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Padmasola GP, Friscourt F, Rigoni I, Vulliémoz S, Schaller K, Michel CM, Sheybani L, Quairiaux C. Involvement of the contralateral hippocampus in ictal-like but not interictal epileptic activities in the kainate mouse model of temporal lobe epilepsy. Epilepsia 2024. [PMID: 38758110 DOI: 10.1111/epi.17970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 03/19/2024] [Accepted: 03/19/2024] [Indexed: 05/18/2024]
Abstract
OBJECTIVE Animal and human studies have shown that the seizure-generating region is vastly dependent on distant neuronal hubs that can decrease duration and propagation of ongoing seizures. However, we still lack a comprehensive understanding of the impact of distant brain areas on specific interictal and ictal epileptic activities (e.g., isolated spikes, spike trains, seizures). Such knowledge is critically needed, because all kinds of epileptic activities are not equivalent in terms of clinical expression and impact on the progression of the disease. METHODS We used surface high-density electroencephalography and multisite intracortical recordings, combined with pharmacological silencing of specific brain regions in the well-known kainate mouse model of temporal lobe epilepsy. We tested the impact of selective regional silencing on the generation of epileptic activities within a continuum ranging from very transient to more sustained and long-lasting discharges reminiscent of seizures. RESULTS Silencing the contralateral hippocampus completely suppresses sustained ictal activities in the focus, as efficiently as silencing the focus itself, but whereas focus silencing abolishes all focus activities, contralateral silencing fails to control transient spikes. In parallel, we observed that sustained focus epileptiform discharges in the focus are preceded by contralateral firing and more strongly phase-locked to bihippocampal delta/theta oscillations than transient spiking activities, reinforcing the presumed dominant role of the contralateral hippocampus in promoting long-lasting, but not transient, epileptic activities. SIGNIFICANCE Altogether, our work provides suggestive evidence that the contralateral hippocampus is necessary for the interictal to ictal state transition and proposes that crosstalk between contralateral neuronal activity and ipsilateral delta/theta oscillation could be a candidate mechanism underlying the progression from short- to long-lasting epileptic activities.
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Affiliation(s)
- Guru Prasad Padmasola
- Functional Brain Mapping Lab, Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland
| | - Fabien Friscourt
- Functional Brain Mapping Lab, Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland
- Neurosurgery Clinic, Department of Clinical Neuroscience, University Hospital Geneva, Geneva, Switzerland
| | - Isotta Rigoni
- EEG and Epilepsy Unit, Department of Neuroscience, University Hospital and Faculty of Medicine of Geneva, University of Geneva, Geneva, Switzerland
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, Department of Neuroscience, University Hospital and Faculty of Medicine of Geneva, University of Geneva, Geneva, Switzerland
| | - Karl Schaller
- Neurosurgery Clinic, Department of Clinical Neuroscience, University Hospital Geneva, Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Lab, Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland
| | - Laurent Sheybani
- Neurology Clinic, Department of Clinical Neuroscience, University Hospital Geneva, Geneva, Switzerland
- Department of Clinical and Experimental Epilepsy, Queen's Square Institute of Neurology, London, UK
| | - Charles Quairiaux
- Functional Brain Mapping Lab, Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland
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Stern MA, Cole ER, Gross RE, Berglund K. Seizure event detection using intravital two-photon calcium imaging data. Neurophotonics 2024; 11:024202. [PMID: 38274784 PMCID: PMC10809036 DOI: 10.1117/1.nph.11.2.024202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 12/20/2023] [Accepted: 12/26/2023] [Indexed: 01/27/2024]
Abstract
Significance Intravital cellular calcium imaging has emerged as a powerful tool to investigate how different types of neurons interact at the microcircuit level to produce seizure activity, with newfound potential to understand epilepsy. Although many methods exist to measure seizure-related activity in traditional electrophysiology, few yet exist for calcium imaging. Aim To demonstrate an automated algorithmic framework to detect seizure-related events using calcium imaging-including the detection of pre-ictal spike events, propagation of the seizure wavefront, and terminal spreading waves for both population-level activity and that of individual cells. Approach We developed an algorithm for precise recruitment detection of population and individual cells during seizure-associated events, which broadly leverages averaged population activity and high-magnitude slope features to detect single-cell pre-ictal spike and seizure recruitment. We applied this method to data recorded using awake in vivo two-photon calcium imaging during pentylenetetrazol-induced seizures in mice. Results We demonstrate that our detected recruitment times are concordant with visually identified labels provided by an expert reviewer and are sufficiently accurate to model the spatiotemporal progression of seizure-associated traveling waves. Conclusions Our algorithm enables accurate cell recruitment detection and will serve as a useful tool for researchers investigating seizure dynamics using calcium imaging.
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Affiliation(s)
- Matthew A. Stern
- Emory University School of Medicine, Department of Neurosurgery, Atlanta, Georgia, United States
| | - Eric R. Cole
- Emory University School of Medicine, Department of Neurosurgery, Atlanta, Georgia, United States
- Emory University, Georgia Institute of Technology, Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Robert E. Gross
- Emory University School of Medicine, Department of Neurosurgery, Atlanta, Georgia, United States
- Emory University, Georgia Institute of Technology, Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Ken Berglund
- Emory University School of Medicine, Department of Neurosurgery, Atlanta, Georgia, United States
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Karimi-Rouzbahani H, McGonigal A. Generalisability of epileptiform patterns across time and patients. Sci Rep 2024; 14:6293. [PMID: 38491096 PMCID: PMC10942983 DOI: 10.1038/s41598-024-56990-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Accepted: 03/13/2024] [Indexed: 03/18/2024] Open
Abstract
The complexity of localising the epileptogenic zone (EZ) contributes to surgical resection failures in achieving seizure freedom. The distinct patterns of epileptiform activity during interictal and ictal phases, varying across patients, often lead to suboptimal localisation using electroencephalography (EEG) features. We posed two key questions: whether neural signals reflecting epileptogenicity generalise from interictal to ictal time windows within each patient, and whether epileptiform patterns generalise across patients. Utilising an intracranial EEG dataset from 55 patients, we extracted a large battery of simple to complex features from stereo-EEG (SEEG) and electrocorticographic (ECoG) neural signals during interictal and ictal windows. Our features (n = 34) quantified many aspects of the signals including statistical moments, complexities, frequency-domain and cross-channel network attributes. Decision tree classifiers were then trained and tested on distinct time windows and patients to evaluate the generalisability of epileptogenic patterns across time and patients, respectively. Evidence strongly supported generalisability from interictal to ictal time windows across patients, particularly in signal power and high-frequency network-based features. Consistent patterns of epileptogenicity were observed across time windows within most patients, and signal features of epileptogenic regions generalised across patients, with higher generalisability in the ictal window. Signal complexity features were particularly contributory in cross-patient generalisation across patients. These findings offer insights into generalisable features of epileptic neural activity across time and patients, with implications for future automated approaches to supplement other EZ localisation methods.
