1
|
Bower MR. Review: seizure-related consolidation and the network theory of epilepsy. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1430934. [PMID: 39238837 PMCID: PMC11374659 DOI: 10.3389/fnetp.2024.1430934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Accepted: 06/25/2024] [Indexed: 09/07/2024]
Abstract
Epilepsy is a complex, multifaceted disease that affects patients in several ways in addition to seizures, including psychological, social, and quality of life issues, but epilepsy is also known to interact with sleep. Seizures often occur at the boundary between sleep and wake, patients with epilepsy often experience disrupted sleep, and the rate of inter-ictal epileptiform discharges increases during non-REM sleep. The Network Theory of Epilepsy did not address a role for sleep, but recent emphasis on the interaction between epilepsy and sleep suggests that post-seizure sleep may also be involved in the process by which seizures arise and become more severe with time ("epileptogenesis") by co-opting processes related to the formation of long-term memories. While it is generally acknowledged that recurrent seizures arise from the aberrant function of neural circuits, it is possible that the progression of epilepsy is aided by normal, physiological function of neural circuits during sleep that are driven by pathological signals. Studies recording multiple, single neurons prior to spontaneous seizures have shown that neural assemblies activated prior to the start of seizures were reactivated during post-seizure sleep, similar to the reactivation of behavioral neural assemblies, which is thought to be involved in the formation of long-term memories, a process known as Memory Consolidation. The reactivation of seizure-related neural assemblies during sleep was thus described as being a component of Seizure-Related Consolidation (SRC). These results further suggest that SRC may viewed as a network-related aspect of epilepsy, even in those seizures that have anatomically restricted neuroanatomical origins. As suggested by the Network Theory of Epilepsy as a means of interfering with ictogenesis, therapies that interfered with SRC may provide some anti-epileptogenic therapeutic benefit, even if the interference targeted structures that were not involved originally in the seizure. Here, we show how the Network Theory of Epilepsy can be expanded to include neural plasticity mechanisms associated with learning by providing an overview of Memory Consolidation, the mechanisms thought to underlie MC, their relation to Seizure-Related Consolidation, and suggesting novel, anti-epileptogenic therapies targeting interference with network activation in epilepsy following seizures during post-seizure sleep.
Collapse
Affiliation(s)
- Mark R Bower
- Department of Neurology, Yale University, New Haven, CT, United States
| |
Collapse
|
2
|
Salners T, Dahmen KA, Beggs J. Simple model for the prediction of seizure durations. Phys Rev E 2024; 110:014401. [PMID: 39161021 DOI: 10.1103/physreve.110.014401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 06/12/2024] [Indexed: 08/21/2024]
Abstract
A simple model is used to simulate seizures in a population of spiking excitatory neurons experiencing a uniform effect from inhibitory neurons. A key feature is introduced into the model, i.e., a mechanism that weakens the firing thresholds. This weakening mechanism adds memory to the dynamics. We find a seizure-prone state in a "mode-switching" phase. In this phase, the system can suddenly switch from a "healthy" state with small scale-free avalanches to a "seizure" state with almost periodic large avalanches ("seizures"). Simulations of the model predict statistics for the average time spent in the seizure state (the seizure "duration") that agree with experiments and theoretical examples of similar behavior in neuronal systems. Our study points to. different connections between seizures and fracture and also offers an alternative view on the type of critical point controlling neuronal avalanches.
Collapse
|
3
|
Lai S, Zhang L, Tu X, Ma X, Song Y, Cao K, Li M, Meng J, Shi Y, Wu Q, Yang C, Lan Z, Lau CG, Shi J, Ma W, Li S, Xue YX, Huang Z. Termination of convulsion seizures by destabilizing and perturbing seizure memory engrams. SCIENCE ADVANCES 2024; 10:eadk9484. [PMID: 38507477 PMCID: PMC10954199 DOI: 10.1126/sciadv.adk9484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 02/13/2024] [Indexed: 03/22/2024]
Abstract
Epileptogenesis, arising from alterations in synaptic strength, shares mechanistic and phenotypic parallels with memory formation. However, direct evidence supporting the existence of seizure memory remains scarce. Leveraging a conditioned seizure memory (CSM) paradigm, we found that CSM enabled the environmental cue to trigger seizure repetitively, and activating cue-responding engram cells could generate CSM artificially. Moreover, cue exposure initiated an analogous process of memory reconsolidation driven by mammalian target of rapamycin-brain-derived neurotrophic factor signaling. Pharmacological targeting of the mammalian target of rapamycin pathway within a limited time window reduced seizures in animals and interictal epileptiform discharges in patients with refractory seizures. Our findings reveal a causal link between seizure memory engrams and seizures, which leads us to a deeper understanding of epileptogenesis and points to a promising direction for epilepsy treatment.
Collapse
Affiliation(s)
- Shirong Lai
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China
- School of Health Management, Xihua University, Chengdu 610039, China
| | - Libo Zhang
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China
- Shenzhen Public Service Platform for Clinical Application of Medical Imaging, Shenzhen Key Laboratory for Drug Addiction and Medication Safety, Department of Ultrasound, Peking University Shenzhen Hospital, Shenzhen-PKU-HKUST Medical Center, Shenzhen 518036, China
| | - Xinyu Tu
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Xinyue Ma
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Yujing Song
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Kexin Cao
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China
- Department of Pharmacology, School of Basic Medical Sciences, Peking University, Beijing 100191, China
| | - Miaomiao Li
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang 110022, China
| | - Jihong Meng
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang 110022, China
| | - Yiqiang Shi
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Qing Wu
- School of Health Management, Xihua University, Chengdu 610039, China
| | - Chen Yang
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Zifan Lan
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China
| | | | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China
| | - Weining Ma
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang 110022, China
| | - Shaoyi Li
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang 110022, China
| | - Yan-Xue Xue
- National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Zhuo Huang
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| |
Collapse
|
4
|
Bröhl T, Rings T, Pukropski J, von Wrede R, Lehnertz K. The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 3:1338864. [PMID: 38293249 PMCID: PMC10825060 DOI: 10.3389/fnetp.2023.1338864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 12/19/2023] [Indexed: 02/01/2024]
Abstract
Epilepsy is now considered a network disease that affects the brain across multiple levels of spatial and temporal scales. The paradigm shift from an epileptic focus-a discrete cortical area from which seizures originate-to a widespread epileptic network-spanning lobes and hemispheres-considerably advanced our understanding of epilepsy and continues to influence both research and clinical treatment of this multi-faceted high-impact neurological disorder. The epileptic network, however, is not static but evolves in time which requires novel approaches for an in-depth characterization. In this review, we discuss conceptual basics of network theory and critically examine state-of-the-art recording techniques and analysis tools used to assess and characterize a time-evolving human epileptic brain network. We give an account on current shortcomings and highlight potential developments towards an improved clinical management of epilepsy.
