog, Vlasgaardstraat 52, Ghent, Belgium.,Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | | | - Pieter van Mierlo
- Epilog, Vlasgaardstraat 52, Ghent, Belgium.,Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Tim J von Oertzen
- Member of European Reference Network EpiCARE.,Department of Neurology 1, Kepler Universitätsklinikum, Johannes Kepler University Linz, Linz, Austria
| | - Petr Marusic
- Member of European Reference Network EpiCARE.,Department of Neurology, Charles University, Second Faculty of Medicine, Motol University Hospital, Prague, Czech Republic
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.,Member of European Reference Network EpiCARE
| | - Sándor Beniczky
- Member of European Reference Network EpiCARE.,Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark.,Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | - Matthias Dümpelmann
- Epilepsy Center, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.,Member of European Reference Network EpiCARE
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9
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Shu S, Luo S, Cao M, Xu K, Qin L, Zheng L, Xu J, Wang X, Gao JH. Informed MEG/EEG source imaging reveals the locations of interictal spikes missed by SEEG. Neuroimage 2022; 254:119132. [PMID: 35337964 DOI: 10.1016/j.neuroimage.2022.119132] [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: 05/06/2021] [Revised: 02/18/2022] [Accepted: 03/21/2022] [Indexed: 11/19/2022] Open
Abstract
Determining the accurate locations of interictal spikes has been fundamental in the presurgical evaluation of epilepsy surgery. Stereo-electroencephalography (SEEG) is able to directly record cortical activity and localize interictal spikes. However, the main caveat of SEEG techniques is that they have limited spatial sampling (covering <5% of the whole brain), which may lead to missed spikes originating from brain regions that were not covered by SEEG. To address this problem, we propose a SEEG-informed minimum-norm estimates (SIMNE) method by combining SEEG with magnetoencephalography (MEG) or EEG. Specifically, the spike locations determined by SEEG offer as a priori information to guide MEG source reconstruction. Both computer simulations and experiments using data from five epilepsy patients were conducted to evaluate the performance of SIMNE. Our results demonstrate that SIMNE generates more accurate source estimation than a traditional minimum-norm estimates method and reveals the locations of spikes missed by SEEG, which would improve presurgical evaluation of the epileptogenic zone.
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Affiliation(s)
- Su Shu
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Shen Luo
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Miao Cao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Ke Xu
- Department of Neurosurgery, Sanbo Brain Hospital of Capital Medical University, Beijing 100093, China
| | - Lang Qin
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Li Zheng
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Jing Xu
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Laboratory of Applied Brain and Cognitive Sciences, College of International Business, Shanghai International Studies University, Shanghai 201620, China
| | - Xiongfei Wang
- Department of Neurosurgery, Sanbo Brain Hospital of Capital Medical University, Beijing 100093, China
| | - Jia-Hong Gao
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; McGovern Institute for Brain Research, Peking University, Beijing 100871, China; National Biomedical Imaging Center, Peking University, Beijing 100871, China.
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10
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Chvojka J, Kudlacek J, Chang WC, Novak O, Tomaska F, Otahal J, Jefferys JGR, Jiruska P. The role of interictal discharges in ictogenesis - A dynamical perspective. Epilepsy Behav 2021; 121:106591. [PMID: 31806490 DOI: 10.1016/j.yebeh.2019.106591] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 09/23/2019] [Accepted: 09/23/2019] [Indexed: 10/25/2022]
Abstract
Interictal epileptiform discharge (IED) is a traditional hallmark of epileptic tissue that is generated by the synchronous activity of a population of neurons. Interictal epileptiform discharges represent a heterogeneous group of pathological activities that differ in shape, duration, spatiotemporal distribution, underlying cellular and network mechanisms, and their relationship to seizure genesis. The exact role of IEDs in epilepsy is still not well understood, and there remains a persistent dichotomy about the impact on IEDs on seizures. Proseizure, antiseizure, and no impact on ictogenesis have all been described in previous studies. In this article, we review the existing knowledge on the role of interictal discharges in seizure genesis, and we discuss how dynamical approaches to ictogenesis can explain the existing dichotomy about the multifaceted role of IEDs in ictogenesis. This article is part of the Special Issue "NEWroscience 2018".
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Affiliation(s)
- Jan Chvojka
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic; Department of Developmental Epileptology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic; Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Jan Kudlacek
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic; Department of Developmental Epileptology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic; Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Wei-Chih Chang
- Faculty of Veterinary Medicine and Neuroscience Center, University of Helsinki, Helsinki 00014, Finland
| | - Ondrej Novak
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Filip Tomaska
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Jakub Otahal
- Department of Developmental Epileptology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
| | - John G R Jefferys
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic; Department of Pharmacology, University of Oxford, Mansfield Road, Oxford OX1 3QT, United Kingdom
| | - Premysl Jiruska
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic; Department of Developmental Epileptology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic.
