Seizure Prediction In Epilepsy

Comprising some 30 contributions, experts from around the world present and discuss recent advances related to seizure prediction in epilepsy. The book covers an extraordinarily broad spectrum, starting from modeling epilepsy in single cells or networks of a few cells to precisely-tailored seizure prediction techniques as applied to human data. This unique overview of our current level of knowledge and future perspectives provides theoreticians as well as practitioners, newcomers and experts with an up-to-date survey of developments in this important field of research.

A study of epilepsy from an engineering perspective, this volume begins by summarizing the physiology and the fundamental ideas behind the measurement, analysis and modeling of the epileptic brain. It introduces the EEG and provides an explanation of the type of brain activity likely to register in EEG measurements, offering an overview of how these EEG records are and have been analyzed in the past. The book focuses on the problem of seizure detection and surveys the physiologically based dynamic models of brain activity. Finally, it addresses the fundamental question: can seizures be predicted? Based on the authors' extensive research, the book concludes by exploring a range of future possibilities in seizure prediction.

This book is to improve our understanding of mechanisms leading to seizures in humans and in developing new therapeutic options. The book covers topics such as recent approaches to seizure control, recent developments in signal processing of interest for seizure prediction, ictogenesis in complex epileptic brain networks, active probing of the pre-seizure state, non-EEG based approaches to the transition to seizures, microseizures and their role in the generation of clinical seizures, the impact of sleep and long-biological cycles on seizure prediction, as well as animal and computational models of seizures and epilepsy. Furthermore the book covers recent developments of international databases and of parallel computing structures based on Cellular Nonlinear Networks that can play an important role in the realization of a portable seizure warning device. Contents:Epileptic Networks and Their Role for Seizure Prediction and Seizure Control:Transition Into and Out of a Focal Seizure (M de Curtis)Neuronal and Network Dynamics Preceding Experimental Seizures (P Jiruska, F Mormann and J G R Jefferys)Interictal EEG and Its Relevance for Seizure Prediction (A Schulze-Bonhage)Invasive Brain Stimulation in the Treatment of Epilepsy (M Sprengers, R Raedt, A Meurs, E Carrette, D van Roost, P Boon and K Vonck)Computational Models of Seizures and Epilepsy:Patient-Specific Neural Mass Modeling — Stochastic and Deterministic Methods (D R Freestone, L Kuhlmann, M S Chong, D Nesic and D B Grayden)Computational Modelling of Microseizures and Focal Seizure Onset (Y Wang, M Goodfellow, P N Taylor, D J Garry and G Baier)Predictability of Seizure-Like Events in a Complex Network Model of Integrate-and-Fire Neurons (A Rothkegel and K Lehnertz)Bursting and Synchrony in Networks of Model Neurons (C Geier, A Rothkegel and K Lehnertz)Advances in Analysis and Measurement Techniques:Signal Processing of the EEG: Approaches Tailored to Epilepsy (B Schelter, M Thiel, M Mader and W Mader)From Time Series to Complex Networks: An Overview (S Bialonski and K Lehnertz)Visualizing and Quantifying EEG Complexity on the Base of Ordinal Pattern Distributions (K Keller)Dynamics of Linear and Nonlinear Interrelation Networks in Peri-Ictal Intracranial EEG: Seizure Onset and Termination (C Rummel, M Müller, M Hauf, R Wiest and K Schindler)On the Centrality of the Focus in Human Epileptic Brain Networks (C Geier, M-T Kuhnert, C E Elger and K Lehnertz)Pre-Seizure States in Epileptic Brain Nnetworks: A Surrogate-Assisted, Weighted Network Analysis (G Ansmann, M-T Kuhnert, C E Elger and K Lehnertz)Network Analysis of Generalized Epileptic Discharges (P Ossenblok, P van Houdt, A Lüttjohann and G van Luijtelaar)Signal Processing Platform Based on Cellular Nonlinear Networks (J Müller, J Müller, R Becker and R Tetzlaff)Seizure Prediction by Cellular Nonlinear Networks? (V Senger and R Tetzlaff)Measuring Directed Interactions Using Cellular Neural Networks with Complex Connection Topologies (H Dickten, C E Elger and K Lehnertz)Seizure Prediction Using Optical Measurements of Blood Flow and Oxygenation (M Zhao, H Ma and T H Schwartz)Observing the Sleep-Wake Regulatory System to Improve Prediction of Seizures (M Sedigh-Sarvestani and B J Gluckman)The World's Largest Epilepsy Database: Content and Structure (M Ihle, B Schelter, J Timmer and A Schulze-Bonhage) Readership: Graduate students and professionals in the field of epileptology, neurosurgery and neuroscience. Keywords:Epileptic Networks;Seizure Prediction;Seizure Control;Computational Models;EpilepsyKey Features:Provides latest findings in the field of epilepsy research

