Multiple Neural Circuits in Value-Based Decision-Making

  • Masamichi Sakagami
Conference paper


Valuation is an essential function in decision-making. To understand the nature of the distinct neural systems used in such valuation, we performed monkey single-unit recording experiments and a human fMRI experiment using (1) a perceptual discrimination task with asymmetric reward, and (2) a reward inference task. The results suggest that both the primate and human brain have, at least, two distinct valuation systems: one in the nigro-striatal circuit (the stimulus-based valuation system) and the other in the PFC circuit (the knowledge-based valuation system). We propose that the stimulus-based valuation system calculates values based on the empirical and probabilistic relation between an event and its outcome. The knowledge-based valuation system generates values by further extension of directly-experienced association through categorical processes and rules, thereby enabling animals to predict the outcome of an inexperienced event.


Motion Stimulus Large Reward Reward Condition Reward Prediction Perceptual Decision 
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.



Our research was supported by the twenty-first Century Center of Excellence (COE) program (Integrative Human Science Program, Tamagawa University) and the global COE program (Origins of the Social Mind, Tamagawa University) from the Japan Society for Promotion of Science (JSPS), and Grants-in-Aid for Scientific Research on Priority areas from the Ministry of Education, Culture, Sports, Science and Technology, Japan.


  1. 1.
    Rangel, A., Camerer, C., Montague, P.R.: A framework for studying the neurobiology of value-based decision-making. Nat. Rev. Neurosci. 9 (2008) 545–556PubMedCrossRefGoogle Scholar
  2. 2.
    Yamamoto, M., Okuda, J., Samejima, K., Sakagami, M.: Differential reward prediction on salient and uncertain perception as revealed by random dot motion stimuli and fMRI. Soc. Neurosci. Abstr. (2007) 311.12Google Scholar
  3. 3.
    Nomoto, K., Schultz, W., Watanabe, T., Sakagami, M.: Temporally extended dopamine responses to perceptually demanding reward-predictive stimuli. J. Neurosci. 30 (2010) 10692–10702PubMedCentralPubMedCrossRefGoogle Scholar
  4. 4.
    Pan, X., Sawa, K., Tsuda, I., Tsukada, M., Sakagami, M.: Reward prediction based on stimulus categorization in primate lateral prefrontal cortex. Nat. Neurosci. 11 (2008) 703–712PubMedCrossRefGoogle Scholar
  5. 5.
    Haber, S.N.: The primate basal ganglia: parallel and integrative networks. J. Chem. Neuroanat. 26 (2003) 317–330PubMedCrossRefGoogle Scholar
  6. 6.
    Schultz, W., Dayan, P., Montague, P.R.: A neural substrate of prediction and reward. Science, 275 (1997) 1593–1599PubMedCrossRefGoogle Scholar
  7. 7.
    Tobler, P.N., O’Doherty, J.P., Dolan, R.J., Schultz, W.: Reward value coding distinct from risk attitude-related uncertainty coding in human reward systems. J. Neurophysiol. 97 (2007) 1621–1632PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Summerfield, C., Egner, T., Mangels, J., Hirsch, J.: Mistaking a house for a face: neural correlates of misperception in healthy humans. Cereb. Cortex, 16 (2006) 500–508PubMedCrossRefGoogle Scholar
  9. 9.
    Hayden, B.Y., Pearson, J.M., Platt, M.L.: Fictive reward signals in the anterior cingulate cortex. Science, 324 (2009) 248–250CrossRefGoogle Scholar
  10. 10.
    Yoshida, W., Seymour, B., Friston, K.J., Dolan, R.J.: Neural mechanisms of belief inference during cooperative games. J. Neurosci. 30 (2010) 10744–10751PubMedCentralPubMedCrossRefGoogle Scholar
  11. 11.
    Kim, J., Shadlen, M.N.: Neural correlates of a decision in the dorsolateral prefrontal cortex of the macaque. Nat. Neurosci. 2 (1999) 176–185PubMedCrossRefGoogle Scholar
  12. 12.
    Daw, N.D., Niv, Y., Dayan, P.: Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control. Nat. Neurosci. 8 (2005) 1704–1711PubMedCrossRefGoogle Scholar
  13. 13.
    Behrens, T.E., Hunt, L.T., Rushworth, M.F.: The computation of social behavior. Science, 324 (2009) 1160–1164PubMedCrossRefGoogle Scholar
  14. 14.
    Hare, T.A., Camerer, C.F., Rangel, A.: Self-control in decision-making involves modulation of the vMPFC valuation system. Science, 324 (2009) 646–648PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Brain Science Research InstituteTamagawa UniversityTokyoJapan

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