Toward a Computationally Unified Behavioral-Economic Model of Addiction

  • E. Terry Mueller
  • Laurence P. Carter
  • Warren K. Bickel
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI, volume 10)


This chapter describes an instance of computational constructionism applied to the understanding of drug addiction. Rather than devising models of increasingly smaller anatomical, physiological or chemical units of analysis, the practice exposited here was to expand the integrative scope of behavioral-economic concepts that have been used to describe addiction phenomena. We discussed (a) excessive and persistent consumption of substances, as studied in analysis of demand; and (b) concurrent-choice preference for immediate small and unhealthy reinforcers over delayed but large and healthy reinforcers, and reversals of preference between this two types of alternatives, as studied in the science of delay discounting. While all of these phenomena are characteristic of addiction, it is remarkable how seldom concepts for explaining (a) appear in scientific reports on (b). The notion of expanding the scope of an explanatory concept is introduced via consideration of the concept of unit price. This concept integrates numerous variables traditionally studied in isolation in addiction research, and provides the basis of more general and parsimonious explanations of addiction phenomena. The scope of the unit price concept is further expanded, as it plays a role in a computational formulation describing choice among, and reversals of preference between, concurrently available reinforcers, which are very complex aspects of behavior that are fundamental to addiction phenomena. Lastly, we discuss computational implications and cautions, and scientific and practical prospects that derive from the exercise of expanding the integrative scope of the unit price concept to a broader and more complex range of addiction phenomena. Future developments along these lines are expected to produce constructs with which preferences exhibited by drug-dependent individuals may be predicted more accurately, and may be therapeutically modified.


Preference Reversal Demand Curve Unit Price Behavioral Economic Delay Discount 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The writing of this chapter was supported by National Institute on Drug Abuse Grants R37 DA 006526-18, R01 DA 11692-10, R01 DA022386-02, R01 DA024080-01A1, Wilbur Mills Chair Endowment, and in part by the Arkansas Biosciences Institute, a partnership of scientists from Arkansas Children’s Hospital, Arkansas State University, the University of Arkansas-Division of Agriculture, the University of Arkansas, Fayetteville, and the University of Arkansas for Medical Sciences. The Arkansas Biosciences Institute is the major research component of the Tobacco Settlement Proceeds Act of 2000.


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • E. Terry Mueller
    • 1
  • Laurence P. Carter
    • 2
  • Warren K. Bickel
    • 3
  1. 1.Advanced Recovery Research Center, Virginia Tech Carilion Research InstituteVirginia TechRoanokeUSA
  2. 2.Center for Addiction Research, Psychiatric Research InstituteUniversity of Arkansas for Medical SciencesLittle RockUSA
  3. 3.Advanced Recovery Research Center, Virginia Tech Carilion Research Institute and Department of PsychologyVirginia TechRoanokeUSA

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