Collapse
Affiliation(s)
- Timo Bröhl
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
| | - Thorsten Rings
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
| | - Jan Pukropski
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Randi von Wrede
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Klaus Lehnertz
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
- Interdisciplinary Center for Complex Systems, University of Bonn, Bonn, Germany
| |
Collapse
|
5
|
Schroeder GM, Karoly PJ, Maturana M, Panagiotopoulou M, Taylor PN, Cook MJ, Wang Y. Chronic intracranial EEG recordings and interictal spike rate reveal multiscale temporal modulations in seizure states. Brain Commun 2023; 5:fcad205. [PMID: 37693811 PMCID: PMC10484289 DOI: 10.1093/braincomms/fcad205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 06/07/2023] [Accepted: 07/18/2023] [Indexed: 09/12/2023] Open
Abstract
Many biological processes are modulated by rhythms on circadian and multidien timescales. In focal epilepsy, various seizure features, such as spread and duration, can change from one seizure to the next within the same patient. However, the specific timescales of this variability, as well as the specific seizure characteristics that change over time, are unclear. Here, in a cross-sectional observational study, we analysed within-patient seizure variability in 10 patients with chronic intracranial EEG recordings (185-767 days of recording time, 57-452 analysed seizures/patient). We characterized the seizure evolutions as sequences of a finite number of patient-specific functional seizure network states. We then compared seizure network state occurrence and duration to (1) time since implantation and (2) patient-specific circadian and multidien cycles in interictal spike rate. In most patients, the occurrence or duration of at least one seizure network state was associated with the time since implantation. Some patients had one or more seizure network states that were associated with phases of circadian and/or multidien spike rate cycles. A given seizure network state's occurrence and duration were usually not associated with the same timescale. Our results suggest that different time-varying factors modulate within-patient seizure evolutions over multiple timescales, with separate processes modulating a seizure network state's occurrence and duration. These findings imply that the development of time-adaptive treatments in epilepsy must account for several separate properties of epileptic seizures and similar principles likely apply to other neurological conditions.
Collapse
Affiliation(s)
- Gabrielle M Schroeder
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Philippa J Karoly
- Graeme Clark Institute and St Vincent’s Hospital, University of Melbourne, Parkville, Victoria 3010, Australia
- Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Matias Maturana
- Graeme Clark Institute and St Vincent’s Hospital, University of Melbourne, Parkville, Victoria 3010, Australia
- Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
- Research Department, Seer Medical Pty Ltd., Melbourne, Victoria 3000, Australia
| | - Mariella Panagiotopoulou
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Peter N Taylor
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
- UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Mark J Cook
- Graeme Clark Institute and St Vincent’s Hospital, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Yujiang Wang
- CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
- UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
| |
Collapse
|
6
|
Issa NP, Nunn KC, Wu S, Haider HA, Tao JX. Putative roles for homeostatic plasticity in epileptogenesis. Epilepsia 2023; 64:539-552. [PMID: 36617338 PMCID: PMC10015501 DOI: 10.1111/epi.17500] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 01/04/2023] [Accepted: 01/05/2023] [Indexed: 01/09/2023]
Abstract
Homeostatic plasticity allows neural circuits to maintain an average activity level while preserving the ability to learn new associations and efficiently transmit information. This dynamic process usually protects the brain from excessive activity, like seizures. However, in certain contexts, homeostatic plasticity might produce seizures, either in response to an acute provocation or more chronically as a driver of epileptogenesis. Here, we review three seizure conditions in which homeostatic plasticity likely plays an important role: acute drug withdrawal seizures, posttraumatic or disconnection epilepsy, and cyclic seizures. Identifying the homeostatic mechanisms active at different stages of development and in different circuits could allow better targeting of therapies, including determining when neuromodulation might be most effective, proposing ways to prevent epileptogenesis, and determining how to disrupt the cycle of recurring seizure clusters.
Collapse
Affiliation(s)
- Naoum P. Issa
- Comprehensive Epilepsy Center, Department of Neurology, 5841 S. Maryland Ave., MC 2030, University of Chicago, Chicago, IL 60637
| | | | - Shasha Wu
- Comprehensive Epilepsy Center, Department of Neurology, 5841 S. Maryland Ave., MC 2030, University of Chicago, Chicago, IL 60637
| | - Hiba A. Haider
- Comprehensive Epilepsy Center, Department of Neurology, 5841 S. Maryland Ave., MC 2030, University of Chicago, Chicago, IL 60637
| | - James X. Tao
- Comprehensive Epilepsy Center, Department of Neurology, 5841 S. Maryland Ave., MC 2030, University of Chicago, Chicago, IL 60637
| |
Collapse
|
7
|
Lehnertz K, Bröhl T, Wrede RV. Epileptic-network-based prediction and control of seizures in humans. Neurobiol Dis 2023; 181:106098. [PMID: 36997129 DOI: 10.1016/j.nbd.2023.106098] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 03/08/2023] [Accepted: 03/22/2023] [Indexed: 03/30/2023] Open
Abstract
Epilepsy is now conceptualized as a network disease. The epileptic brain network comprises structurally and functionally connected cortical and subcortical brain regions - spanning lobes and hemispheres -, whose connections and dynamics evolve in time. With this concept, focal and generalized seizures as well as other related pathophysiological phenomena are thought to emerge from, spread via, and be terminated by network vertices and edges that also generate and sustain normal, physiological brain dynamics. Research over the last years has advanced concepts and techniques to identify and characterize the evolving epileptic brain network and its constituents on various spatial and temporal scales. Network-based approaches further our understanding of how seizures emerge from the evolving epileptic brain network, and they provide both novel insights into pre-seizure dynamics and important clues for success or failure of measures for network-based seizure control and prevention. In this review, we summarize the current state of knowledge and address several important challenges that would need to be addressed to move network-based prediction and control of seizures closer to clinical translation.
Collapse
Affiliation(s)
- Klaus Lehnertz
- Department of Epileptology, University of Bonn Medical Centre, Venusberg Campus 1, 53127 Bonn, Germany; Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn, Germany; Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53175 Bonn, Germany.