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11
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Westin K, Pfeiffer C, Andersen LM, Ruffieux S, Cooray G, Kalaboukhov A, Winkler D, Ingvar M, Schneiderman J, Lundqvist D. Detection of interictal epileptiform discharges: A comparison of on-scalp MEG and conventional MEG measurements. Clin Neurophysiol 2020; 131:1711-1720. [DOI: 10.1016/j.clinph.2020.03.041] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 03/06/2020] [Accepted: 03/30/2020] [Indexed: 10/24/2022]
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12
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Conrad EC, Tomlinson SB, Wong JN, Oechsel KF, Shinohara RT, Litt B, Davis KA, Marsh ED. Spatial distribution of interictal spikes fluctuates over time and localizes seizure onset. Brain 2020; 143:554-569. [PMID: 31860064 DOI: 10.1093/brain/awz386] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 10/15/2019] [Accepted: 10/25/2019] [Indexed: 12/21/2022] Open
Abstract
The location of interictal spikes is used to aid surgical planning in patients with medically refractory epilepsy; however, their spatial and temporal dynamics are poorly understood. In this study, we analysed the spatial distribution of interictal spikes over time in 20 adult and paediatric patients (12 females, mean age = 34.5 years, range = 5-58) who underwent intracranial EEG evaluation for epilepsy surgery. Interictal spikes were detected in the 24 h surrounding each seizure and spikes were clustered based on spatial location. The temporal dynamics of spike spatial distribution were calculated for each patient and the effects of sleep and seizures on these dynamics were evaluated. Finally, spike location was assessed in relation to seizure onset location. We found that spike spatial distribution fluctuated significantly over time in 14/20 patients (with a significant aggregate effect across patients, Fisher's method: P < 0.001). A median of 12 sequential hours were required to capture 80% of the variability in spike spatial distribution. Sleep and postictal state affected the spike spatial distribution in 8/20 and 4/20 patients, respectively, with a significant aggregate effect (Fisher's method: P < 0.001 for each). There was no evidence of pre-ictal change in the spike spatial distribution for any patient or in aggregate (Fisher's method: P = 0.99). The electrode with the highest spike frequency and the electrode with the largest area of downstream spike propagation both localized the seizure onset zone better than predicted by chance (Wilcoxon signed-rank test: P = 0.005 and P = 0.002, respectively). In conclusion, spikes localize seizure onset. However, temporal fluctuations in spike spatial distribution, particularly in relation to sleep and post-ictal state, can confound localization. An adequate duration of intracranial recording-ideally at least 12 sequential hours-capturing both sleep and wakefulness should be obtained to sufficiently sample the interictal network.
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Affiliation(s)
- Erin C Conrad
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Samuel B Tomlinson
- Division of Child Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.,School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, NY, USA
| | - Jeremy N Wong
- Division of Child Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kelly F Oechsel
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics and Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Brian Litt
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Kathryn A Davis
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Eric D Marsh
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.,Division of Child Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
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13
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Klimes P, Cimbalnik J, Brazdil M, Hall J, Dubeau F, Gotman J, Frauscher B. NREM sleep is the state of vigilance that best identifies the epileptogenic zone in the interictal electroencephalogram. Epilepsia 2019; 60:2404-2415. [PMID: 31705527 DOI: 10.1111/epi.16377] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 10/09/2019] [Accepted: 10/09/2019] [Indexed: 01/26/2023]
Abstract
OBJECTIVE Interictal epileptiform anomalies such as epileptiform discharges or high-frequency oscillations show marked variations across the sleep-wake cycle. This study investigates which state of vigilance is the best to localize the epileptogenic zone (EZ) in interictal intracranial electroencephalography (EEG). METHODS Thirty patients with drug-resistant epilepsy undergoing stereo-EEG (SEEG)/sleep recording and subsequent open surgery were included; 13 patients (43.3%) had good surgical outcome (Engel class I). Sleep was scored following standard criteria. Multiple features based on the interictal EEG (interictal epileptiform discharges, high-frequency oscillations, univariate and bivariate features) were used to train a support vector machine (SVM) model to classify SEEG contacts placed in the EZ. The performance of the algorithm was evaluated by the mean area under the receiver-operating characteristic (ROC) curves (AUCs) and positive predictive values (PPVs) across 10-minute sections of wake, non-rapid eye movement sleep (NREM) stages N2 and N3, REM sleep, and their combination. RESULTS Highest AUCs were achieved in NREM sleep stages N2 and N3 compared to wakefulness and REM (P < .01). There was no improvement when using a combination of all four states (P > .05); the best performing features in the combined state were selected from NREM sleep. There were differences between good (Engel I) and poor (Engel II-IV) outcomes in PPV (P < .05) and AUC (P < .01) across all states. The SVM multifeature approach outperformed spikes and high-frequency oscillations (P < .01) and resulted in results similar to those of the seizure-onset zone (SOZ; P > .05). SIGNIFICANCE Sleep improves the localization of the EZ with best identification obtained in NREM sleep stages N2 and N3. Results based on the multifeature classification in 10 minutes of NREM sleep were not different from the results achieved by the SOZ based on 12.7 days of seizure monitoring. This finding might ultimately result in a more time-efficient intracranial presurgical investigation of focal epilepsy.
