Computational Neuroscience of Drug Addiction / Springer Series in Computational Neuroscience Bd.10 (PDF)

Drug addiction is one of the most important public health problems in Western societies, and is a rising concern for developing nations. Over the past three decades, experimental research on the neurobiology and psychology of drug addiction has generated a tremendous amount of exciting data, from the molecular 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 eclecticism to deepen our understanding of drug addiction and to foster our capacity to prevent and to cure drug addiction.

Recently, researchers from a broad spectrum of scientific disciplines - from pharmacokinetics to neuroeconomics - have begun to take up this challenge. Computational Neuroscience of Drug Addiction collects recent mathematical and neurocomputational modeling approaches to drug self-administration and addiction. This selection of chapters illustrates how mathematical modeling can contribute to our understanding of the mechanisms underlying the transition between the different stages of addiction, from initiation of regulated drug use and subsequent loss of control over drug use to relapse after long-term abstinence. The volume provides an overview of this emerging area and will serve as a standard reference for addiction researchers and quantitative scientists entering the field.