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Affiliation(s)
- Hamid Karimi-Rouzbahani
- Neurosciences Centre, Mater Hospital, South Brisbane, 4101, Australia.
- Mater Research Institute, University of Queensland, South Brisbane, 4101, Australia.
- Queensland Brain Institute, University of Queensland, St Lucia, 4072, Australia.
| | - Aileen McGonigal
- Neurosciences Centre, Mater Hospital, South Brisbane, 4101, Australia
- Mater Research Institute, University of Queensland, South Brisbane, 4101, Australia
- Queensland Brain Institute, University of Queensland, St Lucia, 4072, Australia
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Mohan UR, Zhang H, Ermentrout B, Jacobs J. The direction of theta and alpha travelling waves modulates human memory processing. Nat Hum Behav 2024:10.1038/s41562-024-01838-3. [PMID: 38459263 DOI: 10.1038/s41562-024-01838-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 01/24/2024] [Indexed: 03/10/2024]
Abstract
To support a range of behaviours, the brain must flexibly coordinate neural activity across widespread brain regions. One potential mechanism for this coordination is a travelling wave, in which a neural oscillation propagates across the brain while organizing the order and timing of activity across regions. Although travelling waves are present across the brain in various species, their potential functional relevance has remained unknown. Here, using rare direct human brain recordings, we demonstrate a distinct functional role for travelling waves of theta- and alpha-band (2-13 Hz) oscillations in the cortex. Travelling waves propagate in different directions during separate cognitive processes. In episodic memory, travelling waves tended to propagate in a posterior-to-anterior direction during successful memory encoding and in an anterior-to-posterior direction during recall. Because travelling waves of oscillations correspond to local neuronal spiking, these patterns indicate that rhythmic pulses of activity move across the brain in different directions for separate behaviours. More broadly, our results suggest a fundamental role for travelling waves and oscillations in dynamically coordinating neural connectivity, by flexibly organizing the timing and directionality of network interactions across the cortex to support cognition and behaviour.
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Affiliation(s)
- Uma R Mohan
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD, USA
| | | | - Bard Ermentrout
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University, New York City, NY, USA.
- Department of Neurological Surgery, Columbia University, New York City, NY, USA.
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Wang S, Wu M, Wu S, Lin F, Ji X, Yan J. A polysomnographic study of slow-wave sleep loss in elderly patients with epilepsy. Heliyon 2024; 10:e25904. [PMID: 38379992 PMCID: PMC10877289 DOI: 10.1016/j.heliyon.2024.e25904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 01/02/2024] [Accepted: 02/05/2024] [Indexed: 02/22/2024] Open
Abstract
Objective The primary objective is to explore what causes slow-wave sleep loss in elderly patients with epilepsy. The secondary objective is to identify the PSG characteristics in elderly patients with epilepsy. The clinical demographics, sleep architecture, sleep-related events, and interictal epileptiform discharges are to be evaluated in the objectives. Methods The video electroencephalography (VEEG) and polysomnogram (PSG) data from 44 elderly patients with epilepsy and 52 elderly patients with sleep disorders but without definite central nervous system diseases were analysed. This was a case-control study. The differences in the PSG sleep architecture parameters (total sleep time (TST), sleep efficiency, wake after sleep onset, etc.) and sleep-related events (apnea hypopnea index, oxygen desaturation index (ODI), periodic limb movement index, etc.) between the epilepsy and control groups. As Additionally, these parameters were assessed within the elderly patients with epilepsy, comparing the slow-wave sleep existence and slow-wave sleep loss groups, using VEEG and PSG. Results The epileptic group exhibited significantly lower TST (343.477 ± 96.3046min vs 389.115 ± 61.5727min, p < 0.05), rapid eye movement (%) (13.011 ± 7.5384 vs 16.992 ± 6.7025, p < 0.05), non-rapid eye movement stage 3 (%) (1.35[0,7.225] vs 3.65[0.425,13.75], p < 0.05), and sleep efficiency (%) (69.482 ± 14.1771% vs 77.242 ± 10.6171%, p < 0.05). Conversely, the ODI (25.6[9.825,51.775] events/hour vs 16.85[5.3,30.425] events/hour, p < 0.05) and spontaneous arousal index (4.0455[2.1805,6.9609] events/hour vs 2.9709[1.4747,5.0554] events/hour, p < 0.05) were significantly higher in elderly patients with epilepsy. The prevalence of obstructive sleep apnea-hypopnea syndrome (OSAHS) was significantly higher in the slow-wave sleep loss group than in the slow-wave sleep existence group (100% vs 77.8%, p < 0.05). The incidence of slow-wave sleep loss was lower in patients with epilepsy aged between 75 and 85 years compared to those aged between 65 and 75 years. Conclusion Elderly patients with epilepsy exhibit higher levels of ODI and spontaneous arousal index. Our findings indicate that OSAHS could be a contributing factor to slow-wave sleep loss in this population. The incidence of slow-wave sleep loss was lower in patients aged above 75 years among elderly patients with epilepsy.