| | - Timo Bröhl
- Department of Epileptology, University of Bonn Medical Centre, Venusberg Campus 1, 53127 Bonn, Germany; Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn, Germany
| | - Randi von Wrede
- Department of Epileptology, University of Bonn Medical Centre, Venusberg Campus 1, 53127 Bonn, Germany
| |
Collapse
|
8
|
Hagemann A, Wilting J, Samimizad B, Mormann F, Priesemann V. Assessing criticality in pre-seizure single-neuron activity of human epileptic cortex. PLoS Comput Biol 2021; 17:e1008773. [PMID: 33684101 PMCID: PMC7971851 DOI: 10.1371/journal.pcbi.1008773] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Revised: 03/18/2021] [Accepted: 02/04/2021] [Indexed: 11/18/2022] Open
Abstract
Epileptic seizures are characterized by abnormal and excessive neural activity, where cortical network dynamics seem to become unstable. However, most of the time, during seizure-free periods, cortex of epilepsy patients shows perfectly stable dynamics. This raises the question of how recurring instability can arise in the light of this stable default state. In this work, we examine two potential scenarios of seizure generation: (i) epileptic cortical areas might generally operate closer to instability, which would make epilepsy patients generally more susceptible to seizures, or (ii) epileptic cortical areas might drift systematically towards instability before seizure onset. We analyzed single-unit spike recordings from both the epileptogenic (focal) and the nonfocal cortical hemispheres of 20 epilepsy patients. We quantified the distance to instability in the framework of criticality, using a novel estimator, which enables an unbiased inference from a small set of recorded neurons. Surprisingly, we found no evidence for either scenario: Neither did focal areas generally operate closer to instability, nor were seizures preceded by a drift towards instability. In fact, our results from both pre-seizure and seizure-free intervals suggest that despite epilepsy, human cortex operates in the stable, slightly subcritical regime, just like cortex of other healthy mammalians.
Collapse
Affiliation(s)
- Annika Hagemann
- Max-Planck-Institute for Dynamics and Self-Organization, Göttingen, Germany
| | - Jens Wilting
- Max-Planck-Institute for Dynamics and Self-Organization, Göttingen, Germany
| | - Bita Samimizad
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Florian Mormann
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Viola Priesemann
- Max-Planck-Institute for Dynamics and Self-Organization, Göttingen, Germany
- Bernstein Center for Computational Neuroscience (BCCN) Göttingen, Germany
| |
Collapse
|
9
|
Varley TF, Sporns O, Puce A, Beggs J. Differential effects of propofol and ketamine on critical brain dynamics. PLoS Comput Biol 2020; 16:e1008418. [PMID: 33347455 PMCID: PMC7785236 DOI: 10.1371/journal.pcbi.1008418] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 01/05/2021] [Accepted: 10/05/2020] [Indexed: 11/18/2022] Open
Abstract
Whether the brain operates at a critical "tipping" point is a long standing scientific question, with evidence from both cellular and systems-scale studies suggesting that the brain does sit in, or near, a critical regime. Neuroimaging studies of humans in altered states of consciousness have prompted the suggestion that maintenance of critical dynamics is necessary for the emergence of consciousness and complex cognition, and that reduced or disorganized consciousness may be associated with deviations from criticality. Unfortunately, many of the cellular-level studies reporting signs of criticality were performed in non-conscious systems (in vitro neuronal cultures) or unconscious animals (e.g. anaesthetized rats). Here we attempted to address this knowledge gap by exploring critical brain dynamics in invasive ECoG recordings from multiple sessions with a single macaque as the animal transitioned from consciousness to unconsciousness under different anaesthetics (ketamine and propofol). We use a previously-validated test of criticality: avalanche dynamics to assess the differences in brain dynamics between normal consciousness and both drug-states. Propofol and ketamine were selected due to their differential effects on consciousness (ketamine, but not propofol, is known to induce an unusual state known as "dissociative anaesthesia"). Our analyses indicate that propofol dramatically restricted the size and duration of avalanches, while ketamine allowed for more awake-like dynamics to persist. In addition, propofol, but not ketamine, triggered a large reduction in the complexity of brain dynamics. All states, however, showed some signs of persistent criticality when testing for exponent relations and universal shape-collapse. Further, maintenance of critical brain dynamics may be important for regulation and control of conscious awareness.
Collapse
Affiliation(s)
- Thomas F. Varley
- Psychological & Brain Sciences, Indiana University, Bloomington, Indiana, USA
- School of Informatics, Indiana University, Bloomington, Indiana, USA
| | - Olaf Sporns
- Psychological & Brain Sciences, Indiana University, Bloomington, Indiana, USA
| | - Aina Puce
- Psychological & Brain Sciences, Indiana University, Bloomington, Indiana, USA
| | - John Beggs
- Department of Physics, Indiana University, Bloomington, Indiana, USA
| |
Collapse
|
10
|
Zaveri HP, Schelter B, Schevon CA, Jiruska P, Jefferys JGR, Worrell G, Schulze-Bonhage A, Joshi RB, Jirsa V, Goodfellow M, Meisel C, Lehnertz K. Controversies on the network theory of epilepsy: Debates held during the ICTALS 2019 conference. Seizure 2020; 78:78-85. [PMID: 32272333 DOI: 10.1016/j.seizure.2020.03.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 03/13/2020] [Accepted: 03/15/2020] [Indexed: 12/21/2022] Open
Abstract
Debates on six controversial topics on the network theory of epilepsy were held during two debate sessions, as part of the International Conference for Technology and Analysis of Seizures, 2019 (ICTALS 2019) convened at the University of Exeter, UK, September 2-5 2019. The debate topics were (1) From pathologic to physiologic: is the epileptic network part of an existing large-scale brain network? (2) Are micro scale recordings pertinent for defining the epileptic network? (3) From seconds to years: do we need all temporal scales to define an epileptic network? (4) Is it necessary to fully define the epileptic network to control it? (5) Is controlling seizures sufficient to control the epileptic network? (6) Does the epileptic network want to be controlled? This article, written by the organizing committee for the debate sessions and the debaters, summarizes the arguments presented during the debates on these six topics.
Collapse
Affiliation(s)
- Hitten P Zaveri
- Department of Neurology, Yale University, New Haven, CT 06520, USA
| | - Björn Schelter
- Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen AB24 3UE, UK
| | | | - Premysl Jiruska
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - John G R Jefferys
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic; Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK
| | - Gregory Worrell
- Mayo Systems Electrophysiology Laboratory, Departments of Neurology and Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Rasesh B Joshi
- Department of Neurobiology and Anatomy, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, Aix Marseille University, Marseille, France
| | - Marc Goodfellow
- Living Systems Institute, University of Exeter, Exeter, UK; Wellcome Trust Centre for Biomedical Modelling and Analysis, University of Exeter, Exeter, UK; EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, UK
| | - Christian Meisel
- Department of Neurology, Boston Children's Hospital, 300 Longwood Ave, Boston, MA 02115, USA; Department of Neurology, University Clinic Carl Gustav Carus, Fetscherstrasse 74, 01307 Dresden, Germany
| | - Klaus Lehnertz
- Department of Epileptology, University of Bonn, Venusberg Campus 1, 53127 Bonn, Germany; Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Str. 7, 53175 Bonn, Germany.
| |
Collapse
|
11
|
Palaniyappan L. Inefficient neural system stabilization: a theory of spontaneous resolutions and recurrent relapses in psychosis. J Psychiatry Neurosci 2019; 44:367-383. [PMID: 31245961 PMCID: PMC6821513 DOI: 10.1503/jpn.180038] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 02/07/2019] [Accepted: 03/05/2019] [Indexed: 12/21/2022] Open
Abstract
A striking feature of psychosis is its heterogeneity. Presentations of psychosis vary from transient symptoms with no functional consequence in the general population to a tenacious illness at the other extreme, with a wide range of variable trajectories in between. Even among patients with schizophrenia, who are diagnosed on the basis of persistent deterioration, marked variation is seen in response to treatment, frequency of relapses and degree of eventual recovery. Existing theoretical accounts of psychosis focus almost exclusively on how symptoms are initially formed, with much less emphasis on explaining their variable course. In this review, I present an account that links several existing notions of the biology of psychosis with the variant clinical trajectories. My aim is to incorporate perspectives of systems neuroscience in a staging framework to explain the individual variations in illness course that follow the onset of psychosis.
