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Doss DJ, Shless JS, Bick SK, Makhoul GS, Negi AS, Bibro CE, Rashingkar R, Gummadavelli A, Chang C, Gallagher MJ, Naftel RP, Reddy SB, Williams Roberson S, Morgan VL, Johnson GW, Englot DJ. The interictal suppression hypothesis is the dominant differentiator of seizure onset zones in focal epilepsy. Brain 2024; 147:3009-3017. [PMID: 38874456 DOI: 10.1093/brain/awae189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 04/19/2024] [Accepted: 05/16/2024] [Indexed: 06/15/2024] Open
Abstract
Successful surgical treatment of drug-resistant epilepsy traditionally relies on the identification of seizure onset zones (SOZs). Connectome-based analyses of electrographic data from stereo electroencephalography (SEEG) may empower improved detection of SOZs. Specifically, connectome-based analyses based on the interictal suppression hypothesis posit that when the patient is not having a seizure, SOZs are inhibited by non-SOZs through high inward connectivity and low outward connectivity. However, it is not clear whether there are other motifs that can better identify potential SOZs. Thus, we sought to use unsupervised machine learning to identify network motifs that elucidate SOZs and investigate if there is another motif that outperforms the ISH. Resting-state SEEG data from 81 patients with drug-resistant epilepsy undergoing a pre-surgical evaluation at Vanderbilt University Medical Center were collected. Directed connectivity matrices were computed using the alpha band (8-13 Hz). Principal component analysis (PCA) was performed on each patient's connectivity matrix. Each patient's components were analysed qualitatively to identify common patterns across patients. A quantitative definition was then used to identify the component that most closely matched the observed pattern in each patient. A motif characteristic of the interictal suppression hypothesis (high-inward and low-outward connectivity) was present in all individuals and found to be the most robust motif for identification of SOZs in 64/81 (79%) patients. This principal component demonstrated significant differences in SOZs compared to non-SOZs. While other motifs for identifying SOZs were present in other patients, they differed for each patient, suggesting that seizure networks are patient specific, but the ISH is present in nearly all networks. We discovered that a potentially suppressive motif based on the interictal suppression hypothesis was present in all patients, and it was the most robust motif for SOZs in 79% of patients. Each patient had additional motifs that further characterized SOZs, but these motifs were not common across all patients. This work has the potential to augment clinical identification of SOZs to improve epilepsy treatment.
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Affiliation(s)
- Derek J Doss
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University Nashville, Nashville, TN 37235, USA
| | - Jared S Shless
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Sarah K Bick
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Ghassan S Makhoul
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University Nashville, Nashville, TN 37235, USA
| | - Aarushi S Negi
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Camden E Bibro
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Rohan Rashingkar
- Department of Computer Science, Vanderbilt University Nashville, Nashville, TN 37235, USA
| | - Abhijeet Gummadavelli
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Catie Chang
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Computer Science, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Martin J Gallagher
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Robert P Naftel
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Shilpa B Reddy
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Shawniqua Williams Roberson
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Computer Science, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Radiology and Biomedical Imaging, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University Nashville, Nashville, TN 37235, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Department of Computer Science, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Department of Radiology and Biomedical Imaging, Vanderbilt University Medical Center, Nashville, TN 37235, USA
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Wang D, Lu D, Zhang M, Dai A, Jin G, Wang Q, Zhang Y, Kahane P. Advances in epileptic network findings of hypothalamic hamartomas. J Cent Nerv Syst Dis 2024; 16:11795735241237627. [PMID: 38449707 PMCID: PMC10916467 DOI: 10.1177/11795735241237627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 01/16/2024] [Indexed: 03/08/2024] Open
Abstract
Hypothalamic hamartomas (HHs) are congenital developmental malformations located in the hypothalamus. They are associated with a characteristic clinical manifestation known as gelastic seizures (GS). However, the traditional understanding of HHs has been limited, resulting in insufficient treatment options and high recurrence rates of seizures after surgery. This is consistent with the network hypothesis of focal epilepsy that the epileptogenic zone is not only limited to HH but may also involve the distant cerebral cortex external to the HH mass. The epilepsy network theory, on the other hand, provides a new perspective. In this study, we aim to explore HH-related epilepsy as a network disease, challenging the conventional notion of being a focal lesional disease. We analyze various aspects of HHs, including genes and signaling pathways, local circuits, the whole-brain level, phenotypical expression in terms of seizure semiology, and comorbidities. By examining HHs through the lens of network theory, we can enhance our understanding of the condition and potentially identify novel approaches for more effective management and treatment of epilepsy associated with HHs.
