NDLI: "Imaging the Addicted Human Brain: from Molecules to Behavior"

Content Provider	IEEE Xplore Digital Library
Author	Volkow, Nora
Copyright Year	2006
Description	Author affiliation: Director, National Institute of Drug Abuse (NIDA), National Institutes of Health (Volkow, Nora)
Abstract	Addiction is a disorder that involves complex interactions between a wide array of biological and environmental variables. Studies employing neuroimaging technology paired with sophisticated behavioral measurement paradigms have led to extraordinary progress in elucidating many of the neurochemical and functional changes that occur in the brains of addicts. Although large and rapid increases in dopamine have been linked with the rewarding properties of drugs, the addicted state, in striking contrast, is marked by significant decreases in brain dopamine function. Such decreases are associated with dysfunction of prefrontal regions including orbitofrontal cortex and cingulate gyrus. In addiction, disturbances in salience attribution result in enhanced value given to drugs and drug-related stimuli at the expense of other reinforcers. Dysfunction in inhibitory control systems, by decreasing the addict's ability to refrain from seeking and consuming drugs, ultimately results in the compulsive drug intake that characterizes the disease. Discovery of such disruptions in the fine balance that normally exists between brain circuits underling reward, motivation, memory and cognitive control have important implications for designing multi-pronged therapies for treating addictive disorders.
Sponsorship	IEEE EMB
Starting Page	1
Ending Page	2
File Size	125095
Page Count	2
File Format	PDF
ISBN	1424400325
ISSN	1557170X
DOI	10.1109/IEMBS.2006.259770
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humans Drugs Neuroimaging Psychiatry Biomedical imaging Pharmaceutical technology Extraterrestrial measurements Control systems Diseases Circuits
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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