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Neurobiology of value integration: When value impacts valuation

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  • Soyoung Q Park
  • Thorsten Kahnt
  • Jörg Rieskamp
  • Hauke R. Heekeren

Abstract

Everyday choice options have advantages (positive values) and disadvantages (negative values) that need to be integrated into an overall subjective value. For decades, economic models have assumed that when a person evaluates a choice option, different values contribute independently to the overall subjective value of the option. However, human choice behavior often violates this assumption, suggesting interactions between values. To investigate how qualitatively different advantages and disadvantages are integrated into an overall subjective value, we measured the brain activity of human subjects using fMRI while they were accepting or rejecting choice options that were combinations of monetary reward and physical pain. We compared different subjective value models on behavioral and neural data. These models all made similar predictions of choice behavior, suggesting that behavioral data alone are not sufficient to uncover the underlying integration mechanism. Strikingly, a direct model comparison on brain data decisively demonstrated that interactive value integration (where values interact and affect overall valuation) predicts neural activity in value-sensitive brain regions significantly better than the independent mechanism. Furthermore, effective connectivity analyses revealed that value-dependent changes in valuation are associated with modulations in subgenual anterior cingulate cortex–amygdala coupling. These results provide novel insights into the neurobiological underpinnings of human decision making involving the integration of different values.

Suggested Citation

  • Soyoung Q Park & Thorsten Kahnt & Jörg Rieskamp & Hauke R. Heekeren, 2011. "Neurobiology of value integration: When value impacts valuation," SFB 649 Discussion Papers SFB649DP2011-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2011-037
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    Cited by:

    1. Chen, Ray-Bing & Chen, Ying & Härdle, Wolfgang K., 2014. "TVICA—Time varying independent component analysis and its application to financial data," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 95-109.
    2. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    3. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Aurélie Bertrand & Christian Hafner, 2014. "On heterogeneous latent class models with applications to the analysis of rating scores," Computational Statistics, Springer, vol. 29(1), pages 307-330, February.
    5. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2016. "Semiparametric Estimation With Generated Covariates," Econometric Theory, Cambridge University Press, vol. 32(05), pages 1140-1177, October.
    6. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Gökhan Cebiroğlu & Ulrich Horst, 2011. "Optimal Display of Iceberg Orders," SFB 649 Discussion Papers SFB649DP2011-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2013. "Multivariate Volatility Modeling Of Electricity Futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 743-761, August.
    10. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2016. "Equilibrium Pricing in Incomplete Markets Under Translation Invariant Preferences," Mathematics of Operations Research, INFORMS, vol. 41(1), pages 174-195, February.
    11. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.
    13. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    14. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers SFB649DP2011-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    More about this item

    Keywords

    EU ETS; Realized Volatility; HAR; Volatility Forecasting; Intraday Data; CO2 Emission Allowances; Emissions Markets; Asymmetry; SHAR; HARQ; MC Simulation JEL Classification: C00;

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General

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