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Affiliation(s)
- Petr Klimes
- Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada.,Institute of Scientific Instruments, The Czech Academy of Sciences, Brno, Czech Republic
| | - Jan Cimbalnik
- International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Milan Brazdil
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital, Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Behavioral and Social Neuroscience Research Group, CEITEC Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Jeffery Hall
- Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada
| | - François Dubeau
- Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada
| | - Jean Gotman
- Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montréal, Quebec, Canada
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14
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Novak V, Maulisova A, Jezdik P, Benova B, Belohlavkova A, Liby P, Tichy M, Krsek P. Generalized quasiperiodic epileptiform activity in sleep is associated with cognitive impairment in children with drug-resistant focal lesional epilepsy. Epilepsia 2019; 60:2263-2276. [PMID: 31612465 DOI: 10.1111/epi.16362] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Revised: 09/16/2019] [Accepted: 09/16/2019] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To evaluate the impact of generalized quasiperiodic epileptiform discharges ("hurdles") observed in non-rapid eye movement (NREM) sleep on cognitive function in children with intractable focal epilepsy. "Hurdles" pattern does not meet the criteria of the electrical status epilepticus in slow-wave sleep (ESES). METHODS In a retrospective analysis, 24 patients with "hurdles" and their 24 peers matched for demographic and epilepsy-related variables were compared in terms of neuropsychological domains and electroencephalography (EEG)-derived quantifiers. Both "hurdles" and controls were children between 2 and 19 years of age who had intractable focal epilepsy evaluated as candidates of resective epilepsy surgery. RESULTS Full-scale intelligence quotient/developmental quotient (FSIQ/DQ) (P = .002) and visuoconstructional skills (P = .004) were significantly lower in children with "hurdles" compared to controls. Patients with "hurdles" presented with higher interictal spike indexes in sleep (P < .001, median difference -0.9, 95% confidence interval [CI] -1.4, -0.6) and wakefulness (P < .001, median difference -0.3, 95% CI -0.5, -1). Relative time of sleep spindles in NREM sleep was significantly reduced (P < .001, median difference 0.1, 95% CI 0.0, 0.1) in the "hurdles" group. The time proportion of sleep spindles represented a significant positive (P = .008) and spike index of generalized spikes in sleep a significant negative explanatory variable (P = .004) of FSIQ/DQ scores. The proportion of seizure-free patients 2 years after epilepsy surgery did not differ significantly between the two groups (P = .19). SIGNIFICANCE Although the "hurdles" pattern does not fulfill the criteria of ESES, it is associated with a pronounced cognitive dysfunction. Disturbed sleep structure marked by reduced sleep spindles and generalized spiking in sleep is associated with worse cognitive performance. Despite having a generalized nature, we did not find a lower probability of postsurgical seizure freedom in patients with "hurdles" pattern.