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Affiliation(s)
- Di Wang
- School of Engineering Medicine, Beihang University, Beijing, China
| | - Di Lu
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- Clinical Research Center for Epilepsy, Capital Medical University, Beijing, China
| | - Mingtai Zhang
- School of Engineering Medicine, Beihang University, Beijing, China
| | - Anqi Dai
- School of Engineering Medicine, Beihang University, Beijing, China
| | - Guangyuan Jin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Qiao Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yuyang Zhang
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Philippe Kahane
- Neurology Deparment, CHU Grenoble Alpes, University Grenoble Alpes, Grenoble Institute Neuroscience, Grenoble, France
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3
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Doss DJ, Johnson GW, Englot DJ. Imaging and Stereotactic Electroencephalography Functional Networks to Guide Epilepsy Surgery. Neurosurg Clin N Am 2024; 35:61-72. [PMID: 38000842 PMCID: PMC10676462 DOI: 10.1016/j.nec.2023.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2023]
Abstract
Epilepsy surgery is a potentially curative treatment of drug-resistant epilepsy that has remained underutilized both due to inadequate referrals and incomplete localization hypotheses. The complexity of patients evaluated for epilepsy surgery has increased, thus new approaches are necessary to treat these patients. The paradigm of epilepsy surgery has evolved to match this challenge, now considering the entire seizure network with the goal of disrupting it through resection, ablation, neuromodulation, or a combination. The network paradigm has the potential to aid in identification of the seizure network as well as treatment selection.
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Affiliation(s)
- Derek J Doss
- Department of Biomedical Engineering, Vanderbilt University, PMB 351631, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Vanderbilt University Institute of Imaging Science (VUIIS), 1161 21st Avenue South, Medical Center North AA-1105, Nashville, TN 37232, USA; Vanderbilt Institute for Surgery and Engineering (VISE), 1161 21st Avenue South, MCN S2323, Nashville, TN 37232, USA
| | - Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University, PMB 351631, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Vanderbilt University Institute of Imaging Science (VUIIS), 1161 21st Avenue South, Medical Center North AA-1105, Nashville, TN 37232, USA; Vanderbilt Institute for Surgery and Engineering (VISE), 1161 21st Avenue South, MCN S2323, Nashville, TN 37232, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, PMB 351631, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Vanderbilt University Institute of Imaging Science (VUIIS), 1161 21st Avenue South, Medical Center North AA-1105, Nashville, TN 37232, USA; Vanderbilt Institute for Surgery and Engineering (VISE), 1161 21st Avenue South, MCN S2323, Nashville, TN 37232, USA; Department of Neurological Surgery, Vanderbilt University Medical Center, 1161 21st Avenue South, T4224 Medical Center North, Nashville, TN 37232, USA; Department of Electrical and Computer Engineering, Vanderbilt University, PMB 351824, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Department of Radiological Sciences, Vanderbilt University Medical Center, 1161 21st Avenue South, Nashville, TN 37232, USA.
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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] [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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Esparza J, Sebastián ER, de la Prida LM. From cell types to population dynamics: Making hippocampal manifolds physiologically interpretable. Curr Opin Neurobiol 2023; 83:102800. [PMID: 37898015 DOI: 10.1016/j.conb.2023.102800] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 09/27/2023] [Accepted: 09/28/2023] [Indexed: 10/30/2023]
Abstract
The study of the hippocampal code is gaining momentum. While the physiological approach targets the contribution of individual cells as determined by genetic, biophysical and circuit factors, the field pushes for a population dynamic approach that considers the representation of behavioural variables by a large number of neurons. In this alternative framework, neuronal activity is projected into low-dimensional manifolds. These manifolds can reveal the structure of population representations, but their physiological interpretation is challenging. Here, we review the recent literature and propose that integrating information regarding behavioral traits, local field potential oscillations and cell-type-specificity into neural manifolds offers strategies to make them interpretable at the physiological level.
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Lillis KP. Connectome the Dots for Presurgical Predictions. Epilepsy Curr 2022; 22:378-380. [PMID: 36426193 PMCID: PMC9661618 DOI: 10.1177/15357597221125221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Presurgical Temporal Lobe Epilepsy Connectome Fingerprint for Seizure Outcome Prediction Morgan VL, Sainburg LE, Johnson GW, Janson A, Levine KK, Rogers BP, Chang C, Englot DJ. Brain Comm. 2022;4(3):fcac128. doi:10.1093/braincomms/fcac128 Temporal lobe epilepsy presents a unique situation where confident clinical localization of the seizure focus does not always result in a seizure-free or favourable outcome after mesial temporal surgery. In this work, magnetic resonance imaging derived functional and structural whole-brain connectivity was used to compute a network fingerprint that captures the connectivity profile characteristics that are common across a group of nine of these patients with seizure-free outcome. The connectivity profile was then computed for 38 left-out patients with the hypothesis that similarity to the fingerprint indicates seizure-free surgical outcome. Patient profile distance to the fingerprint was compared with 1-year seizure outcome and standard clinical parameters. Distance to the fingerprint was higher for patients with Engel III-IV 1-year outcome compared with those with Engel Ia, Ib-d, and II outcome (Kruskal-Wallis, P < 0.01; Wilcoxon rank-sum pcorr <0.05 Bonferroni-corrected). Receiver operator characteristic analysis revealed 100% sensitivity and 90% specificity in identifying patients with Engel III-IV outcome based on distance to the fingerprint in the left-out patients. Furthermore, distance to the fingerprint was not related to any individual clinical parameter including age at scan, duration of disease, total seizure frequency, presence of mesial temporal sclerosis, lateralizing ictal, interictal scalp electroencephalography, invasive stereo-encephalography, or positron emission tomography. And two published algorithms utilizing multiple clinical measures for predicting seizure outcome were not related to distance to the fingerprint, nor predictive of seizure outcome in this cohort. The functional and structural connectome fingerprint provides quantitative, clinically interpretable and significant information not captured by standard clinical assessments alone or in combinations. This automated and simple method may improve patient-specific prediction of seizure outcome in patients with a clinically identified focus in the mesial temporal lobe.