Collapse
Affiliation(s)
- Lena Palaniyappan
- From the Department of Psychiatry and Robarts Research Institute, University of Western Ontario and Lawson Health Research Institute, London, Ont., Canada
| |
Collapse
|
12
|
Precursors of seizures due to specific spatial-temporal modifications of evolving large-scale epileptic brain networks. Sci Rep 2019; 9:10623. [PMID: 31337840 PMCID: PMC6650408 DOI: 10.1038/s41598-019-47092-w] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 07/10/2019] [Indexed: 12/25/2022] Open
Abstract
Knowing when, where, and how seizures are initiated in large-scale epileptic brain networks remains a widely unsolved problem. Seizure precursors – changes in brain dynamics predictive of an impending seizure – can now be identified well ahead of clinical manifestations, but either the seizure onset zone or remote brain areas are reported as network nodes from which seizure precursors emerge. We aimed to shed more light on the role of constituents of evolving epileptic networks that recurrently transit into and out of seizures. We constructed such networks from more than 3200 hours of continuous intracranial electroencephalograms recorded in 38 patients with medication refractory epilepsy. We succeeded in singling out predictive edges and predictive nodes. Their particular characteristics, namely edge weight respectively node centrality (a fundamental concept of network theory), from the pre-ictal periods of 78 out of 97 seizures differed significantly from the characteristics seen during inter-ictal periods. The vast majority of predictive nodes were connected by most of the predictive edges, but these nodes never played a central role in the evolving epileptic networks. Interestingly, predictive nodes were entirely associated with brain regions deemed unaffected by the focal epileptic process. We propose a network mechanism for a transition into the pre-seizure state, which puts into perspective the role of the seizure onset zone in this transition and highlights the necessity to reassess current concepts for seizure generation and seizure prevention.
Collapse
|
13
|
Deep brain stimulation probing performance is enhanced by pairing stimulus with epileptic seizure. Epilepsy Behav 2018; 88:380-387. [PMID: 30352775 DOI: 10.1016/j.yebeh.2018.09.048] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2018] [Revised: 09/27/2018] [Accepted: 09/27/2018] [Indexed: 11/19/2022]
Abstract
The unpredictability of spontaneous and recurrent seizures significantly impairs the quality of life of patients with epilepsy. Probing neural network excitability with deep brain electrical stimulation (DBS) has shown promising results predicting pathological shifts in brain states. This work presents a proof-of-principal that active electroencephalographic (EEG) probing, as a seizure predictive tool, is enhanced by pairing DBS and the electrographic seizure itself. The ictogenic model used consisted of inducing seizures by continuous intravenous infusion of pentylenetetrazol (PTZ - 2.5 mg/ml/min) while a probing DBS was delivered to the thalamus (TH) or amygdaloid complex to detect changes prior to seizure onset. Cortical electrophysiological recordings were performed before, during, and after PTZ infusion. Thalamic DBS probing, but not amygdaloid, was able to predict seizure onset without any observable proconvulsant effects. However, previously pairing amygdaloid DBS and epileptic polyspike discharges (day-1) elicited distinct preictal cortically recorded evoked response (CRER) (day-2) when compared with control groups that received the same amount of electrical pulses at different moments of the ictogenic progress at day-1. In conclusion, our results have demonstrated that the pairing strategy potentiated the detection of an altered brain state prior to the seizure onset. The EEG probing enhancement method opens many possibilities for both diagnosis and treatment of epilepsy.
Collapse
|
14
|
Karoly PJ, Kuhlmann L, Soudry D, Grayden DB, Cook MJ, Freestone DR. Seizure pathways: A model-based investigation. PLoS Comput Biol 2018; 14:e1006403. [PMID: 30307937 PMCID: PMC6199000 DOI: 10.1371/journal.pcbi.1006403] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2018] [Revised: 10/23/2018] [Accepted: 07/26/2018] [Indexed: 02/06/2023] Open
Abstract
We present the results of a model inversion algorithm for electrocorticography (ECoG) data recorded during epileptic seizures. The states and parameters of neural mass models were tracked during a total of over 3000 seizures from twelve patients with focal epilepsy. These models provide an estimate of the effective connectivity within intracortical circuits over the time course of seizures. Observing the dynamics of effective connectivity provides insight into mechanisms of seizures. Estimation of patients seizure dynamics revealed: 1) a highly stereotyped pattern of evolution for each patient, 2) distinct sub-groups of onset mechanisms amongst patients, and 3) different offset mechanisms for long and short seizures. Stereotypical dynamics suggest that, once initiated, seizures follow a deterministic path through the parameter space of a neural model. Furthermore, distinct sub-populations of patients were identified based on characteristic motifs in the dynamics at seizure onset. There were also distinct patterns between long and short duration seizures that were related to seizure offset. Understanding how these different patterns of seizure evolution arise may provide new insights into brain function and guide treatment for epilepsy, since specific therapies may have preferential effects on the various parameters that could potentially be individualized. Methods that unite computational models with data provide a powerful means to generate testable hypotheses for further experimental research. This work provides a demonstration that the hidden connectivity parameters of a neural mass model can be dynamically inferred from data. Our results underscore the power of theoretical models to inform epilepsy management. It is our hope that this work guides further efforts to apply computational models to clinical data.
