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Cognitive Process of Emotion Under Uncertainty

  • Ayako Onzo
  • Ken Mogi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3316)

Abstract

One of the missions of the cognitive process of animals, including humans, is to make reasonable judgments and decisions in the presence of uncertainty. The balance between exploration and exploitation investigated in the reinforcement-learning paradigm is one of the key factors in this process. Recently, following the pioneering work in behavioral economics, growing attention has been directed to human behaviors exhibiting deviations from simple maximization of re-ward. Here we study the nature of human decision making under the existence of reward uncertainty, employing a condition where the reward expectancy is constant (flat reward condition). The characteristic behavioral patterns exhibited by subjects reveal the underlying reward-related neural mechanism. The relevance of this result to the functions of dopamine neurons is discussed.

Keywords

Dopamine Neuron Behavioral Economic Ultimatum Game Differential Behavior Safe Base 
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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References

  1. 1.
    Graham, G., Neisser, J.: Probing for relevance: what metacognition tells us about the power of consciousness. Conscious Cogn. 9(2 Pt 1), 172–7 (2000)Google Scholar
  2. 2.
    Griffiths, D., Dickinson, A., Clayton, N.: Episodic memory: what can animals remember about their past? Trends Cogn Sci. 3(2), 74–80 (1999)CrossRefGoogle Scholar
  3. 3.
    Hampton, R.: Resus monkeys know when they remember. PNAS 98(9), 5359–5362 (2001)CrossRefGoogle Scholar
  4. 4.
    Koriat, A.: The feeling of knowing: some metatheoretical implications for consciousness and control. Conscious Cogn. 9(2 Pt 1), 149–71 (2000)Google Scholar
  5. 5.
    Sutton, R.S., Barto, A.: Reinforcement learning. MIT Press, Cambridge (1998)Google Scholar
  6. 6.
    Ainsworth, M.: Object relations, dependency, and attachment: a theoretical review of the infant-mother relationship. Child Dev. 40(4), 969–1025 (1969)CrossRefGoogle Scholar
  7. 7.
    Bowlby, J.: Attachment. Perseus Books (1982)Google Scholar
  8. 8.
    Fiorillo, C.D., Tobler, P.N., Schultz, W.: Discrete coding of reward probability and uncertainty by dopamine neurons. Science 299(5614), 1898–902 (2003)Google Scholar
  9. 9.
    Schultz, W.: Multiple reward signals in the brain. Nat Rev Neurosci. 1(3), 199–207 (2000)CrossRefMathSciNetGoogle Scholar
  10. 10.
    Schultz, W., Dayan, P., Montague, P.: A neural substrate of prediction and reward. Science 275(5306), 1593–9 (1997)Google Scholar
  11. 11.
    Shizgal, P., Arvanitogiannis, A.: Neuroscience. Gambling on dopamine. Science 299(5614), 1856–8 (2003)Google Scholar
  12. 12.
    Kahneman, D., Slovic, P., Tversky, A.: Judgment under uncertainty. Cambridge University Press, Cambridge (1982)Google Scholar
  13. 13.
    Kahneman, D., Tversky, A.: Choices, Values, and Flames. Cambridge University Press, Cambridge (2000)Google Scholar
  14. 14.
    Sanfey, A.G., Rilling, J.K., Aronson, J.A., Nystrom, L.E., Cohen, J.D.: The neural basis of economic decision-making in the Ultimatum Game. Science 300(5626), 1755–8 (2003)Google Scholar
  15. 15.
    Milinski, M., Wedekind, C.: Working memory constraints human cooperation in the prisoner’s dilemma. Proc Natl Acad Sci U S A 95(23), 13755–8 (1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Ayako Onzo
    • 1
    • 2
  • Ken Mogi
    • 1
    • 2
  1. 1.Sony Computer Science LaboratoriesTokyoJapan
  2. 2.Tokyo Institute of TechnologyYokohamaJapan

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