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Li X, Zhang H, Lai H, Wang J, Wang W, Yang X. High-Frequency Oscillations and Epileptogenic Network. Curr Neuropharmacol 2022; 20:1687-1703. [PMID: 34503414 PMCID: PMC9881061 DOI: 10.2174/1570159x19666210908165641] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 08/26/2021] [Accepted: 08/31/2021] [Indexed: 11/22/2022] Open
Abstract
Epilepsy is a network disease caused by aberrant neocortical large-scale connectivity spanning regions on the scale of several centimeters. High-frequency oscillations, characterized by the 80-600 Hz signals in electroencephalography, have been proven to be a promising biomarker of epilepsy that can be used in assessing the severity and susceptibility of epilepsy as well as the location of the epileptogenic zone. However, the presence of a high-frequency oscillation network remains a topic of debate as high-frequency oscillations have been previously thought to be incapable of propagation, and the relationship between high-frequency oscillations and the epileptogenic network has rarely been discussed. Some recent studies reported that high-frequency oscillations may behave like networks that are closely relevant to the epileptogenic network. Pathological highfrequency oscillations are network-driven phenomena and elucidate epileptogenic network development; high-frequency oscillations show different characteristics coincident with the epileptogenic network dynamics, and cross-frequency coupling between high-frequency oscillations and other signals may mediate the generation and propagation of abnormal discharges across the network.
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Affiliation(s)
- Xiaonan Li
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
| | | | | | - Jiaoyang Wang
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
| | - Wei Wang
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
| | - Xiaofeng Yang
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China,Address correspondence to this author at the Bioland Laboratory, Guangzhou, China; Tel: 86+ 18515855127; E-mail:
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8
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Servilha-Menezes G, Garcia-Cairasco N. A complex systems view on the current hypotheses of epilepsy pharmacoresistance. Epilepsia Open 2022; 7 Suppl 1:S8-S22. [PMID: 35253410 PMCID: PMC9340300 DOI: 10.1002/epi4.12588] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 02/22/2022] [Accepted: 02/27/2022] [Indexed: 11/11/2022] Open
Abstract
Drug-resistant epilepsy remains to this day as a highly prevalent condition affecting around one-third of patients with epilepsy, despite all the research and the development of several new antiseizure medications (ASMs) over the last decades. Epilepsies are multifactorial complex diseases, commonly associated with psychiatric, neurological, and somatic comorbidities. Thus, to solve the puzzling problem of pharmacoresistance, the diagnosis and modeling of epilepsy and comorbidities need to change toward a complex system approach. In this review, we have summarized the sequence of events for the definition of epilepsies and comorbidities, the search for mechanisms, and the major hypotheses of pharmacoresistance, drawing attention to some of the many converging aspects between the proposed mechanisms, their supporting evidence, and comorbidities-related alterations. The use of systems biology applied to epileptology may lead to the discovery of new targets and the development of new ASMs, as may advance our understanding of the epilepsies and their comorbidities, providing much deeper insight on multidrug pharmacoresistance.