Collapse
Affiliation(s)
- Philippa J Karoly
- Department of Biomedical Engineering, The University of Melbourne, Parkville, Australia
- Department of Medicine, St Vincent's Hospital, The University of Melbourne, Fitzroy, Australia
| | - Levin Kuhlmann
- Brain Dynamics Lab, Swinburne University of Technology, Hawthorn, Australia
- Centre for Neural Engineering, The University of Melbourne, Parkville, Australia
| | - Daniel Soudry
- Department of Electrical Engineering, Technion, Haifa, Israel
| | - David B Grayden
- Department of Biomedical Engineering, The University of Melbourne, Parkville, Australia
- Centre for Neural Engineering, The University of Melbourne, Parkville, Australia
| | - Mark J Cook
- Department of Medicine, St Vincent's Hospital, The University of Melbourne, Fitzroy, Australia
| | - Dean R Freestone
- Department of Medicine, St Vincent's Hospital, The University of Melbourne, Fitzroy, Australia
- Seer Medical Pty, Melbourne, Australia
| |
Collapse
|
15
|
Koepp MJ, Caciagli L, Pressler RM, Lehnertz K, Beniczky S. Reflex seizures, traits, and epilepsies: from physiology to pathology. Lancet Neurol 2015; 15:92-105. [PMID: 26627365 DOI: 10.1016/s1474-4422(15)00219-7] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Revised: 08/11/2015] [Accepted: 08/13/2015] [Indexed: 10/22/2022]
Abstract
Epileptic seizures are generally unpredictable and arise spontaneously. Patients often report non-specific triggers such as stress or sleep deprivation, but only rarely do seizures occur as a reflex event, in which they are objectively and consistently modulated, precipitated, or inhibited by external sensory stimuli or specific cognitive processes. The seizures triggered by such stimuli and processes in susceptible individuals can have different latencies. Once seizure-suppressing mechanisms fail and a critical mass (the so-called tipping point) of cortical activation is reached, reflex seizures stereotypically manifest with common motor features independent of the physiological network involved. The complexity of stimuli increases from simple sensory to complex cognitive-emotional with increasing age of onset. The topography of physiological networks involved follows the posterior-to-anterior trajectory of brain development, reflecting age-related changes in brain excitability. Reflex seizures and traits probably represent the extremes of a continuum, and understanding of their underlying mechanisms might help to elucidate the transition of normal physiological function to paroxysmal epileptic activity.
Collapse
Affiliation(s)
- Matthias J Koepp
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Institute of Neurology, London, UK; National Hospital for Neurology and Neurosurgery, Queen Square, UK.
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Institute of Neurology, London, UK; National Hospital for Neurology and Neurosurgery, Queen Square, UK
| | - Ronit M Pressler
- Department of Clinical Neurophysiology, Great Ormond Street Hospital, London, UK; Clinical Neuroscience, UCL Institute of Child Health, London, UK
| | - Klaus Lehnertz
- Department of Epileptology, University Hospital of Bonn, Bonn, Germany
| | - Sándor Beniczky
- Department of Clinical Neurophysiology, Danish Epilepsy Centre, Dianalund, Denmark; Department of Clinical Neurophysiology, Aarhus University, Aarhus, Denmark
| |
Collapse
|
16
|
Hesse J, Gross T. Self-organized criticality as a fundamental property of neural systems. Front Syst Neurosci 2014; 8:166. [PMID: 25294989 PMCID: PMC4171833 DOI: 10.3389/fnsys.2014.00166] [Citation(s) in RCA: 198] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2014] [Accepted: 08/25/2014] [Indexed: 11/19/2022] Open
Abstract
The neural criticality hypothesis states that the brain may be poised in a critical state at a boundary between different types of dynamics. Theoretical and experimental studies show that critical systems often exhibit optimal computational properties, suggesting the possibility that criticality has been evolutionarily selected as a useful trait for our nervous system. Evidence for criticality has been found in cell cultures, brain slices, and anesthetized animals. Yet, inconsistent results were reported for recordings in awake animals and humans, and current results point to open questions about the exact nature and mechanism of criticality, as well as its functional role. Therefore, the criticality hypothesis has remained a controversial proposition. Here, we provide an account of the mathematical and physical foundations of criticality. In the light of this conceptual framework, we then review and discuss recent experimental studies with the aim of identifying important next steps to be taken and connections to other fields that should be explored.
Collapse
Affiliation(s)
- Janina Hesse
- Computational Neurophysiology Group, Institute for Theoretical Biology, Humboldt Universität zu Berlin Berlin, Germany ; Bernstein Center for Computational Neuroscience Berlin Berlin, Germany ; École Normale Supérieure Paris, France
| | - Thilo Gross
- Department of Engineering Mathematics, Merchant Venturers School of Engineering, University of Bristol Bristol, UK
| |
Collapse
|
17
|
Priesemann V, Wibral M, Valderrama M, Pröpper R, Le Van Quyen M, Geisel T, Triesch J, Nikolić D, Munk MHJ. Spike avalanches in vivo suggest a driven, slightly subcritical brain state. Front Syst Neurosci 2014; 8:108. [PMID: 25009473 PMCID: PMC4068003 DOI: 10.3389/fnsys.2014.00108] [Citation(s) in RCA: 159] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2014] [Accepted: 05/21/2014] [Indexed: 11/15/2022] Open
Abstract
In self-organized critical (SOC) systems avalanche size distributions follow power-laws. Power-laws have also been observed for neural activity, and so it has been proposed that SOC underlies brain organization as well. Surprisingly, for spiking activity in vivo, evidence for SOC is still lacking. Therefore, we analyzed highly parallel spike recordings from awake rats and monkeys, anesthetized cats, and also local field potentials from humans. We compared these to spiking activity from two established critical models: the Bak-Tang-Wiesenfeld model, and a stochastic branching model. We found fundamental differences between the neural and the model activity. These differences could be overcome for both models through a combination of three modifications: (1) subsampling, (2) increasing the input to the model (this way eliminating the separation of time scales, which is fundamental to SOC and its avalanche definition), and (3) making the model slightly sub-critical. The match between the neural activity and the modified models held not only for the classical avalanche size distributions and estimated branching parameters, but also for two novel measures (mean avalanche size, and frequency of single spikes), and for the dependence of all these measures on the temporal bin size. Our results suggest that neural activity in vivo shows a mélange of avalanches, and not temporally separated ones, and that their global activity propagation can be approximated by the principle that one spike on average triggers a little less than one spike in the next step. This implies that neural activity does not reflect a SOC state but a slightly sub-critical regime without a separation of time scales. Potential advantages of this regime may be faster information processing, and a safety margin from super-criticality, which has been linked to epilepsy.