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Affiliation(s)
| | | | - Sangru Wu
- Department of Neurology and Sleep Medical Center, Fujian Provincial Governmental Hospital, Fuzhou, China
| | - Fang Lin
- Department of Neurology and Sleep Medical Center, Fujian Provincial Governmental Hospital, Fuzhou, China
| | - Xiaolin Ji
- Department of Neurology and Sleep Medical Center, Fujian Provincial Governmental Hospital, Fuzhou, China
| | - Jinzhu Yan
- Department of Neurology and Sleep Medical Center, Fujian Provincial Governmental Hospital, Fuzhou, China
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Ye H, Ye L, Hu L, Yang Y, Ge Y, Chen R, Wang S, Jin B, Ming W, Wang Z, Xu S, Xu C, Wang Y, Ding Y, Zhu J, Ding M, Chen Z, Wang S, Chen C. Widespread slow oscillations support interictal epileptiform discharge networks in focal epilepsy. Neurobiol Dis 2024; 191:106409. [PMID: 38218457 DOI: 10.1016/j.nbd.2024.106409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 01/01/2024] [Accepted: 01/09/2024] [Indexed: 01/15/2024] Open
Abstract
Interictal epileptiform discharges (IEDs) often co-occur across spatially-separated cortical regions, forming IED networks. However, the factors prompting IED propagation remain unelucidated. We hypothesized that slow oscillations (SOs) might facilitate IED propagation. Here, the amplitude and phase synchronization of SOs preceding propagating and non-propagating IEDs were compared in 22 patients with focal epilepsy undergoing intracranial electroencephalography (EEG) evaluation. Intracranial channels were categorized into the irritative zone (IZ) and normal zone (NOZ) regarding the presence of IEDs. During wakefulness, we found that pre-IED SOs within the IZ exhibited higher amplitudes for propagating IEDs than non-propagating IEDs (delta band: p = 0.001, theta band: p < 0.001). This increase in SOs was also concurrently observed in the NOZ (delta band: p = 0.04). Similarly, the inter-channel phase synchronization of SOs prior to propagating IEDs was higher than those preceding non-propagating IEDs in the IZ (delta band: p = 0.04). Through sliding window analysis, we observed that SOs preceding propagating IEDs progressively increased in amplitude and phase synchronization, while those preceding non-propagating IEDs remained relatively stable. Significant differences in amplitude occurred approximately 1150 ms before IEDs. During non-rapid eye movement (NREM) sleep, SOs on scalp recordings also showed higher amplitudes before intracranial propagating IEDs than before non-propagating IEDs (delta band: p = 0.006). Furthermore, the analysis of IED density around sleep SOs revealed that only high-amplitude sleep SOs demonstrated correlation with IED propagation. Overall, our study highlights that transient but widely distributed SOs are associated with IED propagation as well as generation in focal epilepsy during sleep and wakefulness, providing new insight into the EEG substrate supporting IED networks.
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Affiliation(s)
- Hongyi Ye
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Nanhu Brain-computer Interface Institute, Hangzhou, China
| | - Lingqi Ye
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lingli Hu
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuyu Yang
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yi Ge
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ruotong Chen
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shan Wang
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Bo Jin
- Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wenjie Ming
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhongjin Wang
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Sha Xu
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Cenglin Xu
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yi Wang
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yao Ding
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Junming Zhu
- Department of Neurosurgery and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Meiping Ding
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhong Chen
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
| | - Shuang Wang
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Nanhu Brain-computer Interface Institute, Hangzhou, China.
| | - Cong Chen
- Department of Neurology and Epilepsy Center, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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Abdi-Sargezeh B, Shirani S, Sanei S, Took CC, Geman O, Alarcon G, Valentin A. A review of signal processing and machine learning techniques for interictal epileptiform discharge detection. Comput Biol Med 2024; 168:107782. [PMID: 38070202 DOI: 10.1016/j.compbiomed.2023.107782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 11/15/2023] [Accepted: 11/28/2023] [Indexed: 01/10/2024]
Abstract
Brain interictal epileptiform discharges (IEDs), as one of the hallmarks of epileptic brain, are transient events captured by electroencephalogram (EEG). IEDs are generated by seizure networks, and they occur between seizures (interictal periods). The development of a robust method for IED detection could be highly informative for clinical treatment procedures and epileptic patient management. Since 1972, different machine learning techniques, from template matching to deep learning, have been developed to automatically detect IEDs from scalp EEG (scEEG) and intracranial EEG (iEEG). While the scEEG signals suffer from low information details and high attenuation of IEDs due to the high skull electrical impedance, the iEEG signals recorded using implanted electrodes enjoy higher details and are more suitable for identifying the IEDs. In this review paper, we group IED detection techniques into six categories: (1) template matching, (2) feature representation (mimetic, time-frequency, and nonlinear features), (3) matrix decomposition, (4) tensor factorization, (5) neural networks, and (6) estimation of the iEEG from the concurrent scEEG followed by detection and classification. The methods are compared quantitatively (e.g., in terms of accuracy, sensitivity, and specificity), and their general advantages and limitations are described. Finally, current limitations and possible future research paths related to this field are mentioned.
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Affiliation(s)
- Bahman Abdi-Sargezeh
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; School of Science and Technology, Nottingham Trent University, Nottingham, UK.
| | - Sepehr Shirani
- School of Science and Technology, Nottingham Trent University, Nottingham, UK
| | - Saeid Sanei
- School of Science and Technology, Nottingham Trent University, Nottingham, UK
| | - Clive Cheong Took
- Department of Electronic Engineering, Royal Holloway, University of London, London, UK
| | - Oana Geman
- Computer, Electronics and Automation Department, University Stefan cel Mare, Suceava, Romania
| | - Gonzalo Alarcon
- Department of Clinical Neurophysiology, Royal Manchester Children's Hospital, Manchester, UK
| | - Antonio Valentin
- Department of Clinical Neuroscience, King's College London, London, UK
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Gerstl JVE, Kiseleva A, Imbach L, Sarnthein J, Fedele T. High frequency oscillations in relation to interictal spikes in predicting postsurgical seizure freedom. Sci Rep 2023; 13:21313. [PMID: 38042925 PMCID: PMC10693609 DOI: 10.1038/s41598-023-48764-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 11/30/2023] [Indexed: 12/04/2023] Open
Abstract
We evaluate whether interictal spikes, epileptiform HFOs and their co-occurrence (Spike + HFO) were included in the resection area with respect to seizure outcome. We also characterise the relationship between high frequency oscillations (HFOs) and propagating spikes. We analysed intracranial EEG of 20 patients that underwent resective epilepsy surgery. The co-occurrence of ripples and fast ripples was considered an HFO event; the co-occurrence of an interictal spike and HFO was considered a Spike + HFO event. HFO distribution and spike onset were compared in cases of spike propagation. Accuracy in predicting seizure outcome was 85% for HFO, 60% for Spikes, and 79% for Spike + HFO. Sensitivity was 57% for HFO, 71% for Spikes and 67% for Spikes + HFO. Specificity was 100% for HFO, 54% for Spikes and 85% for Spikes + HFO. In 2/2 patients with spike propagation, the spike onset included the HFO area. Combining interictal spikes with HFO had comparable accuracy to HFO. In patients with propagating spikes, HFO rate was maximal at the onset of spike propagation.
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Affiliation(s)
- Jakob V E Gerstl
- University College London Medical School, London, UK
- Department of Neurosurgery, University Hospital and University of Zurich, Zurich, Switzerland
| | - Alina Kiseleva
- Institute for Cognitive Neuroscience, HSE University, Myasnitskaya Ulitsa, 20, Moscow, Russian Federation, 101000
| | - Lukas Imbach
- Swiss Epilepsy Center, Klinik Lengg, Zurich, Switzerland
| | - Johannes Sarnthein
- Department of Neurosurgery, University Hospital and University of Zurich, Zurich, Switzerland
| | - Tommaso Fedele
- Department of Neurosurgery, University Hospital and University of Zurich, Zurich, Switzerland.