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Affiliation(s)
- Gabriel Servilha-Menezes
- Department of Physiology, Ribeirão Preto Medical School, University of São Paulo (FMRP-SP), Ribeirão Preto, São Paulo, Brazil
| | - Norberto Garcia-Cairasco
- Department of Physiology, Ribeirão Preto Medical School, University of São Paulo (FMRP-SP), Ribeirão Preto, São Paulo, Brazil.,Department of Neurosciences and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo (FMRP-SP), Ribeirão Preto, São Paulo, Brazil
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9
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Morgan VL, Sainburg LE, Johnson GW, Janson A, Levine KK, Rogers BP, Chang C, Englot DJ. Presurgical temporal lobe epilepsy connectome fingerprint for seizure outcome prediction. Brain Commun 2022; 4:fcac128. [PMID: 35774185 PMCID: PMC9237708 DOI: 10.1093/braincomms/fcac128] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 03/02/2022] [Accepted: 05/12/2022] [Indexed: 01/19/2023] Open
Abstract
Temporal lobe epilepsy presents a unique situation where confident clinical localization of the seizure focus does not always result in a seizure-free or favourable outcome after mesial temporal surgery. In this work, magnetic resonance imaging derived functional and structural whole-brain connectivity was used to compute a network fingerprint that captures the connectivity profile characteristics that are common across a group of nine of these patients with seizure-free outcome. The connectivity profile was then computed for 38 left-out patients with the hypothesis that similarity to the fingerprint indicates seizure-free surgical outcome. Patient profile distance to the fingerprint was compared with 1-year seizure outcome and standard clinical parameters. Distance to the fingerprint was higher for patients with Engel III-IV 1-year outcome compared with those with Engel Ia, Ib-d, and II outcome (Kruskal-Wallis, P < 0.01; Wilcoxon rank-sum p corr <0.05 Bonferroni-corrected). Receiver operator characteristic analysis revealed 100% sensitivity and 90% specificity in identifying patients with Engel III-IV outcome based on distance to the fingerprint in the left-out patients. Furthermore, distance to the fingerprint was not related to any individual clinical parameter including age at scan, duration of disease, total seizure frequency, presence of mesial temporal sclerosis, lateralizing ictal, interictal scalp electroencephalography, invasive stereo-encephalography, or positron emission tomography. And two published algorithms utilizing multiple clinical measures for predicting seizure outcome were not related to distance to the fingerprint, nor predictive of seizure outcome in this cohort. The functional and structural connectome fingerprint provides quantitative, clinically interpretable and significant information not captured by standard clinical assessments alone or in combinations. This automated and simple method may improve patient-specific prediction of seizure outcome in patients with a clinically identified focus in the mesial temporal lobe.
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Affiliation(s)
- Victoria L Morgan
- Correspondence to: Victoria L. Morgan, PhD 1161 21st Avenue South, R0102 MCN Nashville, TN 37232 USA E-mail:
| | - Lucas E Sainburg
- Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, 1161 21st Avenue South, R0102 MCN, Nashville, TN 37232, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Graham W Johnson
- Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, 1161 21st Avenue South, R0102 MCN, Nashville, TN 37232, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA,Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Andrew Janson
- Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, 1161 21st Avenue South, R0102 MCN, Nashville, TN 37232, USA
| | - Kaela K Levine
- Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, 1161 21st Avenue South, R0102 MCN, Nashville, TN 37232, USA
| | - Baxter P Rogers
- Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, 1161 21st Avenue South, R0102 MCN, Nashville, TN 37232, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Catie Chang
- Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, 1161 21st Avenue South, R0102 MCN, Nashville, TN 37232, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
| | - Dario J Englot
- Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, 1161 21st Avenue South, R0102 MCN, Nashville, TN 37232, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA,Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
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Drug-resistant focal epilepsy in children is associated with increased modal controllability of the whole brain and epileptogenic regions. Commun Biol 2022; 5:394. [PMID: 35484213 PMCID: PMC9050895 DOI: 10.1038/s42003-022-03342-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 04/06/2022] [Indexed: 02/06/2023] Open
Abstract
Network control theory provides a framework by which neurophysiological dynamics of the brain can be modelled as a function of the structural connectome constructed from diffusion MRI. Average controllability describes the ability of a region to drive the brain to easy-to-reach neurophysiological states whilst modal controllability describes the ability of a region to drive the brain to difficult-to-reach states. In this study, we identify increases in mean average and modal controllability in children with drug-resistant epilepsy compared to healthy controls. Using simulations, we purport that these changes may be a result of increased thalamocortical connectivity. At the node level, we demonstrate decreased modal controllability in the thalamus and posterior cingulate regions. In those undergoing resective surgery, we also demonstrate increased modal controllability of the resected parcels, a finding specific to patients who were rendered seizure free following surgery. Changes in controllability are a manifestation of brain network dysfunction in epilepsy and may be a useful construct to understand the pathophysiology of this archetypical network disease. Understanding the mechanisms underlying these controllability changes may also facilitate the design of network-focussed interventions that seek to normalise network structure and function.
