IDEAS home Printed from https://ideas.repec.org/p/hum/wpaper/sfb649dp2010-063.html
   My bibliography  Save this paper

How the brain integrates costs and benefits during decision making

Author

Listed:
  • Basten U
  • Biele G. P.
  • Heekeren H. R.
  • Fiebach

Abstract

When we make decisions, the benefits of an option often need to be weighed against accompanying costs. Little is known, however, about the neural systems underlying such cost–benefit computations. Using functional magnetic resonance imaging and choice modeling, we show that decision making based on cost–benefit comparison can be explained as a stochastic accumulation of cost–benefit difference. Model-driven functional MRI shows that ventromedial and left dorsolateral prefrontal cortex compare costs and benefits by computing the difference between neural signatures of anticipated benefits and costs from the ventral striatum and amygdala, respectively. Moreover, changes in blood oxygen level dependent (BOLD) signal in the bilateral middle intraparietal sulcus reflect the accumulation of the difference signal from ventromedial prefrontal cortex. In sum, we show that a neurophysiological mechanism previously established for perceptual decision making, that is, the difference-based accumulation of evidence, is fundamental also in value-based decisions. The brain, thus, weighs costs against benefits by combining neural benefit and cost signals into a single, difference-based neural representation of net value, which is accumulated over time until the individual decides to accept or reject an option.

Suggested Citation

  • Basten U & Biele G. P. & Heekeren H. R. & Fiebach, 2010. "How the brain integrates costs and benefits during decision making," SFB 649 Discussion Papers SFB649DP2010-063, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2010-063
    as

    Download full text from publisher

    File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2010-063.pdf
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Daniel Serra, 2021. "Decision-making: from neuroscience to neuroeconomics—an overview," Theory and Decision, Springer, vol. 91(1), pages 1-80, July.
    2. Ryan Webb, 2019. "The (Neural) Dynamics of Stochastic Choice," Management Science, INFORMS, vol. 65(1), pages 230-255, January.
    3. Thomas, Armin W. & Molter, Felix & Krajbich, Ian & Heekeren, Hauke R. & Mohr, Peter N. C., 2019. "Gaze bias differences capture individual choice behaviour," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 3(6), pages 625-635.
    4. Clithero, John A., 2018. "Response times in economics: Looking through the lens of sequential sampling models," Journal of Economic Psychology, Elsevier, vol. 69(C), pages 61-86.
    5. Ryan Webb & Paul W. Glimcher & Kenway Louie, 2021. "The Normalization of Consumer Valuations: Context-Dependent Preferences from Neurobiological Constraints," Management Science, INFORMS, vol. 67(1), pages 93-125, January.
    6. Tobias Otto & Fred R H Zijlstra & Rainer Goebel, 2018. "Feeling the force: Changes in a left-lateralized network of brain areas under simulated workday conditions are reflected in subjective mental effort investment," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-21, June.
    7. Ian Krajbich & Todd Hare & Björn Bartling & Yosuke Morishima & Ernst Fehr, 2015. "A Common Mechanism Underlying Food Choice and Social Decisions," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-24, October.
    8. Mads Lund Pedersen & Tor Endestad & Guido Biele, 2015. "Evidence Accumulation and Choice Maintenance Are Dissociated in Human Perceptual Decision Making," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-20, October.
    9. Vriens, M. & Vidden, C. & Schomaker, J., 2020. "What I see is what I want: Top-down attention biasing choice behavior," Journal of Business Research, Elsevier, vol. 111(C), pages 262-269.
    10. Filip Gesiarz & Donal Cahill & Tali Sharot, 2019. "Evidence accumulation is biased by motivation: A computational account," PLOS Computational Biology, Public Library of Science, vol. 15(6), pages 1-15, June.
    11. Ernst Fehr & Antonio Rangel, 2011. "Neuroeconomic Foundations of Economic Choice--Recent Advances," Journal of Economic Perspectives, American Economic Association, vol. 25(4), pages 3-30, Fall.
    12. Cary Frydman & Nicholas Barberis & Colin Camerer & Peter Bossaerts & Antonio Rangel, 2012. "Using Neural Data to Test a Theory of Investor Behavior: An Application to Realization Utility," NBER Working Papers 18562, National Bureau of Economic Research, Inc.
    13. Clithero, John A., 2018. "Improving out-of-sample predictions using response times and a model of the decision process," Journal of Economic Behavior & Organization, Elsevier, vol. 148(C), pages 344-375.

    More about this item

    Keywords

    cost–benefit; integration valuation; diffusion model; model-based functional MRI JEL Classification: C00;
    All these keywords.

    JEL classification:

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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hum:wpaper:sfb649dp2010-063. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: RDC-Team (email available below). General contact details of provider: https://edirc.repec.org/data/sohubde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.