- Institute for Cognitive Neuroscience, HSE University, Myasnitskaya Ulitsa, 20, Moscow, Russian Federation, 101000.
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Ramantani G, Westover MB, Gliske S, Sarnthein J, Sarma S, Wang Y, Baud MO, Stacey WC, Conrad EC. Passive and active markers of cortical excitability in epilepsy. Epilepsia 2023; 64 Suppl 3:S25-S36. [PMID: 36897228 PMCID: PMC10512778 DOI: 10.1111/epi.17578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/07/2023] [Accepted: 03/07/2023] [Indexed: 03/11/2023]
Abstract
Electroencephalography (EEG) has been the primary diagnostic tool in clinical epilepsy for nearly a century. Its review is performed using qualitative clinical methods that have changed little over time. However, the intersection of higher resolution digital EEG and analytical tools developed in the past decade invites a re-exploration of relevant methodology. In addition to the established spatial and temporal markers of spikes and high-frequency oscillations, novel markers involving advanced postprocessing and active probing of the interictal EEG are gaining ground. This review provides an overview of the EEG-based passive and active markers of cortical excitability in epilepsy and of the techniques developed to facilitate their identification. Several different emerging tools are discussed in the context of specific EEG applications and the barriers we must overcome to translate these tools into clinical practice.
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Affiliation(s)
- Georgia Ramantani
- Department of Neuropediatrics and Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
- University of Zurich, Zurich, Switzerland
| | - M Brandon Westover
- Department of Neurology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Department of Data Science, Massachusetts General Hospital McCance Center for Brain Health, Boston, Massachusetts, USA
- Research Affiliate Faculty, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Research Affiliate Faculty, Broad Institute, Cambridge, Massachusetts, USA
| | - Stephen Gliske
- Department of Neurosurgery, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Johannes Sarnthein
- Department of Neurosurgery, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - Sridevi Sarma
- Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Yujiang Wang
- Interdisciplinary Computing and Complex BioSystems, School of Computing Science, Newcastle University, Newcastle Upon Tyne, UK
| | - Maxime O Baud
- Sleep-Wake-Epilepsy Center, NeuroTec, Center for Experimental Neurology, Department of Neurology, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland
| | - William C Stacey
- Department of Neurology, BioInterfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
- Department of Biomedical Engineering, BioInterfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
- Division of Neurology, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA
| | - Erin C Conrad
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Neurology, Penn Epilepsy Center, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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11
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Bernard C, Frauscher B, Gelinas J, Timofeev I. Sleep, oscillations, and epilepsy. Epilepsia 2023; 64 Suppl 3:S3-S12. [PMID: 37226640 PMCID: PMC10674035 DOI: 10.1111/epi.17664] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 04/27/2023] [Accepted: 05/23/2023] [Indexed: 05/26/2023]
Abstract
Sleep and wake are defined through physiological and behavioral criteria and can be typically separated into non-rapid eye movement (NREM) sleep stages N1, N2, and N3, rapid eye movement (REM) sleep, and wake. Sleep and wake states are not homogenous in time. Their properties vary during the night and day cycle. Given that brain activity changes as a function of NREM, REM, and wake during the night and day cycle, are seizures more likely to occur during NREM, REM, or wake at a specific time? More generally, what is the relationship between sleep-wake cycles and epilepsy? We will review specific examples from clinical data and results from experimental models, focusing on the diversity and heterogeneity of these relationships. We will use a top-down approach, starting with the general architecture of sleep, followed by oscillatory activities, and ending with ionic correlates selected for illustrative purposes, with respect to seizures and interictal spikes. The picture that emerges is that of complexity; sleep disruption and pathological epileptic activities emerge from reorganized circuits. That different circuit alterations can occur across patients and models may explain why sleep alterations and the timing of seizures during the sleep-wake cycle are patient-specific.
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Affiliation(s)
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Jennifer Gelinas
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Igor Timofeev
- Faculté de Médecine, Département de Psychiatrie et de Neurosciences, Centre de Recherche CERVO, Université Laval, Québec, QC G1J2G3, Canada
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12
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Shamas M, Yeh HJ, Fried I, Engel J, Staba RJ. High-rate leading spikes in propagating spike sequences predict seizure outcome in surgical patients with temporal lobe epilepsy. Brain Commun 2023; 5:fcad289. [PMID: 37953846 PMCID: PMC10636565 DOI: 10.1093/braincomms/fcad289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 08/14/2023] [Accepted: 10/23/2023] [Indexed: 11/14/2023] Open
Abstract
Inter-ictal spikes aid in the diagnosis of epilepsy and in planning surgery of medication-resistant epilepsy. However, the localizing information from spikes can be unreliable because spikes can propagate, and the burden of spikes, often assessed as a rate, does not always correlate with the seizure onset zone or seizure outcome. Recent work indicates identifying where spikes regularly emerge and spread could localize the seizure network. Thus, the current study sought to better understand where and how rates of single and coupled spikes, and especially brain regions with high-rate and leading spike of a propagating sequence, informs the extent of the seizure network. In 37 patients with medication-resistant temporal lobe seizures, who had surgery to treat their seizure disorder, an algorithm detected spikes in the pre-surgical depth inter-ictal EEG. A separate algorithm detected spike propagation sequences and identified the location of leading and downstream spikes in each sequence. We analysed the rate and power of single spikes on each electrode and coupled spikes between pairs of electrodes, and the proportion of sites with high-rate, leading spikes in relation to the seizure onset zone of patients seizure free (n = 19) and those with continuing seizures (n = 18). We found increased rates of single spikes in mesial temporal seizure onset zone (ANOVA, P < 0.001, η2 = 0.138), and increased rates of coupled spikes within, but not between, mesial-, lateral- and extra-temporal seizure onset zone of patients with continuing seizures (P < 0.001; η2 = 0.195, 0.113 and 0.102, respectively). In these same patients, there was a higher proportion of brain regions with high-rate leaders, and each sequence contained a greater number of spikes that propagated with a higher efficiency over a longer distance outside the seizure onset zone than patients seizure free (Wilcoxon, P = 0.0172). The proportion of high-rate leaders in and outside the seizure onset zone could predict seizure outcome with area under curve = 0.699, but not rates of single or coupled spikes (0.514 and 0.566). Rates of coupled spikes to a greater extent than single spikes localize the seizure onset zone and provide evidence for inter-ictal functional segregation, which could be an adaptation to avert seizures. Spike rates, however, have little value in predicting seizure outcome. High-rate spike sites leading propagation could represent sources of spikes that are important components of an efficient seizure network beyond the clinical seizure onset zone, and like the seizure onset zone these, too, need to be removed, disconnected or stimulated to increase the likelihood for seizure control.
