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Cognitive, Affective, & Behavioral Neuroscience

, Volume 9, Issue 4, pp 365–379 | Cite as

Aging and the neuroeconomics of decision making: A review

  • Stephen B. R. E. Brown
  • K. Richard RidderinkhofEmail author
Article

Abstract

Neuroeconomics refers to a combination of paradigms derived from neuroscience, psychology, and economics for the study of decision making and is an area that has received considerable scientific attention in the recent literature. Using realistic laboratory tasks, researchers seek to study the neurocognitive processes underlying economic decision making and outcome-based decision learning, as well as individual differences in these processes and the social and affective factors that modulate them. To this point, one question has remained largely unanswered: What happens to decision-making processes and their neural substrates during aging? After all, aging is associated with neurocognitive change, which may affect outcome-based decision making. In our study, we use the subjective expected utility model—a well-established decision-making model in economics—as a descriptive framework. After a short survey of the brain areas and neurotransmitter systems associated with outcome-based decision making—and of the effects of aging thereon—we review a number of decision-making studies. Their general data pattern indicates that the decision-making process is changed by age: The elderly perform less efficiently than younger participants, as demonstrated, for instance, by the smaller total rewards that the elderly acquire in lab tasks. These findings are accounted for in terms of age-related deficiencies in the probability and value parameters of the subjective expected utility model. Finally, we discuss some implications and suggestions for future research.

Keywords

Anterior Cingulate Cortex Ventral Striatum Reversal Learning Dorsal Striatum Avoidance Learning 
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.

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Copyright information

© Psychonomic Society, Inc. 2009

Authors and Affiliations

  • Stephen B. R. E. Brown
    • 1
  • K. Richard Ridderinkhof
    • 1
    Email author
  1. 1.Department of PsychologyUniversity of AmsterdamAmsterdamThe Netherlands

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