Collapse
Affiliation(s)
- Viola Priesemann
- Department of Non-linear Dynamics, Max Planck Institute for Dynamics and Self-Organization Göttingen, Germany ; Bernstein Center for Computational Neuroscience Göttingen, Germany ; Frankfurt Institute for Advanced Studies Frankfurt, Germany ; Department of Neurophysiology, Max Planck Institute for Brain Research Frankfurt, Germany
| | - Michael Wibral
- Magnetoencephalography Unit, Brain Imaging Center, Johann Wolfgang Goethe University Frankfurt, Germany ; Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society Frankfurt, Germany
| | - Mario Valderrama
- Department of Biomedical Engineering, University of Los Andes Bogotá, Colombia
| | - Robert Pröpper
- Neural Information Processing Group, Department of Software Engineering and Theoretical Computer Science, TU Berlin Berlin, Germany ; Bernstein Center for Computational Neuroscience Berlin, Germany
| | - Michel Le Van Quyen
- Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière, Hôpital de la Pitié-Salpêtrière, INSERM UMRS 975-CNRS UMR 7225-UPMC Paris, France
| | - Theo Geisel
- Department of Non-linear Dynamics, Max Planck Institute for Dynamics and Self-Organization Göttingen, Germany ; Bernstein Center for Computational Neuroscience Göttingen, Germany
| | - Jochen Triesch
- Frankfurt Institute for Advanced Studies Frankfurt, Germany
| | - Danko Nikolić
- Frankfurt Institute for Advanced Studies Frankfurt, Germany ; Department of Neurophysiology, Max Planck Institute for Brain Research Frankfurt, Germany ; Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society Frankfurt, Germany ; Department of Psychology, Faculty of Humanities and Social Sciences, University of Zagreb Zagreb, Croatia
| | - Matthias H J Munk
- Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics Tübingen, Germany
| |
Collapse
|
18
|
Priesemann V, Valderrama M, Wibral M, Le Van Quyen M. Neuronal avalanches differ from wakefulness to deep sleep--evidence from intracranial depth recordings in humans. PLoS Comput Biol 2013; 9:e1002985. [PMID: 23555220 PMCID: PMC3605058 DOI: 10.1371/journal.pcbi.1002985] [Citation(s) in RCA: 110] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2012] [Accepted: 01/25/2013] [Indexed: 12/20/2022] Open
Abstract
Neuronal activity differs between wakefulness and sleep states. In contrast, an attractor state, called self-organized critical (SOC), was proposed to govern brain dynamics because it allows for optimal information coding. But is the human brain SOC for each vigilance state despite the variations in neuronal dynamics? We characterized neuronal avalanches--spatiotemporal waves of enhanced activity--from dense intracranial depth recordings in humans. We showed that avalanche distributions closely follow a power law--the hallmark feature of SOC--for each vigilance state. However, avalanches clearly differ with vigilance states: slow wave sleep (SWS) shows large avalanches, wakefulness intermediate, and rapid eye movement (REM) sleep small ones. Our SOC model, together with the data, suggested first that the differences are mediated by global but tiny changes in synaptic strength, and second, that the changes with vigilance states reflect small deviations from criticality to the subcritical regime, implying that the human brain does not operate at criticality proper but close to SOC. Independent of criticality, the analysis confirms that SWS shows increased correlations between cortical areas, and reveals that REM sleep shows more fragmented cortical dynamics.
Collapse
Affiliation(s)
- Viola Priesemann
- Department of Neural Systems and Coding, Max Planck Institute for Brain Research, Frankfurt, Germany.
| | | | | | | |
Collapse
|
19
|
Bodner M, Turner RP, Schwacke J, Bowers C, Norment C. Reduction of seizure occurrence from exposure to auditory stimulation in individuals with neurological handicaps: a randomized controlled trial. PLoS One 2012; 7:e45303. [PMID: 23071510 PMCID: PMC3469625 DOI: 10.1371/journal.pone.0045303] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2012] [Accepted: 08/20/2012] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND The purpose of this work was to determine in a clinical trial the efficacy of reducing or preventing seizures in patients with neurological handicaps through sustained cortical activation evoked by passive exposure to a specific auditory stimulus (particular music). The specific type of stimulation had been determined in previous studies to evoke anti-epileptiform/anti-seizure brain activity. METHODS The study was conducted at the Thad E. Saleeby Center in Harstville, South Carolina, which is a permanent residence for individuals with heterogeneous neurological impairments, many with epilepsy. We investigated the ability to reduce or prevent seizures in subjects through cortical stimulation from sustained passive nightly exposure to a specific auditory stimulus (music) in a three-year randomized controlled study. In year 1, baseline seizure rates were established. In year 2, subjects were randomly assigned to treatment and control groups. Treatment group subjects were exposed during sleeping hours to specific music at regular intervals. Control subjects received no music exposure and were maintained on regular anti-seizure medication. In year 3, music treatment was terminated and seizure rates followed. We found a significant treatment effect (p = 0.024) during the treatment phase persisting through the follow-up phase (p = 0.002). Subjects exposed to treatment exhibited a significant 24% decrease in seizures during the treatment phase, and a 33% decrease persisting through the follow-up phase. Twenty-four percent of treatment subjects exhibited a complete absence of seizures during treatment. CONCLUSION/SIGNIFICANCE Exposure to specific auditory stimuli (i.e. music) can significantly reduce seizures in subjects with a range of epilepsy and seizure types, in some cases achieving a complete cessation of seizures. These results are consistent with previous work showing reductions in epileptiform activity from particular music exposure and offers potential for achieving a non-invasive, non-pharmacologic treatment of epilepsy. TRIAL REGISTRATION Clinicaltrials.gov NCT01459692.
Collapse
Affiliation(s)
- Mark Bodner
- MIND Research Institute, Santa Ana, California, United States of America
- Department of Neurosurgery, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Robert P. Turner
- Department of Neurosciences, Pediatrics, Epidemiology & Biostatistics, Medical University of South Carolina, Charleston, South Carolina, United States of America
| | - John Schwacke
- Department of Epidemiology and Biostatistics, Medical University of South Carolina, Charleston, South Carolina, United States of America
| | - Christopher Bowers
- Department of Neurosciences, Medical University of South Carolina, Charleston, South Carolina, United States of America
| | - Caroline Norment
- Department of Neurosciences, Medical University of South Carolina, Charleston, South Carolina, United States of America
| |
Collapse
|
20
|
Orzi F, Casolla B, Rocchi R, Fornai F. Prion-like mechanisms in epileptogenesis. Neurol Sci 2012; 34:1035-8. [PMID: 22777569 DOI: 10.1007/s10072-012-1148-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2012] [Accepted: 06/22/2012] [Indexed: 01/06/2023]
Abstract
Epilepsy often follows a focal insult, and develops with a time delay so to reveal a complex cascade of events. Both clinical and experimental findings suggest that the initial insult triggers a self-promoted pathological process, currently named epileptogenesis. An early phase reflects the complex response of the nervous system to the insult, which includes pro-injury and pro-repair mechanisms. Successively, the sprouting and probably neurogenesis and gliosis set up the stage for the onset of spontaneous seizures. Thus, local changes in excitability would cause a functional change within a network, and the altered circuitry would favor the seizures. A latent or clinically silent period, as long as years, may precede epilepsy. In spite of the substantial knowledge on the biochemical and morphological changes associated with epileptogenesis, the mechanisms supposedly underlying the process are still uncertain. The uncertainty refers mostly to the silent period, a stage in which most, if not all, the receptor and ion changes are supposedly settled. It is tempting to explore the nature of the factors promoting the epileptogenesis within the notional field of neurodegeneration. Specifically, several observations converge to support the hypothesis that a prion-like mechanism promotes the "maturation" process underlying epileptogenesis. The mechanism, consistently with data from different neurodegenerative diseases, is predictably associated with deposition of self-aggregating misfolded proteins and changes of the ubiquitin proteasome and autophagy-lysosome pathways.