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Affiliation(s)
- Mohamad Shamas
- David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Hsiang J Yeh
- David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Itzhak Fried
- David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Jerome Engel
- David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Richard J Staba
- David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
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13
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Stern MA, Cole ER, Gross RE, Berglund K. Seizure Event Detection Using Intravital Two-Photon Calcium Imaging Data. bioRxiv 2023:2023.09.28.558338. [PMID: 37808822 PMCID: PMC10557641 DOI: 10.1101/2023.09.28.558338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Significance Genetic cellular calcium imaging has emerged as a powerful tool to investigate how different types of neurons interact at the microcircuit level to produce seizure activity, with newfound potential to understand epilepsy. Although many methods exist to measure seizure-related activity in traditional electrophysiology, few yet exist for calcium imaging. Aim To demonstrate an automated algorithmic framework to detect seizure-related events using calcium imaging - including the detection of pre-ictal spike events, propagation of the seizure wavefront, and terminal spreading waves for both population-level activity and that of individual cells. Approach We developed an algorithm for precise recruitment detection of population and individual cells during seizure-associated events, which broadly leverages averaged population activity and high-magnitude slope features to detect single-cell pre-ictal spike and seizure recruitment. We applied this method to data recorded using awake in vivo two-photon calcium imaging during pentylenetetrazol induced seizures in mice. Results We demonstrate that our detected recruitment times are concordant with visually identified labels provided by an expert reviewer and are sufficiently accurate to model the spatiotemporal progression of seizure-associated traveling waves. Conclusions Our algorithm enables accurate cell recruitment detection and will serve as a useful tool for researchers investigating seizure dynamics using calcium imaging.
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Affiliation(s)
- Matthew A. Stern
- Authors Contributed Equally
- Emory University School of Medicine, Department of Neurosurgery, Atlanta, GA, United States
| | - Eric R. Cole
- Authors Contributed Equally
- Emory University School of Medicine, Department of Neurosurgery, Atlanta, GA, United States
- Emory University and Georgia Institute of Technology, Coulter Department of Biomedical Engineering, Atlanta, GA, United States
| | - Robert E. Gross
- Emory University School of Medicine, Department of Neurosurgery, Atlanta, GA, United States
- Emory University and Georgia Institute of Technology, Coulter Department of Biomedical Engineering, Atlanta, GA, United States
| | - Ken Berglund
- Emory University School of Medicine, Department of Neurosurgery, Atlanta, GA, United States
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14
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Weiss SA, Fried I, Engel J, Sperling MR, Wong RKS, Nir Y, Staba RJ. Fast ripples reflect increased excitability that primes epileptiform spikes. Brain Commun 2023; 5:fcad242. [PMID: 37869578 PMCID: PMC10587774 DOI: 10.1093/braincomms/fcad242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 07/08/2023] [Accepted: 09/07/2023] [Indexed: 10/24/2023] Open
Abstract
The neuronal circuit disturbances that drive inter-ictal and ictal epileptiform discharges remain elusive. Using a combination of extra-operative macro-electrode and micro-electrode inter-ictal recordings in six pre-surgical patients during non-rapid eye movement sleep, we found that, exclusively in the seizure onset zone, fast ripples (200-600 Hz), but not ripples (80-200 Hz), frequently occur <300 ms before an inter-ictal intra-cranial EEG spike with a probability exceeding chance (bootstrapping, P < 1e-5). Such fast ripple events are associated with higher spectral power (P < 1e-10) and correlated with more vigorous neuronal firing than solitary fast ripple (generalized linear mixed-effects model, P < 1e-9). During the intra-cranial EEG spike that follows a fast ripple, action potential firing is lower than during an intra-cranial EEG spike alone (generalized linear mixed-effects model, P < 0.05), reflecting an inhibitory restraint of intra-cranial EEG spike initiation. In contrast, ripples do not appear to prime epileptiform spikes. We next investigated the clinical significance of pre-spike fast ripple in a separate cohort of 23 patients implanted with stereo EEG electrodes, who underwent resections. In non-rapid eye movement sleep recordings, sites containing a high proportion of fast ripple preceding intra-cranial EEG spikes correlate with brain areas where seizures begin more than solitary fast ripple (P < 1e-5). Despite this correlation, removal of these sites does not guarantee seizure freedom. These results are consistent with the hypothesis that fast ripple preceding EEG spikes reflect an increase in local excitability that primes EEG spike discharges preferentially in the seizure onset zone and that epileptogenic brain regions are necessary, but not sufficient, for initiating inter-ictal epileptiform discharges.
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Affiliation(s)
- Shennan A Weiss
- Department of Neurology, State University of New York Downstate, Brooklyn, NY 11203, USA
- Department of Physiology and Pharmacology, State University of New York Downstate, Brooklyn, NY 11203, USA
- Department of Neurology, New York City Health + Hospitals/Kings County, Brooklyn, NY 11203, USA
| | - Itzhak Fried
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Jerome Engel
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
- Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
- Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Michael R Sperling
- Departments of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Robert K S Wong
- Department of Physiology and Pharmacology, State University of New York Downstate, Brooklyn, NY 11203, USA
| | - Yuval Nir
- Department of Physiology and Pharmacology, Sackler School of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 6997801, Israel
- Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv 6997801, Israel
- The Sieratzki-Sagol Center for Sleep Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel
| | - Richard J Staba
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
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15
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Kundu B, Charlebois CM, Nesterovich Anderson D, Peters A, Rolston JD. Chronic intracranial recordings after resection for epilepsy reveal a "running down" of epileptiform activity. Epilepsia 2023; 64:e135-e142. [PMID: 37163225 PMCID: PMC10524582 DOI: 10.1111/epi.17645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 05/06/2023] [Accepted: 05/08/2023] [Indexed: 05/11/2023]
Abstract
We describe an electrical "running down" phenomenon and also a consistent spectral change (in the aperiodic component of the power spectrum) derived from chronic interictal electrocorticography (ECoG) after surgery in a patient with drug-resistant epilepsy. These data were recorded using a closed-loop neurostimulation system that was implanted after resection. The patient has been seizure-free for 2.5 years since resection without requiring the neurostimulator to be turned on to stimulate. Concurrently, there was an exponential decrease in the number of epileptiform electrographic detections recorded by the device, particularly over the first 26 weeks, indicative of an electrical running down phenomenon as the brain adapted to an extended period of seizure freedom. We also find that the aperiodic exponent of the power spectrum gradually decreases over time. The aperiodic component of intracranial ECoG may represent a novel marker of epileptogenicity, independent of seizures.
