Epilepsy

Epilepsy: The Intersection of Neurosciences, Biology, Mathematics, Engineering, and Physics

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Features

  • Provides up to date information about the state of research in the field, future research, and clinical directions
  • Offers unique insights into controversial issues
  • Includes extensive references in each chapter to enhance further study

Summary

Epilepsy, one of the most prevalent neurological disorders, affects approximately 1% (greater than 60 million) of the world's population. In an estimated 20 million of these patients, seizures are not controlled even by multiple anti-seizure drugs, and are extremely difficult to predict. Epilepsy: The Intersection of Neurosciences, Biology, Mathematics, Engineering, and Physics seamlessly brings together the neurosciences, mathematics, computational sciences, engineering, physics, and clinical epileptology to present to readers a highly didactic, integrated, clear and practically useful knowledge base and research directions.

Laying out the foundations of signal analysis, data conditioning, linear and non-linear analysis, introduction to dynamical systems and fundamental anatomical and neurophysiological concepts, this book:

  • Introduces non-physicians to language and concepts necessary to establish a meaningful dialog with epileptologists
  • Introduces physicians to dynamical theory and signal processing without which interdisciplinary collaborations would not be productive
  • Mines knowledge from fields devoted to the investigation of aperiodic paroxysmal relaxation phenomena, such as earthquakes, which bear dynamical similarities with epilepsy, so as to lay the proper scientific foundations for epileptology and foster much needed therapeutic advances efficiently
  • Reviews spatiotemporal behavior of seizures, mechanisms of epileptogenesis and ictogenesis as well as of seizure control and ancillary technology
  • Calls attention to nocturnal frontal lobe epilepsy as a potentially fruitful paradigm for advancing seizure prediction.

Of all neurological disorders, epilepsy demands of investigators the broadest and deepest knowledge of dynamical, control, and system theories, knowledge that cannot be amassed without possessing a certain level of sophistication in relevant areas of neurosciences, physics, mathematics, and engineering. Narrowing the inescapable cultural chasm that commonly fragments multidisciplinary efforts, this book captures and enriches the burgeoning interdisciplinary synergism in the nascent field of dynamical epileptology.

Table of Contents

Foundations of Epilepsy
Neuroanatomy as Applicable to Epilepsy: Gross and Microscopic Anatomy/ Histology
Taufik A. Valiante
Introduction to EEG for Nonepileptologists Working in Seizure Prediction and Dynamics
Richard Wennberg
Basic Mechanisms of Seizure Generation
John G. R. Jefferys and Premysl Jiruska
An Introduction to Epileptiform Activities and Seizure Patterns Obtained by Scalp and Invasive EEG Recordings
Andreas Schulze-Bonhage
Seizures and Epilepsy: An Overview
Steven Weinstein

Foundations of Engineering, Math, and Physics
Intracranial EEG: Electrodes, Filtering, Amplification, Digitization, Storage, and Display
Hitten P. Zaveri and Mark G. Frei
Time-Frequency Energy Analysis.
Piotr J. Franaszczuk
Neurodynamics and Ion Channels: A Tutorial.
John G. Milton
Nonlinear Time Series Analysis in a Nutshell
Ralph Gregor Andrzejak
How to Detect and Quantify Epileptic Seizures
Sridhar Sunderam
Seizure Time Series Analysis II: Automated Prediction and Assessment of Seizure Prediction Algorithms
Florian Mormann, Klaus Lehnertz, and Ralph Gregor Andrzejak
Autonomous State Transitions in the Epileptic Brain: Anticipation and Control
Stiliyan N. Kalitzin, Demetrios N. Velis, and Fernando Lopes da Silva

