Overview
- Intrigued by the apparent irrational behavior of drug addicts, researchers from a wide range of scientific disciplines have formulated a plethora of theoretical schemes over the years to understand addiction
- Collects several recent mathematical and neurocomputational models of drug self-administration and addiction
- Illustrates how mathematical modeling can contribute to our understanding of the mechanisms underlying the transition between the different stages of addiction
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Series in Computational Neuroscience (NEUROSCI, volume 10)
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About this book
Drug addiction remains one of the most important public health problems in western societies
and is a rising concern for developing nations. Over the past 3 decades, experimental research on the
neurobiology and psychology of drug addiction has generated a torrent of exciting data, from the molecular up to the behavioral levels. As a result, a new and pressing challenge for addiction research is to formulate a synthetic theoretical framework that goes well beyond mere scientific eclectism to deepen our understanding of drug addiction and to foster our capacity to prevent and to cure drug addiction.
Intrigued by the apparent irrational behavior of drug addicts, researchers from a wide range of scientific
disciplines have formulated a plethora of theoretical schemes over the years to understand addiction.
However, most of these theories and models are qualitative in nature and are formulated using terms that are often ill-defined. As a result, the empirical validity of these models has been difficult to test rigorously, which has served to generate more controversy than clarity. In this context, as in other scientific fields, mathematical and computational modeling should contribute to the development of more testable and rigorous models of addiction.
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Table of contents (11 chapters)
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Front Matter
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Pharmacological-Based Models of Addiction
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Front Matter
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Neurocomputational Models of Addiction
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Front Matter
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Neurocomputational models of addiction
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Economic-Based Models of Addiction
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Front Matter
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Back Matter
Reviews
From the reviews:
“This is a fascinating … new book covering mathematical modeling of various aspects of addiction. … Written and edited by experts in the field, this is a welcome addition to the neuroscientific literature of addictions. … Each chapter concludes with timely and relevant citations of the scientific literature. … This new … book is a stimulating introduction to the field for those with the computational neuroscientific background knowledge to comprehend it.” (Michael Joel Schrift, Doody's Book Reviews, March, 2013)Editors and Affiliations
Bibliographic Information
Book Title: Computational Neuroscience of Drug Addiction
Editors: Boris Gutkin, Serge H. Ahmed
Series Title: Springer Series in Computational Neuroscience
DOI: https://doi.org/10.1007/978-1-4614-0751-5
Publisher: Springer New York, NY
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer Science+Business Media, LLC 2012
Hardcover ISBN: 978-1-4614-0750-8Published: 26 October 2011
Softcover ISBN: 978-1-4614-2940-1Published: 28 November 2013
eBook ISBN: 978-1-4614-0751-5Published: 27 October 2011
Series ISSN: 2197-1900
Series E-ISSN: 2197-1919
Edition Number: 1
Number of Pages: XIV, 342