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Affiliation(s)
- Bornali Kundu
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA
| | - Chantel M. Charlebois
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
- Scientific Computing & Imaging Institute, University of Utah, Salt Lake City, Utah, USA
| | - Daria Nesterovich Anderson
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, Utah, USA
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, Utah, USA
| | - Angela Peters
- Department of Neurology, University of Utah, Salt Lake City, Utah, USA
| | - John D. Rolston
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
- Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
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16
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Wu Y, Chen ZS. Computational models for state-dependent traveling waves in hippocampal formation. bioRxiv 2023:2023.05.19.541436. [PMID: 37292865 PMCID: PMC10245836 DOI: 10.1101/2023.05.19.541436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Hippocampal theta (4-10 Hz) oscillations have been identified as traveling waves in both rodents and humans. In freely foraging rodents, the theta traveling wave is a planar wave propagating from the dorsal to ventral hippocampus along the septotemporal axis. Motivated from experimental findings, we develop a spiking neural network of excitatory and inhibitory neurons to generate state-dependent hippocampal traveling waves to improve current mechanistic understanding of propagating waves. Model simulations demonstrate the necessary conditions for generating wave propagation and characterize the traveling wave properties with respect to model parameters, running speed and brain state of the animal. Networks with long-range inhibitory connections are more suitable than networks with long-range excitatory connections. We further generalize the spiking neural network to model traveling waves in the medial entorhinal cortex (MEC) and predict that traveling theta waves in the hippocampus and entorhinal cortex are in sink.
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17
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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18
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Weiss SA, Fried I, Engel J, Sperling MR, Wong RK, Nir Y, Staba RJ. Fast ripples reflect increased excitability that primes epileptiform spikes. medRxiv 2023:2023.03.26.23287702. [PMID: 37034609 PMCID: PMC10081394 DOI: 10.1101/2023.03.26.23287702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
The neuronal circuit disturbances that drive interictal and ictal epileptiform discharges remains elusive. Using a combination of extraoperative macro- and micro-electrode interictal recordings in six presurgical patients during non-rapid eye movement (REM) sleep we found that, exclusively in the seizure onset zone, fast ripples (FR; 200-600Hz), but not ripples (80-200 Hz), frequently occur <300 msec before an interictal intracranial EEG (iEEG) spike with a probability exceeding chance (bootstrapping, p<1e-5). Such FR events are associated with higher spectral power (p<1e-10) and correlated with more vigorous neuronal firing than solitary FR (generalized linear mixed-effects model, GLMM, p<1e-3) irrespective of FR power. During the iEEG spike that follows a FR, action potential firing is lower than during a iEEG spike alone (GLMM, p<1e-10), reflecting an inhibitory restraint of iEEG spike initiation. In contrast, ripples do not appear to prime epileptiform spikes. We next investigated the clinical significance of pre-spike FR in a separate cohort of 23 patients implanted with stereo EEG electrodes who underwent resections. In non-REM sleep recordings, sites containing a high proportion of FR preceding iEEG spikes correlate with brain areas where seizures begin more than solitary FR (p<1e-5). Despite this correlation, removal of these sites does not guarantee seizure freedom. These results are consistent with the hypothesis that FR preceding EEG spikes reflect an increase in local excitability that primes EEG spike discharges preferentially in the seizure onset zone and that epileptogenic brain regions are necessary, but not sufficient, for initiating interictal epileptiform discharges.
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Affiliation(s)
- Shennan A Weiss
- Dept. of Neurology, State University of New York Downstate, Brooklyn, New York, 11203 USA
- Dept. of Physiology and Pharmacology, State University of New York Downstate, Brooklyn, New York, 11203 USA
- Dept. of Neurology, New York City Health + Hospitals/Kings County, Brooklyn, NY, USA
| | - Itzhak Fried
- Dept. of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
| | - Jerome Engel
- Dept. of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Dept. of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Dept. of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
| | - Michael R. Sperling
- Depts. of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, 19107, USA
| | - Robert K.S. Wong
- Dept. of Physiology and Pharmacology, State University of New York Downstate, Brooklyn, New York, 11203 USA
| | - Yuval Nir
- Department of Physiology and Pharmacology, Sackler School of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 6997801, Israel
- Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv 6997801, Israel
- The Sieratzki-Sagol Center for Sleep Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel
| | - Richard J Staba
- Dept. of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
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19
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Burgos DF, Sciaccaluga M, Worby CA, Zafra-Puerta L, Iglesias-Cabeza N, Sánchez-Martín G, Prontera P, Costa C, Serratosa JM, Sánchez MP. Epm2a R240X knock-in mice present earlier cognitive decline and more epileptic activity than Epm2a -/- mice. Neurobiol Dis 2023; 181:106119. [PMID: 37059210 DOI: 10.1016/j.nbd.2023.106119] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 04/02/2023] [Accepted: 04/05/2023] [Indexed: 04/16/2023] Open
Abstract
Lafora disease is a rare recessive form of progressive myoclonic epilepsy, usually diagnosed during adolescence. Patients present with myoclonus, neurological deterioration, and generalized tonic-clonic, myoclonic, or absence seizures. Symptoms worsen until death, usually within the first ten years of clinical onset. The primary histopathological hallmark is the formation of aberrant polyglucosan aggregates called Lafora bodies in the brain and other tissues. Lafora disease is caused by mutations in either the EPM2A gene, encoding laforin, or the EPM2B gene, coding for malin. The most frequent EPM2A mutation is R241X, which is also the most prevalent in Spain. The Epm2a-/- and Epm2b-/- mouse models of Lafora disease show neuropathological and behavioral abnormalities similar to those seen in patients, although with a milder phenotype. To obtain a more accurate animal model, we generated the Epm2aR240X knock-in mouse line with the R240X mutation in the Epm2a gene, using genetic engineering based on CRISPR-Cas9 technology. Epm2aR240X mice exhibit most of the alterations reported in patients, including the presence of LBs, neurodegeneration, neuroinflammation, interictal spikes, neuronal hyperexcitability, and cognitive decline, despite the absence of motor impairments. The Epm2aR240X knock-in mouse displays some symptoms that are more severe that those observed in the Epm2a-/- knock-out, including earlier and more pronounced memory loss, increased levels of neuroinflammation, more interictal spikes and increased neuronal hyperexcitability, symptoms that more precisely resemble those observed in patients. This new mouse model can therefore be specifically used to evaluate how new therapies affects these features with greater precision.