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Affiliation(s)
- Vilem Novak
- Department of Paediatric Neurology, Ostrava Faculty Hospital, Ostrava, Czech Republic.,Second Faculty of Medicine, Charles University Prague, Prague, Czech Republic
| | - Alice Maulisova
- Department of Clinical Psychology, Motol University Hospital, Prague, Czech Republic
| | - Petr Jezdik
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University of Prague, Prague, Czech Republic
| | - Barbora Benova
- Second Faculty of Medicine, Charles University Prague, Prague, Czech Republic.,Department of Paediatric Neurology, Motol University Hospital, Prague, Czech Republic
| | - Anezka Belohlavkova
- Second Faculty of Medicine, Charles University Prague, Prague, Czech Republic.,Department of Paediatric Neurology, Motol University Hospital, Prague, Czech Republic
| | - Petr Liby
- Department of Neurosurgery, 2nd Faculty of Medicine, Motol University Hospital, Charles University, Prague 5, Czech Republic
| | - Michal Tichy
- Department of Neurosurgery, 2nd Faculty of Medicine, Motol University Hospital, Charles University, Prague 5, Czech Republic
| | - Pavel Krsek
- Second Faculty of Medicine, Charles University Prague, Prague, Czech Republic.,Department of Paediatric Neurology, Motol University Hospital, Prague, Czech Republic
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15
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Diamond JM, Chapeton JI, Theodore WH, Inati SK, Zaghloul KA. The seizure onset zone drives state-dependent epileptiform activity in susceptible brain regions. Clin Neurophysiol 2019; 130:1628-1641. [PMID: 31325676 DOI: 10.1016/j.clinph.2019.05.032] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 04/05/2019] [Accepted: 05/14/2019] [Indexed: 01/14/2023]
Abstract
OBJECTIVE Due to variability in the patterns of propagation of interictal epileptiform discharges (IEDs), qualitative definition of the irritative zone has been challenging. Here, we introduce a quantitative approach toward exploration of the dynamics of IED propagation within the irritative zone. METHODS We examined intracranial EEG (iEEG) in nine participants undergoing invasive monitoring for seizure localization. We used an automated IED detector and a community detection algorithm to identify populations of electrodes exhibiting IED activity that co-occur in time, and to group these electrodes into communities. RESULTS Within our algorithmically-identified communities, IED activity in the seizure onset zone (SOZ) tended to lead IED activity in other functionally coupled brain regions. The tendency of pathological activity to arise in the SOZ, and to spread to non-SOZ tissues, was greater in the asleep state. CONCLUSIONS IED activity, and, by extension, the variability observed between the asleep and awake states, is propagated from a core seizure focus to nearby less pathological brain regions. SIGNIFICANCE Using an unsupervised, computational approach, we show that the spread of IED activity through the epilepsy network varies with physiologic state.
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Affiliation(s)
- Joshua M Diamond
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, United States
| | - Julio I Chapeton
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, United States
| | - William H Theodore
- Clinical Epilepsy Section, NINDS, National Institutes of Health, Bethesda, MD 20892, United States
| | - Sara K Inati
- Epilepsy Service and EEG Section, NINDS, National Institutes of Health, Bethesda, MD 20892, United States.
| | - Kareem A Zaghloul
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, United States.
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16
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Tomlinson SB, Wong JN, Conrad EC, Kennedy BC, Marsh ED. Reproducibility of interictal spike propagation in children with refractory epilepsy. Epilepsia 2019; 60:898-910. [PMID: 31006860 PMCID: PMC6488404 DOI: 10.1111/epi.14720] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Revised: 02/11/2019] [Accepted: 03/13/2019] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Interictal spikes are a characteristic feature of invasive electroencephalography (EEG) recordings in children with refractory epilepsy. Spikes frequently co-occur across multiple brain regions with discernable latencies, suggesting that spikes can propagate through distributed neural networks. The purpose of this study was to examine the long-term reproducibility of spike propagation patterns over hours to days of interictal recording. METHODS Twelve children (mean age 13.1 years) were retrospectively studied. A mean ± standard deviation (SD) of 47.2 ± 40.1 hours of interictal EEG recordings were examined per patient (range 17.5-166.5 hours). Interictal recordings were divided into 30-minute segments. Networks were extracted based on the frequency of spike coactivation between pairs of electrodes. For each 30-minute segment, electrodes were assigned a "Degree Preference (DP)" based on the tendency to appear upstream or downstream within propagation sequences. The consistency of DPs across segments ("DP-Stability") was quantified using the Spearman rank correlation. RESULTS Regions exhibited highly stable preferences to appear upstream, intermediate, or downstream in spike propagation sequences. Across networks, the mean ± SD DP-Stability was 0.88 ± 0.07, indicating that propagation patterns observed in 30-minute segments were representative of the patterns observed in the full interictal window. At the group level, regions involved in seizure generation appeared more upstream in spike propagation sequences. SIGNIFICANCE Interictal spike propagation is a highly reproducible output of epileptic networks. These findings shed new light on the spatiotemporal dynamics that may constrain the network mechanisms of refractory epilepsy.
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Affiliation(s)
- Samuel B. Tomlinson
- Division of Neurosurgery, Children’s Hospital of Philadelphia, Philadelphia, PA
- School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, NY
| | - Jeremy N. Wong
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Erin C. Conrad
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Benjamin C. Kennedy
- Division of Neurosurgery, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Eric D. Marsh
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA
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