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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.
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.
Neuroscience is an interdisciplinary field that strives to
understand the functioning of neural systems at levels ranging from
biomolecules and cells to behaviour and higher brain functions
(perception, memory, cognition). Neurophysics has flourished over
the past three decades, becoming an indelible part of neuroscience,
and has arguably entered its maturity. It encompasses a vast array
of approaches stemming from theoretical physics, computer science,
and applied mathematics. This book provides a detailed review of
this field from basic concepts to its most recent development.
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