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Affiliation(s)
- Daniel F Burgos
- Laboratory of Neurology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid 28040, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid 28029, Spain; Program in Neuroscience, Autonoma de Madrid University-Cajal Institute, Madrid 28029, Spain
| | - Miriam Sciaccaluga
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia 06132, Italy; Fondazione Malattie Rare Mauro Baschirotto BIRD Onlus, Longare (VI), Italy
| | - Carolyn A Worby
- University of California at San Diego, 9500 Gilman Drive, La Jolla CA92093-0721, USA
| | - Luis Zafra-Puerta
- Laboratory of Neurology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid 28040, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid 28029, Spain; Program in Neuroscience, Autonoma de Madrid University-Cajal Institute, Madrid 28029, Spain; Fondazione Malattie Rare Mauro Baschirotto BIRD Onlus, Longare (VI), Italy
| | - Nerea Iglesias-Cabeza
- Laboratory of Neurology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid 28040, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid 28029, Spain
| | - Gema Sánchez-Martín
- Laboratory of Neurology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid 28040, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid 28029, Spain
| | - Paolo Prontera
- Medical Genetics Unit, S. Maria della Misericordia Hospital, Perugia 06132, Italy
| | - Cinzia Costa
- Section of Neurology, S. Maria della Misericordia Hospital, Department of Medicine and Surgery, University of Perugia, Perugia 06132, Italy
| | - José M Serratosa
- Laboratory of Neurology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid 28040, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid 28029, Spain
| | - Marina P Sánchez
- Laboratory of Neurology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid 28040, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid 28029, Spain.
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Vataman A, Ciolac D, Chiosa V, Aftene D, Leahu P, Winter Y, Groppa SA, Gonzalez-Escamilla G, Muthuraman M, Groppa S. Dynamic flexibility and controllability of network communities in juvenile myoclonic epilepsy. Neurobiol Dis 2023; 179:106055. [PMID: 36849015 DOI: 10.1016/j.nbd.2023.106055] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 02/03/2023] [Accepted: 02/22/2023] [Indexed: 02/27/2023] Open
Abstract
Juvenile myoclonic epilepsy (JME) is the most common syndrome within the idiopathic generalized epilepsy spectrum, manifested by myoclonic and generalized tonic-clonic seizures and spike-and-wave discharges (SWDs) on electroencephalography (EEG). Currently, the pathophysiological concepts addressing SWD generation in JME are still incomplete. In this work, we characterize the temporal and spatial organization of functional networks and their dynamic properties as derived from high-density EEG (hdEEG) recordings and MRI in 40 JME patients (25.4 ± 7.6 years, 25 females). The adopted approach allows for the construction of a precise dynamic model of ictal transformation in JME at the cortical and deep brain nuclei source levels. We implement Louvain algorithm to attribute brain regions with similar topological properties to modules during separate time windows before and during SWD generation. Afterwards, we quantify how modular assignments evolve and steer through different states towards the ictal state by measuring characteristics of flexibility and controllability. We find antagonistic dynamics of flexibility and controllability within network modules as they evolve towards and undergo ictal transformation. Prior to SWD generation, we observe concomitantly increasing flexibility (F(1,39) = 25.3, corrected p < 0.001) and decreasing controllability (F(1,39) = 55.3, p < 0.001) within the fronto-parietal module in γ-band. On a step further, during interictal SWDs as compared to preceding time windows, we notice decreasing flexibility (F(1,39) = 11.9, p < 0.001) and increasing controllability (F(1,39) = 10.1, p < 0.001) within the fronto-temporal module in γ-band. During ictal SWDs as compared to prior time windows, we demonstrate significantly decreasing flexibility (F(1,14) = 31.6; p < 0.001) and increasing controllability (F(1,14) = 44.7, p < 0.001) within the basal ganglia module. Furthermore, we show that flexibility and controllability within the fronto-temporal module of the interictal SWDs relate to seizure frequency and cognitive performance in JME patients. Our results demonstrate that detection of network modules and quantification of their dynamic properties is relevant to track the generation of SWDs. The observed flexibility and controllability dynamics reflect the reorganization of de-/synchronized connections and the ability of evolving network modules to reach a seizure-free state, respectively. These findings may advance the elaboration of network-based biomarkers and more targeted therapeutic neuromodulatory approaches in JME.
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Affiliation(s)
- Anatolie Vataman
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany; Laboratory of Neurobiology and Medical Genetics, Nicolae Testemițanu State University of Medicine and Pharmacy, Chisinau, Republic of Moldova; Department of Neurology, Institute of Emergency Medicine, Chisinau, Moldavia
| | - Dumitru Ciolac
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany; Laboratory of Neurobiology and Medical Genetics, Nicolae Testemițanu State University of Medicine and Pharmacy, Chisinau, Republic of Moldova; Department of Neurology, Institute of Emergency Medicine, Chisinau, Moldavia
| | - Vitalie Chiosa
- Laboratory of Neurobiology and Medical Genetics, Nicolae Testemițanu State University of Medicine and Pharmacy, Chisinau, Republic of Moldova; Department of Neurology, Institute of Emergency Medicine, Chisinau, Moldavia
| | - Daniela Aftene
- Laboratory of Neurobiology and Medical Genetics, Nicolae Testemițanu State University of Medicine and Pharmacy, Chisinau, Republic of Moldova; Department of Neurology, Institute of Emergency Medicine, Chisinau, Moldavia
| | - Pavel Leahu
- Laboratory of Neurobiology and Medical Genetics, Nicolae Testemițanu State University of Medicine and Pharmacy, Chisinau, Republic of Moldova; Department of Neurology, Institute of Emergency Medicine, Chisinau, Moldavia
| | - Yaroslav Winter
- Mainz Comprehensive Epilepsy and Sleep Medicine Center, Department of Neurology, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Stanislav A Groppa
- Laboratory of Neurobiology and Medical Genetics, Nicolae Testemițanu State University of Medicine and Pharmacy, Chisinau, Republic of Moldova; Department of Neurology, Institute of Emergency Medicine, Chisinau, Moldavia
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
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Campbell JM, Davis TS, Anderson DN, Arain A, Inman CS, Smith EH, Rolston JD. Subsets of cortico-cortical evoked potentials propagate as traveling waves. bioRxiv 2023:2023.03.27.534002. [PMID: 37034691 PMCID: PMC10081214 DOI: 10.1101/2023.03.27.534002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Emerging evidence suggests that the temporal dynamics of cortico-cortical evoked potentials (CCEPs) may be used to characterize the patterns of information flow between and within brain networks. At present, however, the spatiotemporal dynamics of CCEP propagation cortically and subcortically are incompletely understood. We hypothesized that CCEPs propagate as an evoked traveling wave emanating from the site of stimulation. To elicit CCEPs, we applied single-pulse stimulation to stereoelectroencephalography (SEEG) electrodes implanted in 21 adult patients with intractable epilepsy. For each robust CCEP, we measured the timing of the maximal descent in evoked local field potentials and broadband high-gamma power (70-150 Hz) envelopes relative to the distance between the recording and stimulation contacts using three different metrics (i.e., Euclidean distance, path length, geodesic distance), representing direct, subcortical, and transcortical propagation, respectively. Many evoked responses to single-pulse electrical stimulation appear to propagate as traveling waves (~17-30%), even in the sparsely sampled, three-dimensional SEEG space. These results provide new insights into the spatiotemporal dynamics of CCEP propagation.