Brain Seizure Detection and Classification Using Electroencephalographic Signals presents EEG signal processing and analysis with high performance feature extraction. The book covers the feature selection method based on One-way ANOVA, along with high performance machine learning classifiers for the classification of EEG signals in normal and epileptic EEG signals. In addition, the authors also present new methods of feature extraction, including Singular Spectrum-Empirical Wavelet Transform (SSEWT) for improved classification of seizures in significant seizure-types, specifically epileptic and Non-Epileptic Seizures (NES). The performance of the system is compared with existing methods of feature extraction using Wavelet Transform (WT) and Empirical Wavelet Transform (EWT). The book's objective is to analyze the EEG signals to observe abnormalities of brain activities called epileptic seizure. Seizure is a neurological disorder in which too many neurons are excited at the same time and are triggered by brain injury or by chemical imbalance. Presents EEG signal processing and analysis concepts with high performance feature extraction Discusses recent trends in seizure detection, prediction and classification methodologies Helps classify epileptic and non-epileptic seizures where misdiagnosis may lead to the unnecessary use of antiepileptic medication Provides new guidance and technical discussions on feature-extraction methods and feature selection methods based on One-way ANOVA, along with high performance machine learning classifiers for classification of EEG signals in normal and epileptic EEG signals, and new methods of feature extraction developed by the authors, including Singular Spectrum-Empirical Wavelet

A study of epilepsy from an engineering perspective, this volume begins by summarizing the physiology and the fundamental ideas behind the measurement, analysis and modeling of the epileptic brain. It introduces the EEG and provides an explanation of the type of brain activity likely to register in EEG measurements, offering an overview of how these EEG records are and have been analyzed in the past. The book focuses on the problem of seizure detection and surveys the physiologically based dynamic models of brain activity. Finally, it addresses the fundamental question: can seizures be predicted? Based on the authors' extensive research, the book concludes by exploring a range of future possibilities in seizure prediction.

Designed to provide a comprehensive but accessible introduction to epilepsy and seizure disorders, Epilepsy, 2nd edition provides state-of-the-art information in a concise format useful to a wide audience, from neurology residents to epilepsy fellows and practitioners. This illustrated guide to the assessment, diagnosis, and treatment of epilepsy is a valuable resource enabling clinicians to stay on top of the latest recommendations for best practice.

As a truly translational area of biomedical investigation, epilepsy research spans an extraordinary breadth of subjects and involves virtually every tool that modern neuroscience has at its disposal. The Encyclopedia of Basic Epilepsy Research provides an up to date, comprehensive reference for all epilepsy researchers. With an expert list of authors, the encyclopedia covers the full spectrum of research activities from genes and molecules to animal models and human patients. The encyclopedia's electronic format also provides unparalleled access to frequent updates and additions, while the limited edition print version provides another option for owning this content. The Encyclopedia of Basic Epilepsy Research is an essential resource for researchers of all levels and clinicians who study epilepsy. The only comprehensive reference for basic research and current activities in epilepsy Electronic format provides fast and easy access to updates and additions, with limited print version available as well Contains over 85 articles, all written by experts in epilepsy research

This book is to improve our understanding of mechanisms leading to seizures in humans and in developing new therapeutic options. The book covers topics such as recent approaches to seizure control, recent developments in signal processing of interest for seizure prediction, ictogenesis in complex epileptic brain networks, active probing of the pre-seizure state, non-EEG based approaches to the transition to seizures, microseizures and their role in the generation of clinical seizures, the impact of sleep and long-biological cycles on seizure prediction, as well as animal and computational models of seizures and epilepsy. Furthermore the book covers recent developments of international databases and of parallel computing structures based on Cellular Nonlinear Networks that can play an important role in the realization of a portable seizure warning device.