Collapse
|
21
|
Beggs JM, Timme N. Being critical of criticality in the brain. Front Physiol 2012; 3:163. [PMID: 22701101 PMCID: PMC3369250 DOI: 10.3389/fphys.2012.00163] [Citation(s) in RCA: 247] [Impact Index Per Article: 20.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2012] [Accepted: 05/07/2012] [Indexed: 11/23/2022] Open
Abstract
Relatively recent work has reported that networks of neurons can produce avalanches of activity whose sizes follow a power law distribution. This suggests that these networks may be operating near a critical point, poised between a phase where activity rapidly dies out and a phase where activity is amplified over time. The hypothesis that the electrical activity of neural networks in the brain is critical is potentially important, as many simulations suggest that information processing functions would be optimized at the critical point. This hypothesis, however, is still controversial. Here we will explain the concept of criticality and review the substantial objections to the criticality hypothesis raised by skeptics. Points and counter points are presented in dialog form.
Collapse
Affiliation(s)
- John M Beggs
- Department of Physics, Indiana University Bloomington, IN, USA
| | | |
Collapse
|
22
|
Meisel C, Storch A, Hallmeyer-Elgner S, Bullmore E, Gross T. Failure of adaptive self-organized criticality during epileptic seizure attacks. PLoS Comput Biol 2012; 8:e1002312. [PMID: 22241971 PMCID: PMC3252275 DOI: 10.1371/journal.pcbi.1002312] [Citation(s) in RCA: 101] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2011] [Accepted: 11/02/2011] [Indexed: 11/19/2022] Open
Abstract
Critical dynamics are assumed to be an attractive mode for normal brain functioning as information processing and computational capabilities are found to be optimal in the critical state. Recent experimental observations of neuronal activity patterns following power-law distributions, a hallmark of systems at a critical state, have led to the hypothesis that human brain dynamics could be poised at a phase transition between ordered and disordered activity. A so far unresolved question concerns the medical significance of critical brain activity and how it relates to pathological conditions. Using data from invasive electroencephalogram recordings from humans we show that during epileptic seizure attacks neuronal activity patterns deviate from the normally observed power-law distribution characterizing critical dynamics. The comparison of these observations to results from a computational model exhibiting self-organized criticality (SOC) based on adaptive networks allows further insights into the underlying dynamics. Together these results suggest that brain dynamics deviates from criticality during seizures caused by the failure of adaptive SOC.
Collapse
Affiliation(s)
- Christian Meisel
- Biological Physics Section, Max Planck Institute for the Physics of Complex Systems, Dresden, Germany.
| | | | | | | | | |
Collapse
|
23
|
Aberrant neuronal avalanches in cortical tissue removed from juvenile epilepsy patients. J Clin Neurophysiol 2011; 27:380-6. [PMID: 21076327 DOI: 10.1097/wnp.0b013e3181fdf8d3] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Some forms of epilepsy may arise as a result of pathologic interactions among neurons. Many forms of collective activity have been identified, including waves, spirals, oscillations, synchrony, and neuronal avalanches. All these emergent activity patterns have been hypothesized to show pathologic signatures associated with epilepsy. Here, the authors used 60-channel multielectrode arrays to record neuronal avalanches in cortical tissue removed from juvenile epilepsy patients. For comparison, they also recorded activity in rat cortical slices. The authors found that some human tissue removed from epilepsy patients exhibited prolonged periods of hyperactivity not seen in rat slices. In addition, they found a positive correlation between the branching parameter, a measure of network gain, and firing rate in human slices during periods of hyperactivity. This relationship was not present in rat slices. The authors suggest that this positive correlation between the branching parameter and the firing rate is part of a positive feedback loop and may contribute to some forms of epilepsy. These results also indicate that neuronal avalanches are abnormally regulated in slices removed from pediatric epilepsy patients.
Collapse
|
24
|
Maciejak P, Szyndler J, Lehner M, Turzyńska D, Sobolewska A, Bidziński A, Płaźnik A. The differential effects of protein synthesis inhibition on the expression and reconsolidation of pentylenetetrazole kindled seizures. Epilepsy Behav 2010; 18:193-200. [PMID: 20605533 DOI: 10.1016/j.yebeh.2010.04.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2009] [Revised: 04/06/2010] [Accepted: 04/07/2010] [Indexed: 11/26/2022]
Abstract
This work attempted to answer the question whether the central processes engaged in the memory formation and the epilepsy development are governed by the overlapping mechanisms. The effects of the protein synthesis inhibitor cycloheximide (CHX) were examined on the expression and reconsolidation of pentylenetetrazole (PTZ) - induced kindled seizures and for comparative purposes, on the reconsolidation of conditioned fear response (conditioned freezing). It was found that post-test intracerebroventricular administration of CHX (125microg/5microl) significantly attenuated the expression of a conditioned fear response examined 24h later. Thus, inhibition of de novo brain protein synthesis interfered with the reconsolidation of a conditioned response. CHX given at the same dose repeatedly to fully kindled rats immediately after three consecutive sessions of PTZ-induced seizures (35mg/kg ip) did not modify the strength of convulsions. On the other hand, CHX significantly attenuated the strength of convulsions when the drug was administered 1h before the PTZ injection, which occurred every second day for three consecutive sessions. However, when CHX was omitted in a consecutive session, PTZ induced a fully developed expression of tonic-clonic convulsions, thereby indicating that CHX-induced changes in seizure intensity were transitory. Western Blot analysis confirmed that CHX potently inhibited PTZ-induced protein synthesis (c-Fos) in the rat brain, examined 60min after CHX and PTZ administration. The present findings suggest that the mechanisms underlying kindling are resistant to modification, even under the influence of protein synthesis inhibitors, and that there are important differences between the processes of learning and kindling seizures.
Collapse
Affiliation(s)
- Piotr Maciejak
- Department of Neurochemistry, Institute of Psychiatry and Neurology, 9 Sobieskiego Street, 02-957 Warsaw, Poland.
| | | | | | | | | | | | | |
Collapse
|
25
|
Terry R. Vagus nerve stimulation: a proven therapy for treatment of epilepsy strives to improve efficacy and expand applications. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2010; 2009:4631-4. [PMID: 19963855 DOI: 10.1109/iembs.2009.5332676] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Vagus nerve stimulation (VNS) is an approved therapy for the treatment of adult patients and adolescents aged 12 years and older who have partial onset seizures refractory to antiepileptic medications. More than 50,000 patients worldwide have been implanted with the VNS system. Work continues to understand the mechanism of action of VNS with the goal of improving the treatment, particularly to identify patients who will be helped by VNS, to develop a closed-loop seizure detection system, and to improve the selection of stimulation parameters. VNS has also been approved for treatment-resistant depression, and it may have utility in the treatment of a variety of other medical disorders.