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Affiliation(s)
- Justin M. Campbell
- MD-PhD Program, School of Medicine, University of Utah, Salt Lake City, UT, USA
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - Tyler S. Davis
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - Daria Nesterovich Anderson
- School of Biomedical Engineering, Faculty of Engineering, University of Sydney, Sydney, New South Wales, Australia
| | - Amir Arain
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
| | - Cory S. Inman
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Psychology, University of Utah, Salt Lake City, UT, USA
| | - Elliot H. Smith
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - John D. Rolston
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
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Lai N, Li Z, Xu C, Wang Y, Chen Z. Diverse nature of interictal oscillations: EEG-based biomarkers in epilepsy. Neurobiol Dis 2023; 177:105999. [PMID: 36638892 DOI: 10.1016/j.nbd.2023.105999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/07/2023] [Accepted: 01/09/2023] [Indexed: 01/11/2023] Open
Abstract
Interictal electroencephalogram (EEG) patterns, including high-frequency oscillations (HFOs), interictal spikes (ISs), and slow wave activities (SWAs), are defined as specific oscillations between seizure events. These interictal oscillations reflect specific dynamic changes in network excitability and play various roles in epilepsy. In this review, we briefly describe the electrographic characteristics of HFOs, ISs, and SWAs in the interictal state, and discuss the underlying cellular and network mechanisms. We also summarize representative evidence from experimental and clinical epilepsy to address their critical roles in ictogenesis and epileptogenesis, indicating their potential as electrophysiological biomarkers of epilepsy. Importantly, we put forwards some perspectives for further research in the field.
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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, Zhejiang, China
| | - Zhisheng Li
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, China
| | - Cenglin Xu
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Science, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yi Wang
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, China; Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Science, Zhejiang Chinese Medical University, Hangzhou, China
| | - Zhong Chen
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, China; Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Science, Zhejiang Chinese Medical University, Hangzhou, China; Epilepsy Center, Department of Neurology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
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Schlafly ED, Marshall FA, Merricks EM, Eden UT, Cash SS, Schevon CA, Kramer MA. Multiple Sources of Fast Traveling Waves during Human Seizures: Resolving a Controversy. J Neurosci 2022; 42:6966-6982. [PMID: 35906069 PMCID: PMC9464018 DOI: 10.1523/jneurosci.0338-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 05/26/2022] [Accepted: 06/18/2022] [Indexed: 11/21/2022] Open
Abstract
During human seizures, organized waves of voltage activity rapidly sweep across the cortex. Two contradictory theories describe the source of these fast traveling waves: either a slowly advancing narrow region of multiunit activity (an ictal wavefront) or a fixed cortical location. Limited observations and different analyses prevent resolution of these incompatible theories. Here we address this disagreement by combining the methods and microelectrode array recordings (N = 11 patients, 2 females, N = 31 seizures) from previous human studies to analyze the traveling wave source. We find, inconsistent with both existing theories, a transient relationship between the ictal wavefront and traveling waves, and multiple stable directions of traveling waves in many seizures. Using a computational model that combines elements of both existing theories, we show that interactions between an ictal wavefront and fixed source reproduce the traveling wave dynamics observed in vivo We conclude that combining both existing theories can generate the diversity of ictal traveling waves.SIGNIFICANCE STATEMENT The source of voltage discharges that propagate across cortex during human seizures remains unknown. Two candidate theories exist, each proposing a different discharge source. Support for each theory consists of observations from a small number of human subject recordings, analyzed with separately developed methods. How the different, limited data and different analysis methods impact the evidence for each theory is unclear. To resolve these differences, we combine the unique, human microelectrode array recordings collected separately for each theory and analyze these combined data with a unified approach. We show that neither existing theory adequately describes the data. We then propose a new theory that unifies existing proposals and successfully reproduces the voltage discharge dynamics observed in vivo.
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Affiliation(s)
- Emily D Schlafly
- Graduate Program in Neuroscience, Boston University, Boston, Massachusetts 02215
| | - François A Marshall
- Department of Mathematics and Statistics & Center for Systems Neuroscience, Boston University, Boston, Massachusetts 02215
| | - Edward M Merricks
- Department of Neurology, Columbia University, New York, New York 10032
| | - Uri T Eden
- Department of Mathematics and Statistics & Center for Systems Neuroscience, Boston University, Boston, Massachusetts 02215
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston, Massachusetts 02114
| | | | - Mark A Kramer
- Department of Mathematics and Statistics & Center for Systems Neuroscience, Boston University, Boston, Massachusetts 02215
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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] [What about the content of this article? (0)] [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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Gupta S, Kadam SD. Interictal Discharges: All Roads Lead to Rome? Epilepsy Curr 2022; 22:252-254. [PMID: 36187148 PMCID: PMC9483753 DOI: 10.1177/15357597221098809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Human Interictal Epileptiform Discharges Are Bidirectional Traveling Waves
Echoing Ictal Discharges Smith EH, Liou J-Y, Merricks EM, et al. Elife. 2022;11:e73541.
Published 2022 Jan 20. doi:10.7554/eLife.73541. Interictal epileptiform discharges (IEDs), also known as interictal spikes, are large
intermittent electrophysiological events observed between seizures in patients with
epilepsy. Although they occur far more often than seizures, IEDs are less studied, and
their relationship to seizures remains unclear. To better understand this
relationship, we examined multi-day recordings of microelectrode arrays implanted in
human epilepsy patients, allowing us to precisely observe the spatiotemporal
propagation of IEDs, spontaneous seizures, and how they relate. These recordings
showed that the majority of IEDs are traveling waves, traversing the same path as
ictal discharges during seizures, and with a fixed direction relative to seizure
propagation. Moreover, the majority of IEDs, like ictal discharges, were
bidirectional, with 1 predominant and a second, less frequent antipodal direction.
These results reveal a fundamental spatiotemporal similarity between IEDs and ictal
discharges. These results also imply that most IEDs arise in brain tissue outside the
site of seizure onset and propagate toward it, indicating that the propagation of IEDs
provides useful information for localizing the seizure focus.
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