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Herausgeber: 
  • Boris Gutkin
  • Serge H. Ahmed
  • Computational Neuroscience of Drug Addiction 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  November 2013  
    Genre:  Naturwissensch., Medizin, Technik 
     
    B / bioinformatics / Biology, life sciences / Biomedical and Life Sciences / Computational and Systems Biology / Computational biology / Computer Appl. in Life Sciences / Information technology# general issues
    ISBN:  9781461429401 
    EAN-Code: 
    9781461429401 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #10 - Springer Series in Computational Neuroscience  
    Dimensionen:  H 235 mm / B 155 mm / D 19 mm 
    Gewicht:  545 gr 
    Seiten:  342 
    Illustration:  XIV, 342 p. 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.
     

      



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