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11
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Müller M, Dekkers M, Wiest R, Schindler K, Rummel C. More Than Spikes: On the Added Value of Non-linear Intracranial EEG Analysis for Surgery Planning in Temporal Lobe Epilepsy. Front Neurol 2022; 12:741450. [PMID: 35095712 PMCID: PMC8793863 DOI: 10.3389/fneur.2021.741450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 10/18/2021] [Indexed: 11/13/2022] Open
Abstract
Epilepsy surgery can be a very effective therapy in medication refractory patients. During patient evaluation intracranial EEG is analyzed by clinical experts to identify the brain tissue generating epileptiform events. Quantitative EEG analysis increasingly complements this approach in research settings, but not yet in clinical routine. We investigate the correspondence between epileptiform events and a specific quantitative EEG marker. We analyzed 99 preictal epochs of multichannel intracranial EEG of 40 patients with mixed etiologies. Time and channel of occurrence of epileptiform events (spikes, slow waves, sharp waves, fast oscillations) were annotated by a human expert and non-linear excess interrelations were calculated as a quantitative EEG marker. We assessed whether the visually identified preictal events predicted channels that belonged to the seizure onset zone, that were later resected or that showed strong non-linear interrelations. We also investigated whether the seizure onset zone or the resection were predicted by channels with strong non-linear interrelations. In patients with temporal lobe epilepsy (32 of 40), epileptic spikes and the seizure onset zone predicted the resected brain tissue much better in patients with favorable seizure control after surgery than in unfavorable outcomes. Beyond that, our analysis did not reveal any significant associations with epileptiform EEG events. Specifically, none of the epileptiform event types did predict non-linear interrelations. In contrast, channels with strong non-linear excess EEG interrelations predicted the resected channels better in patients with temporal lobe epilepsy and favorable outcome. Also in the small number of patients with seizure onset in the frontal and parietal lobes, no association between epileptiform events and channels with strong non-linear excess EEG interrelations was detectable. In contrast to patients with temporal seizure onset, EEG channels with strong non-linear excess interrelations did neither predict the seizure onset zone nor the resection of these patients or allow separation between patients with favorable and unfavorable seizure control. Our study indicates that non-linear excess EEG interrelations are not strictly associated with epileptiform events, which are one key concept of current clinical EEG assessment. Rather, they may provide information relevant for surgery planning in temporal lobe epilepsy. Our study suggests to incorporate quantitative EEG analysis in the workup of clinical cases. We make the EEG epochs and expert annotations publicly available in anonymized form to foster similar analyses for other quantitative EEG methods.
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Affiliation(s)
- Michael Müller
- Support Center for Advanced Neuroimaging (SCAN), University Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern, Switzerland
| | - Martijn Dekkers
- Department of Neurology, Inselspital, Bern University Hospital, University Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern, Switzerland
| | - Kaspar Schindler
- Department of Neurology, Inselspital, Bern University Hospital, University Bern, Bern, Switzerland
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern, Switzerland
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12
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Davis KA, Jirsa VK, Schevon CA. Wheels Within Wheels: Theory and Practice of Epileptic Networks. Epilepsy Curr 2021; 21:15357597211015663. [PMID: 33988042 PMCID: PMC8512917 DOI: 10.1177/15357597211015663] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Affiliation(s)
- Kathryn A. Davis
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Viktor K. Jirsa
- Aix-Marseille Universite, Marseille, Provence-Alpes-Cote d’Azu, France
- INSERM, Paris, Ile-de-France, France
- Institute de Neurosciences des Systemes,
Marseille, Provence-Alpes-Cote d’Azu, France
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13
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Scott RC. Brains, complex systems and therapeutic opportunities in epilepsy. Seizure 2021; 90:155-159. [PMID: 33582003 DOI: 10.1016/j.seizure.2021.02.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2021] [Revised: 01/27/2021] [Accepted: 02/01/2021] [Indexed: 12/16/2022] Open
Abstract
The treatment of epilepsy remains extremely challenging for the thirty percent of people that do not become seizure free. This is despite the introduction of multiple new drugs over that last several decades, highlighting the need for new approaches to identifying novel therapeutic strategies. Conceptualizing the brain as a complex adaptive system and applying the tools that are used in addressing such systems provides an opportunity for expanding the space in which to search for new therapies. Epilepsy has long been considered a network disease at the level of whole brain connectivity, but the application of the concepts to gene and protein expression networks as well as to the dynamic behaviors of microcircuits has been underexplored. These levels of the brain complex adaptive system will be reviewed and a case made for the epilepsy community to embrace these concepts in order to reap to enormous potential rewards.
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Affiliation(s)
- Rod C Scott
- University of Vermont, 95 Carrigan Drive, Burlington, VT, 05405, United States; University of Vermont Medical Center, United States; Great Ormond Street Hospital for Children NHS Trust, United Kingdom.
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14
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The vulnerability of the immature brain. HANDBOOK OF CLINICAL NEUROLOGY 2020. [PMID: 32958197 DOI: 10.1016/b978-0-444-64150-2.00010-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
The concept of vulnerability of the immature brain is multifactorial by definition. Newer scientific work in this area has shifted and enlarged the concept from theoretical frameworks to the multiple levels (molecular, cellular, anatomic, network, behavioral) of the organization of the growing brain. The concept of vulnerability was first introduced by Donald O. Hebb in the 1950s and referred to the inability of the immature brain to completely recover normal development after a brain insult. The concept of vulnerability was further extended to the limitations of the brain in the development of specific skills in neuronal substrates originally used for other functions. We present an overview of some neurodevelopmental processes that characterize the immature brain and that can predict vulnerability in the case of disturbances: Hebb's principle, synaptic homeostasis, selective vulnerability of immature cells in mammals, and inherited constraint networks. A better understanding of the vulnerability mechanisms may help in early detection and prevention and further proposed individualized therapeutic approaches to enhance children's developmental outcomes.
