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Frazzini V, Mathon B, Donneger F, Cousyn L, Hanin A, Nguyen-Michel VH, Adam C, Lambrecq V, Dupont S, Poncer JC, Bielle F, Navarro V. Epilepsy related to focal neuronal lipofuscinosis: extra-frontal localization, EEG signatures and GABA involvement. J Neurol 2022; 269:4102-4109. [DOI: 10.1007/s00415-022-11024-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 02/07/2022] [Accepted: 02/11/2022] [Indexed: 12/21/2022]
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Sun J, Li Y, Zhang K, Sun Y, Wang Y, Miao A, Xiang J, Wang X. Frequency-Dependent Dynamics of Functional Connectivity Networks During Seizure Termination in Childhood Absence Epilepsy: A Magnetoencephalography Study. Front Neurol 2021; 12:744749. [PMID: 34759883 PMCID: PMC8573389 DOI: 10.3389/fneur.2021.744749] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 09/21/2021] [Indexed: 12/04/2022] Open
Abstract
Objective: Our aim was to investigate the dynamics of functional connectivity (FC) networks during seizure termination in patients with childhood absence epilepsy (CAE) using magnetoencephalography (MEG) and graph theory (GT) analysis. Methods: MEG data were recorded from 22 drug-naïve patients diagnosed with CAE. FC analysis was performed to evaluate the FC networks in seven frequency bands of the MEG data. GT analysis was used to assess the topological properties of FC networks in different frequency bands. Results: The patterns of FC networks involving the frontal cortex were altered significantly during seizure termination compared with those during the ictal period. Changes in the topological parameters of FC networks were observed in specific frequency bands during seizure termination compared with those in the ictal period. In addition, the connectivity strength at 250–500 Hz during the ictal period was negatively correlated with seizure frequency. Conclusions: FC networks associated with the frontal cortex were involved in the termination of absence seizures. The topological properties of FC networks in different frequency bands could be used as new biomarkers to characterize the dynamics of FC networks related to seizure termination.
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Affiliation(s)
- Jintao Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Yihan Li
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Ke Zhang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Yulei Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Yingfan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Ailiang Miao
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
| | - Jing Xiang
- Division of Neurology, MEG Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China
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Sinha M, Narayanan R. Active Dendrites and Local Field Potentials: Biophysical Mechanisms and Computational Explorations. Neuroscience 2021; 489:111-142. [PMID: 34506834 PMCID: PMC7612676 DOI: 10.1016/j.neuroscience.2021.08.035] [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: 04/27/2021] [Revised: 08/30/2021] [Accepted: 08/31/2021] [Indexed: 10/27/2022]
Abstract
Neurons and glial cells are endowed with membranes that express a rich repertoire of ion channels, transporters, and receptors. The constant flux of ions across the neuronal and glial membranes results in voltage fluctuations that can be recorded from the extracellular matrix. The high frequency components of this voltage signal contain information about the spiking activity, reflecting the output from the neurons surrounding the recording location. The low frequency components of the signal, referred to as the local field potential (LFP), have been traditionally thought to provide information about the synaptic inputs that impinge on the large dendritic trees of various neurons. In this review, we discuss recent computational and experimental studies pointing to a critical role of several active dendritic mechanisms that can influence the genesis and the location-dependent spectro-temporal dynamics of LFPs, spanning different brain regions. We strongly emphasize the need to account for the several fast and slow dendritic events and associated active mechanisms - including gradients in their expression profiles, inter- and intra-cellular spatio-temporal interactions spanning neurons and glia, heterogeneities and degeneracy across scales, neuromodulatory influences, and activitydependent plasticity - towards gaining important insights about the origins of LFP under different behavioral states in health and disease. We provide simple but essential guidelines on how to model LFPs taking into account these dendritic mechanisms, with detailed methodology on how to account for various heterogeneities and electrophysiological properties of neurons and synapses while studying LFPs.
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Affiliation(s)
- Manisha Sinha
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka 560012, India
| | - Rishikesh Narayanan
- Cellular Neurophysiology Laboratory, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka 560012, India.
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Traynelis SF, Dlugos D, Henshall D, Mefford HC, Rogawski MA, Staley KJ, Dacks PA, Whittemore V, Poduri A. Epilepsy Benchmarks Area III: Improved Treatment Options for Controlling Seizures and Epilepsy-Related Conditions Without Side Effects. Epilepsy Curr 2020; 20:23S-30S. [PMID: 31965829 PMCID: PMC7031805 DOI: 10.1177/1535759719895279] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
The goals of Epilepsy Benchmark Area III involve identifying areas that are ripe for progress in terms of controlling seizures and patient symptoms in light of the most recent advances in both basic and clinical research. These goals were developed with an emphasis on potential new therapeutic strategies that will reduce seizure burden and improve quality of life for patients with epilepsy. In particular, we continue to support the proposition that a better understanding of how seizures are initiated, propagated, and terminated in different forms of epilepsy is central to enabling new approaches to treatment, including pharmacological as well as surgical and device-oriented approaches. The stubbornly high rate of treatment-resistant epilepsy—one-third of patients—emphasizes the urgent need for new therapeutic strategies, including pharmacological, procedural, device linked, and genetic. The development of new approaches can be advanced by better animal models of seizure initiation that represent salient features of human epilepsy, as well as humanized models such as induced pluripotent stem cells and organoids. The rapid advances in genetic understanding of a subset of epilepsies provide a path to new and direct patient-relevant cellular and animal models, which could catalyze conceptualization of new treatments that may be broadly applicable across multiple forms of epilepsies beyond those arising from variation in a single gene. Remarkable advances in machine learning algorithms and miniaturization of devices and increases in computational power together provide an enhanced opportunity to detect and mitigate seizures in real time via devices that interrupt electrical activity directly or administer effective pharmaceuticals. Each of these potential areas for advance will be discussed in turn.
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Affiliation(s)
- Stephen F Traynelis
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, GA, USA
| | - Dennis Dlugos
- Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - David Henshall
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland.,FutureNeuro Research Centre, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Heather C Mefford
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Michael A Rogawski
- Departments of Neurology and Pharmacology, School of Medicine, University of California, Davis, Sacramento, CA, USA
| | - Kevin J Staley
- Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | | | - Vicky Whittemore
- Division of Neuroscience, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MA, USA
| | - Annapurna Poduri
- Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
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