Computational Neuroscience in Epilepsy


Book Description

Epilepsy is a neurological disorder that affects millions of patients worldwide and arises from the concurrent action of multiple pathophysiological processes. The power of mathematical analysis and computational modeling is increasingly utilized in basic and clinical epilepsy research to better understand the relative importance of the multi-faceted, seizure-related changes taking place in the brain during an epileptic seizure. This groundbreaking book is designed to synthesize the current ideas and future directions of the emerging discipline of computational epilepsy research. Chapters address relevant basic questions (e.g., neuronal gain control) as well as long-standing, critically important clinical challenges (e.g., seizure prediction). Computational Neuroscience in Epilepsy should be of high interest to a wide range of readers, including undergraduate and graduate students, postdoctoral fellows and faculty working in the fields of basic or clinical neuroscience, epilepsy research, computational modeling and bioengineering. - Covers a wide range of topics from molecular to seizure predictions and brain implants to control seizures - Contributors are top experts at the forefront of computational epilepsy research - Chapter contents are highly relevant to both basic and clinical epilepsy researchers




Epilepsy


Book Description

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, Mathema




Oxford Textbook of Epilepsy and Epileptic Seizures


Book Description

Part of the Oxford Textbooks in Clinical Neurology (OTCN) series, this volume covers the scientific basis, clinical diagnosis, and treatment of epilepsy and epileptic seizures, and is complemented by an online edition.




Computational Neurology and Psychiatry


Book Description

This book presents the latest research in computational methods for modeling and simulating brain disorders. In particular, it shows how mathematical models can be used to study the relationship between a given disorder and the specific brain structure associated with that disorder. It also describes the emerging field of computational psychiatry, including the study of pathological behavior due to impaired functional connectivity, pathophysiological activity, and/or aberrant decision-making. Further, it discusses the data analysis techniques that will be required to analyze the increasing amount of data being generated about the brain. Lastly, the book offers some tips on the application of computational models in the field of quantitative systems pharmacology. Mainly written for computational scientists eager to discover new application fields for their model, this book also benefits neurologists and psychiatrists wanting to learn about new methods.




Seizure Prediction in Epilepsy


Book Description

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.




Recent Advances In Predicting And Preventing Epileptic Seizures - Proceedings Of The 5th International Workshop On Seizure Prediction


Book Description

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.




Data-Driven Computational Neuroscience


Book Description

Trains researchers and graduate students in state-of-the-art statistical and machine learning methods to build models with real-world data.




Introduction to Epilepsy


Book Description

Covers all aspects of epilepsy, from basic mechanisms to diagnosis and management, as well as legal and social considerations.




Seizures and Epilepsy


Book Description

This second edition of 'Seizures and Epilepsy' is completely revised, due to tremendous advances in the understanding of the fundamental neuronal mechanisms underlying epileptic phenomena, as well as current diagnosis and treatment, which have been heavily influenced over the past several decades by seminal neuroscientific developments, particularly the introduction of molecular neurobiology, genetics, and modern neuroimaging. This resource covers a broad range of both basic and clinical epileptology.




Computational Models of Brain and Behavior


Book Description

A comprehensive Introduction to the world of brain and behavior computational models This book provides a broad collection of articles covering different aspects of computational modeling efforts in psychology and neuroscience. Specifically, it discusses models that span different brain regions (hippocampus, amygdala, basal ganglia, visual cortex), different species (humans, rats, fruit flies), and different modeling methods (neural network, Bayesian, reinforcement learning, data fitting, and Hodgkin-Huxley models, among others). Computational Models of Brain and Behavior is divided into four sections: (a) Models of brain disorders; (b) Neural models of behavioral processes; (c) Models of neural processes, brain regions and neurotransmitters, and (d) Neural modeling approaches. It provides in-depth coverage of models of psychiatric disorders, including depression, posttraumatic stress disorder (PTSD), schizophrenia, and dyslexia; models of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, and epilepsy; early sensory and perceptual processes; models of olfaction; higher/systems level models and low-level models; Pavlovian and instrumental conditioning; linking information theory to neurobiology; and more. Covers computational approximations to intellectual disability in down syndrome Discusses computational models of pharmacological and immunological treatment in Alzheimer's disease Examines neural circuit models of serotonergic system (from microcircuits to cognition) Educates on information theory, memory, prediction, and timing in associative learning Computational Models of Brain and Behavior is written for advanced undergraduate, Master's and PhD-level students—as well as researchers involved in computational neuroscience modeling research.