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15
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Chari A, Thornton RC, Tisdall MM, Scott RC. Microelectrode recordings in human epilepsy: a case for clinical translation. Brain Commun 2020; 2:fcaa082. [PMID: 32954332 PMCID: PMC7472902 DOI: 10.1093/braincomms/fcaa082] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 04/21/2020] [Accepted: 04/28/2020] [Indexed: 12/25/2022] Open
Abstract
With their 'all-or-none' action potential responses, single neurons (or units) are accepted as the basic computational unit of the brain. There is extensive animal literature to support the mechanistic importance of studying neuronal firing as a way to understand neuronal microcircuits and brain function. Although most studies have emphasized physiology, there is increasing recognition that studying single units provides novel insight into system-level mechanisms of disease. Microelectrode recordings are becoming more common in humans, paralleling the increasing use of intracranial electroencephalography recordings in the context of presurgical evaluation in focal epilepsy. In addition to single-unit data, microelectrode recordings also record local field potentials and high-frequency oscillations, some of which may be different to that recorded by clinical macroelectrodes. However, microelectrodes are being used almost exclusively in research contexts and there are currently no indications for incorporating microelectrode recordings into routine clinical care. In this review, we summarize the lessons learnt from 65 years of microelectrode recordings in human epilepsy patients. We cover the electrode constructs that can be utilized, principles of how to record and process microelectrode data and insights into ictal dynamics, interictal dynamics and cognition. We end with a critique on the possibilities of incorporating single-unit recordings into clinical care, with a focus on potential clinical indications, each with their specific evidence base and challenges.
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Affiliation(s)
- Aswin Chari
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Department of Neurosurgery, Great Ormond Street Hospital, London WC1N 3JH, UK
| | - Rachel C Thornton
- Department of Clinical Neurophysiology, Great Ormond Street Hospital, London WC1N 3JH, UK
| | - Martin M Tisdall
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Department of Neurosurgery, Great Ormond Street Hospital, London WC1N 3JH, UK
| | - Rodney C Scott
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Department of Neurological Sciences, University of Vermont, Burlington, VT 05405, USA
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16
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Barot N. Networks in Frontal Lobe Epilepsy. Neurosurg Clin N Am 2020; 31:319-324. [PMID: 32475482 DOI: 10.1016/j.nec.2020.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Epilepsy affects about 1% of the general population. Frontal lobe epilepsy is the second most common focal epilepsy accounting for nearly 25% of medically refractory epilepsies. This paper reviews frontal lobe epilepsy from a perspective of a network disease that may help us to understand epilepsy from the microscale of genes, to local neuronal circuits, to the macrolevel of a whole-brain network. Surgical interventions, such as ablation and resection act by removing the active target nodes in the network, while responsive neurostimulation and vagus nerve stimulation act by modulating networks at the local neuronal circuit level and whole-brain level.
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Affiliation(s)
- Niravkumar Barot
- University of Pittsburgh, Kaufmann Medical Building, 3471 Fifth Avenues, Suite 810, Pittsburgh, PA 15213, USA.
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17
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Gummadavelli A, Quraishi IH, Gerrard JL. Responsive Neurostimulation. Stereotact Funct Neurosurg 2020. [DOI: 10.1007/978-3-030-34906-6_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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18
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Schidlitzki A, Bascuñana P, Srivastava PK, Welzel L, Twele F, Töllner K, Käufer C, Gericke B, Feleke R, Meier M, Polyak A, Ross TL, Gerhauser I, Bankstahl JP, Johnson MR, Bankstahl M, Löscher W. Proof-of-concept that network pharmacology is effective to modify development of acquired temporal lobe epilepsy. Neurobiol Dis 2019; 134:104664. [PMID: 31678583 DOI: 10.1016/j.nbd.2019.104664] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Revised: 10/08/2019] [Accepted: 10/30/2019] [Indexed: 10/25/2022] Open
Abstract
Epilepsy is a complex network phenomenon that, as yet, cannot be prevented or cured. We recently proposed network-based approaches to prevent epileptogenesis. For proof of concept we combined two drugs (levetiracetam and topiramate) for which in silico analysis of drug-protein interaction networks indicated a synergistic effect on a large functional network of epilepsy-relevant proteins. Using the intrahippocampal kainate mouse model of temporal lobe epilepsy, the drug combination was administered during the latent period before onset of spontaneous recurrent seizures (SRS). When SRS were periodically recorded by video-EEG monitoring after termination of treatment, a significant decrease in incidence and frequency of SRS was determined, indicating antiepileptogenic efficacy. Such efficacy was not observed following single drug treatment. Furthermore, a combination of levetiracetam and phenobarbital, for which in silico analysis of drug-protein interaction networks did not indicate any significant drug-drug interaction, was not effective to modify development of epilepsy. Surprisingly, the promising antiepileptogenic effect of the levetiracetam/topiramate combination was obtained in the absence of any significant neuroprotective or anti-inflammatory effects as indicated by multimodal brain imaging and histopathology. High throughput RNA-sequencing (RNA-seq) of the ipsilateral hippocampus of mice treated with the levetiracetam/topiramate combination showed that several genes that have been linked previously to epileptogenesis, were significantly differentially expressed, providing interesting entry points for future mechanistic studies. Overall, we have discovered a novel combination treatment with promise for prevention of epilepsy.