The Challenge of Prediction
Prediction
Didier Sornette and Ivan Osorio

The State of Seizure Prediction: Seizure Prediction and Detection
Impact of Biases in the False-Positive Rate on Null Hypothesis Testing..
Ralph Gregor Andrzejak, Daniel Chicharro, and Florian Mormann
Seizure Prediction: An Approach Using Probabilistic Forecasting..
Bjoern Schelter, Hinnerk Feldwisch-Drentrup, Andreas Schulze-Bonhage, and Jens Timmer
Seizure Prediction and Detection Research at Optima Neuroscience
Deng-Shan Shiau, Jui-Hong Chien, Ryan T. Kern, Panos M. Pardalos, and J. Chris Sackellares
Preictal Directed Interactions in Epileptic Brain Networks
Klaus Lehnertz, Dieter Krug, Matthäus Staniek, Dennis Glüsenkamp, and Christian E. Elger
Seizure Prediction and Observability of EEG Sources
Elma O’Sullivan-Greene, Levin Kuhlmann, Andrea Varsavsky, David B. Grayden, Anthony N. Burkitt, and Iven M. Y. Mareels
Circadian Regulation of Neural Excitability in Temporal Lobe Epilepsy
Paul R. Carney, Sachin S. Talathi, Dong-Uk Hwang, and William Ditto
Use of Dynamical Measures in Prediction and Control of Focal and Generalized Epilepsy
Shivkumar Sabesan, Leon Iasemidis, Konstantinos Tsakalis,David M. Treiman, and Joseph Sirven
Time-Series-Based Real-T ime Seizure Prediction
Pooja Rajdev and Pedro P. Irazoqui
Optimizing Seizure Detection Algorithms toward the Development of Implantable Epilepsy Prostheses
Shriram Raghunathan and Pedro P. Irazoqui
Initiation and Termination of Seizure-Like Activity in Small-World Neural Networks
Alexander Rothkegel, Christian E. Elger, and Klaus Lehnertz
Are Interaction Clusters in Epileptic Networks Predictive of Seizures?
Stephan Bialonski, Christian E. Elger, and Klaus Lehnertz
Preictal Spikes in the Hippocampus of Patients with Mesial Temporal Lobe Epilepsy
C. Alvarado-Rojas, M. Valderrama, G. Huberfeld, and M. Le Van Quyen

The State of Seizure Prediction: Seizure Generation
Microanalysis and Macroanalysis of High-Frequency Oscillations in the Human Brain
B. Crépon, M. Valderrama, C. Alvarado-Rojas, V. Navarro, and M. Le Van Quyen

The State of Seizure Prediction: Seizure Control
Vagus Nerve Stimulation Triggered by Machine Learning–Based Seizure Detection: Initial Implementation and Evaluation
Ali Shoeb, Trudy Pang, John V. Guttag, and Steven C. Schachter
Low-Frequency Stimulation as a Therapy for Epilepsy
Jeffrey H. Goodman

The State of Seizure Prediction: Technology
Large-Scale Electrophysiology: Acquisition, Storage, and Analysis
Matt Stead, Mark R. Bower, Benjamin H. Brinkmann, Christopher Warren, and Gregory A. Worrell
EPILAB: A MATLAB® Platform for Multifeature and Multialgorithm Seizure Prediction
B. Direito, R. P. Costa, H. Feldwisch, M. Valderrama, S. Nikolopoulos, B. Schelter, M. Jachan, C. A. Teixeira, L. Aires, J.Timmer, M. Le Van Quyen, and A. Dourado
Emerging Technologies for Brain-Implantable Devices
Bruce Lanning, Bharat S. Joshi, Themis R. Kyriakides, Dennis D. Spencer, and Hitten P. Zaveri

Nocturnal Frontal Lobe Epilepsy: A Paradigm for Seizure Prediction?
Familial and Sporadic Nocturnal Frontal Lobe Epilepsy (NFLE)— Electroclinical Features
Gholam K. Motamedi and Ronald P. Lesser
Nicotinic Acetylcholine Receptors in Circuit Excitability and Epilepsy: The Many Faces of Nocturnal Frontal Lobe Epilepsy
Ortrud K. Steinlein and Daniel Bertrand
Channelopathies in Epileptology
Frank Lehmann-Horn, Holger Lerche, Yvonne Weber, and Karin Jurkat-Rott
Autosomal Dominant Nocturnal Frontal Lobe Epilepsy: Excessive Inhibition?
Molly N. Brown and Gregory C. Mathews
How to Measure Circadian Rhythmicity in Humans
Wytske A. Hofstra and Al W. de Weerd
Seizure Prediction and the Circadian Rhythm
Tyler S. Durazzo and Hitten P. Zaveri
Nocturnal Frontal Lobe Epilepsy: Metastability in a Dynamic Disease?
John Milton and Ivan Osorio

Editor Bio(s)

Hitten P. Zaveri is an Associate Research Scientist within the Department of Neurology at Yale University in New Haven, Connecticut.

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