Collapse
Affiliation(s)
- Reese Terry
- Stockholder of Cyberonics Inc., 100 Cyberonics Blvd, Houston, Texas, USA.
| |
Collapse
|
26
|
Chen W, Hobbs JP, Tang A, Beggs JM. A few strong connections: optimizing information retention in neuronal avalanches. BMC Neurosci 2010; 11:3. [PMID: 20053290 PMCID: PMC2824798 DOI: 10.1186/1471-2202-11-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2009] [Accepted: 01/06/2010] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND How living neural networks retain information is still incompletely understood. Two prominent ideas on this topic have developed in parallel, but have remained somewhat unconnected. The first of these, the "synaptic hypothesis," holds that information can be retained in synaptic connection strengths, or weights, between neurons. Recent work inspired by statistical mechanics has suggested that networks will retain the most information when their weights are distributed in a skewed manner, with many weak weights and only a few strong ones. The second of these ideas is that information can be represented by stable activity patterns. Multineuron recordings have shown that sequences of neural activity distributed over many neurons are repeated above chance levels when animals perform well-learned tasks. Although these two ideas are compelling, no one to our knowledge has yet linked the predicted optimum distribution of weights to stable activity patterns actually observed in living neural networks. RESULTS Here, we explore this link by comparing stable activity patterns from cortical slice networks recorded with multielectrode arrays to stable patterns produced by a model with a tunable weight distribution. This model was previously shown to capture central features of the dynamics in these slice networks, including neuronal avalanche cascades. We find that when the model weight distribution is appropriately skewed, it correctly matches the distribution of repeating patterns observed in the data. In addition, this same distribution of weights maximizes the capacity of the network model to retain stable activity patterns. Thus, the distribution that best fits the data is also the distribution that maximizes the number of stable patterns. CONCLUSIONS We conclude that local cortical networks are very likely to use a highly skewed weight distribution to optimize information retention, as predicted by theory. Fixed distributions impose constraints on learning, however. The network must have mechanisms for preserving the overall weight distribution while allowing individual connection strengths to change with learning.
Collapse
Affiliation(s)
- Wei Chen
- Indiana University Department of Physics, 727 East 3rd Street, Bloomington, Indiana, USA
| | - Jon P Hobbs
- Indiana University Department of Physics, 727 East 3rd Street, Bloomington, Indiana, USA
| | - Aonan Tang
- Indiana University Department of Physics, 727 East 3rd Street, Bloomington, Indiana, USA
| | - John M Beggs
- Indiana University Department of Physics, 727 East 3rd Street, Bloomington, Indiana, USA
| |
Collapse
|
27
|
Schachter SC, Guttag J, Schiff SJ, Schomer DL. Advances in the application of technology to epilepsy: the CIMIT/NIO Epilepsy Innovation Summit. Epilepsy Behav 2009; 16:3-46. [PMID: 19780225 PMCID: PMC8118381 DOI: 10.1016/j.yebeh.2009.06.028] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
In 2008, a group of clinicians, scientists, engineers, and industry representatives met to discuss advances in the application of engineering technologies to the diagnosis and treatment of patients with epilepsy. The presentations also provided a guide for further technological development, specifically in the evaluation of patients for epilepsy surgery, seizure onset detection and seizure prediction, intracranial treatment systems, and extracranial treatment systems. This article summarizes the discussions and demonstrates that cross-disciplinary interactions can catalyze collaborations between physicians and engineers to address and solve many of the pressing unmet needs in epilepsy.
Collapse
Affiliation(s)
- Steven C Schachter
- Center for Integration of Medicine and Innovative Technology, Boston, MA, USA.
| | | | | | | |
Collapse
|
28
|
Hsu D, Hsu M. Zwanzig-Mori projection operators and EEG dynamics: deriving a simple equation of motion. PMC BIOPHYSICS 2009; 2:6. [PMID: 19594920 PMCID: PMC2728514 DOI: 10.1186/1757-5036-2-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2009] [Accepted: 07/13/2009] [Indexed: 11/24/2022]
Abstract
We present a macroscopic theory of electroencephalogram (EEG) dynamics based on the laws of motion that govern atomic and molecular motion. The theory is an application of Zwanzig-Mori projection operators. The result is a simple equation of motion that has the form of a generalized Langevin equation (GLE), which requires knowledge only of macroscopic properties. The macroscopic properties can be extracted from experimental data by one of two possible variational principles. These variational principles are our principal contribution to the formalism. Potential applications are discussed, including applications to the theory of critical phenomena in the brain, Granger causality and Kalman filters. PACS code: 87.19.lj
Collapse
Affiliation(s)
- David Hsu
- Department of Neurology, University of Wisconsin, Madison WI, USA.
| | | |
Collapse
|
29
|
Priesemann V, Munk MHJ, Wibral M. Subsampling effects in neuronal avalanche distributions recorded in vivo. BMC Neurosci 2009; 10:40. [PMID: 19400967 PMCID: PMC2697147 DOI: 10.1186/1471-2202-10-40] [Citation(s) in RCA: 82] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2008] [Accepted: 04/29/2009] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Many systems in nature are characterized by complex behaviour where large cascades of events, or avalanches, unpredictably alternate with periods of little activity. Snow avalanches are an example. Often the size distribution f(s) of a system's avalanches follows a power law, and the branching parameter sigma, the average number of events triggered by a single preceding event, is unity. A power law for f(s), and sigma = 1, are hallmark features of self-organized critical (SOC) systems, and both have been found for neuronal activity in vitro. Therefore, and since SOC systems and neuronal activity both show large variability, long-term stability and memory capabilities, SOC has been proposed to govern neuronal dynamics in vivo. Testing this hypothesis is difficult because neuronal activity is spatially or temporally subsampled, while theories of SOC systems assume full sampling. To close this gap, we investigated how subsampling affects f(s) and sigma by imposing subsampling on three different SOC models. We then compared f(s) and sigma of the subsampled models with those of multielectrode local field potential (LFP) activity recorded in three macaque monkeys performing a short term memory task. RESULTS Neither the LFP nor the subsampled SOC models showed a power law for f(s). Both, f(s) and sigma, depended sensitively on the subsampling geometry and the dynamics of the model. Only one of the SOC models, the Abelian Sandpile Model, exhibited f(s) and sigma similar to those calculated from LFP activity. CONCLUSION Since subsampling can prevent the observation of the characteristic power law and sigma in SOC systems, misclassifications of critical systems as sub- or supercritical are possible. Nevertheless, the system specific scaling of f(s) and sigma under subsampling conditions may prove useful to select physiologically motivated models of brain function. Models that better reproduce f(s) and sigma calculated from the physiological recordings may be selected over alternatives.
Collapse
Affiliation(s)
- Viola Priesemann
- Department of Neurophysiology, Max Planck Institute for Brain Research, Deutschordenstrasse 46, D-60528 Frankfurt am Main, Germany.
| | | | | |
Collapse
|