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Affiliation(s)
- Alina Schidlitzki
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany; Center for Systems Neuroscience, 30559 Hannover, Germany
| | - Pablo Bascuñana
- Department of Nuclear Medicine, Hannover Medical School, Germany
| | | | - Lisa Welzel
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany; Center for Systems Neuroscience, 30559 Hannover, Germany
| | - Friederike Twele
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany
| | - Kathrin Töllner
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany
| | - Christopher Käufer
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany
| | - Birthe Gericke
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany; Center for Systems Neuroscience, 30559 Hannover, Germany
| | - Rahel Feleke
- Division of Brain Sciences, Imperial College London, London, UK
| | - Martin Meier
- Central Animal Facility & Institute for Laboratory Animal Science, Hannover Medical School, Hannover, Germany
| | - Andras Polyak
- Department of Nuclear Medicine, Hannover Medical School, Germany
| | - Tobias L Ross
- Department of Nuclear Medicine, Hannover Medical School, Germany
| | - Ingo Gerhauser
- Department of Pathology, University of Veterinary Medicine Hannover, Germany
| | - Jens P Bankstahl
- Department of Nuclear Medicine, Hannover Medical School, Germany
| | | | - Marion Bankstahl
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany; Center for Systems Neuroscience, 30559 Hannover, Germany; Central Animal Facility & Institute for Laboratory Animal Science, Hannover Medical School, Hannover, Germany
| | - Wolfgang Löscher
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany; Center for Systems Neuroscience, 30559 Hannover, Germany.
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19
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Müller M, Caporro M, Gast H, Pollo C, Wiest R, Schindler K, Rummel C. Linear and nonlinear interrelations show fundamentally distinct network structure in preictal intracranial EEG of epilepsy patients. Hum Brain Mapp 2019; 41:467-483. [PMID: 31625670 PMCID: PMC7268049 DOI: 10.1002/hbm.24816] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2019] [Revised: 09/18/2019] [Accepted: 09/20/2019] [Indexed: 12/24/2022] Open
Abstract
Resection of the seizure generating tissue can be highly beneficial in patients with drug-resistant epilepsy. However, only about half of all patients undergoing surgery get permanently and completely seizure free. Investigating the dependences between intracranial EEG signals adds a multivariate perspective largely unavailable to visual EEG analysis, which is the current clinical practice. We examined linear and nonlinear interrelations between intracranial EEG signals regarding their spatial distribution and network characteristics. The analyzed signals were recorded immediately before clinical seizure onset in epilepsy patients who received a standardized electrode implantation targeting the mesiotemporal structures. The linear interrelation networks were predominantly locally connected and highly reproducible between patients. In contrast, the nonlinear networks had a clearly centralized structure, which was specific for the individual pathology. The nonlinear interrelations were overrepresented in the focal hemisphere and in patients with no or only rare seizures after surgery specifically in the resected tissue. Connections to the outside were predominantly nonlinear. In all patients without worthwhile improvement after resective treatment, tissue producing strong nonlinear interrelations was left untouched by surgery. Our findings indicate that linear and nonlinear interrelations play fundamentally different roles in preictal intracranial EEG. Moreover, they suggest nonlinear signal interrelations to be a marker of epileptogenic tissue and not a characteristic of the mesiotemporal structures. Our results corroborate the network-based nature of epilepsy and suggest the application of network analysis to support the planning of resective epilepsy surgery.
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Affiliation(s)
- Michael Müller
- Support Center for Advanced Neuroimaging (SCAN), University Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern, Switzerland.,Department of Neurology, Inselspital, Bern University Hospital, University Bern, Bern, Switzerland
| | - Matteo Caporro
- Department of Neurology, Inselspital, Bern University Hospital, University Bern, Bern, Switzerland
| | - Heidemarie Gast
- Department of Neurology, Inselspital, Bern University Hospital, University Bern, Bern, Switzerland
| | - Claudio Pollo
- Department of Neurosurgery, Inselspital, Bern University Hospital, University Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern, Switzerland
| | - Kaspar Schindler
- Department of Neurology, Inselspital, Bern University Hospital, University Bern, Bern, Switzerland
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern, Switzerland
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20
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Inhibition and oscillations in the human brain tissue in vitro. Neurobiol Dis 2019; 125:198-210. [DOI: 10.1016/j.nbd.2019.02.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 12/22/2018] [Accepted: 02/07/2019] [Indexed: 01/22/2023] Open
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21
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Li L, Bragin A, Staba R, Engel J. Unit firing and oscillations at seizure onset in epileptic rodents. Neurobiol Dis 2019; 127:382-389. [PMID: 30928646 DOI: 10.1016/j.nbd.2019.03.027] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 03/04/2019] [Accepted: 03/26/2019] [Indexed: 01/27/2023] Open
Abstract
Epileptic seizures result from a variety of pathophysiological processes, evidenced by different electrographic ictal onset patterns, as seen on direct brain recordings. The two most common electrographic patterns of focal ictal onset in patients are hypersynchronous (HYP) and low-voltage fast (LVF). Whereas LVF ictal onsets were believed to result from disinhibition; based on similarities with absence seizures, focal HYP ictal onsets were believed to result from increased synchronizing inhibition. Recent findings, however, suggest the differences between these seizure onset types are more complicated and, in some cases, the opposite of these concepts are true. The following review presents evidence that a reduction of tonic inhibition on small pathologically interconnected neuron (PIN) clusters generating pathological high-frequency oscillations (pHFOs), which reflect abnormal synchronously bursting neurons may be the cause of HYP ictal onsets. Increased inhibition preceding LVF ictal onsets are discussed in other reviews in this issue. We postulate that neuronal cell loss following epileptogenic insults can result in structural reorganization, giving rise to small PIN clusters, which generate pHFOs. These clusters have a heterogeneous distribution and are spatially stable over time. Studies have demonstrated that a transient reduction in tonic inhibition causes these clusters to increase in size. This could result in consolidation and synchronization of pHFOs until a critical mass leads to propagation of HYP ictal discharges. Viewed within a network neuroscience framework, local disturbances such as PIN clusters are likely to contribute to large-scale brain network alterations: a better understanding of these epileptogenic networks promises to elucidate mechanisms of ictogenesis, epileptogenesis, and certain comorbidities of epilepsy.
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Affiliation(s)
- Lin Li
- Department of Neurology, University of California, Los Angeles, CA, USA
| | - Anatol Bragin
- Department of Neurology, University of California, Los Angeles, CA, USA; Brain Research Institute, University of California, Los Angeles, CA, USA
| | - Richard Staba
- Department of Neurology, University of California, Los Angeles, CA, USA
| | - Jerome Engel
- Department of Neurology, University of California, Los Angeles, CA, USA; Brain Research Institute, University of California, Los Angeles, CA, USA; Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
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22
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Welzel L, Twele F, Schidlitzki A, Töllner K, Klein P, Löscher W. Network pharmacology for antiepileptogenesis: Tolerability and neuroprotective effects of novel multitargeted combination treatments in nonepileptic vs. post-status epilepticus mice. Epilepsy Res 2019; 151:48-66. [PMID: 30831337 DOI: 10.1016/j.eplepsyres.2019.02.010] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 02/06/2019] [Accepted: 02/23/2019] [Indexed: 01/08/2023]
Abstract
Network-based approaches in drug discovery comprise both development of novel drugs interacting with multiple targets and repositioning of drugs with known targets to form novel drug combinations that interact with cellular or molecular networks whose function is disturbed in a disease. Epilepsy is a complex network phenomenon that, as yet, cannot be prevented or cured. We recently proposed multitargeted, network-based approaches to prevent epileptogenesis by combinations of clinically available drugs chosen to impact diverse epileptogenic processes. In order to test this strategy preclinically, we developed a multiphase sequential study design for evaluating such drug combinations in rodents, derived from human clinical drug development phases. Because pharmacokinetics of such drugs are known, only the tolerability of novel drug combinations needs to be evaluated in Phase I in öhealthy" controls. In Phase IIa, tolerability is assessed following an epileptogenic brain insult, followed by antiepileptogenic efficacy testing in Phase IIb. Here, we report Phase I and Phase IIa evaluation of 7 new drug combinations in mice, using 10 drugs (levetiracetam, topiramate, gabapentin, deferoxamine, fingolimod, ceftriaxone, α-tocopherol, melatonin, celecoxib, atorvastatin) with diverse mechanisms thought to be important in epileptogenesis. Six of the 7 drug combinations were well tolerated in mice during prolonged treatment at the selected doses in both controls and during the latent phase following status epilepticus induced by intrahippocampal kainate. However, none of the combinations prevented hippocampal damage in response to kainate, most likely because treatment started only 16-18 h after kainate. This suggests that antiepileptogenic or disease-modifying treatment may need to start earlier after the brain insult. The present data provide a rich collection of tolerable, network-based combinatorial therapies as a basis for antiepileptogenic or disease-modifying efficacy testing.
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Affiliation(s)
- Lisa Welzel
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany; Center for Systems Neuroscience, 30559 Hannover, Germany
| | - Friederike Twele
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany
| | - Alina Schidlitzki
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany
| | - Kathrin Töllner
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany
| | - Pavel Klein
- Mid-Atlantic Epilepsy and Sleep Center, Bethesda, MD 20817, USA
| | - Wolfgang Löscher
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, 30559 Hannover, Germany; Center for Systems Neuroscience, 30559 Hannover, Germany.
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