Literature DB >> 23022992

Measuring the subjective value of risky and ambiguous options using experimental economics and functional MRI methods.

Ifat Levy1, Lior Rosenberg Belmaker, Kirk Manson, Agnieszka Tymula, Paul W Glimcher.   

Abstract

Most of the choices we make have uncertain consequences. In some cases the probabilities for different possible outcomes are precisely known, a condition termed "risky". In other cases when probabilities cannot be estimated, this is a condition described as "ambiguous". While most people are averse to both risk and ambiguity(1,2), the degree of those aversions vary substantially across individuals, such that the subjective value of the same risky or ambiguous option can be very different for different individuals. We combine functional MRI (fMRI) with an experimental economics-based method(3 )to assess the neural representation of the subjective values of risky and ambiguous options(4). This technique can be now used to study these neural representations in different populations, such as different age groups and different patient populations. In our experiment, subjects make consequential choices between two alternatives while their neural activation is tracked using fMRI. On each trial subjects choose between lotteries that vary in their monetary amount and in either the probability of winning that amount or the ambiguity level associated with winning. Our parametric design allows us to use each individual's choice behavior to estimate their attitudes towards risk and ambiguity, and thus to estimate the subjective values that each option held for them. Another important feature of the design is that the outcome of the chosen lottery is not revealed during the experiment, so that no learning can take place, and thus the ambiguous options remain ambiguous and risk attitudes are stable. Instead, at the end of the scanning session one or few trials are randomly selected and played for real money. Since subjects do not know beforehand which trials will be selected, they must treat each and every trial as if it and it alone was the one trial on which they will be paid. This design ensures that we can estimate the true subjective value of each option to each subject. We then look for areas in the brain whose activation is correlated with the subjective value of risky options and for areas whose activation is correlated with the subjective value of ambiguous options.

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Year:  2012        PMID: 23022992      PMCID: PMC3490235          DOI: 10.3791/3724

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  8 in total

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Authors:  Christopher R Genovese; Nicole A Lazar; Thomas Nichols
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2.  Optimized EPI for fMRI studies of the orbitofrontal cortex.

Authors:  R Deichmann; J A Gottfried; C Hutton; R Turner
Journal:  Neuroimage       Date:  2003-06       Impact factor: 6.556

3.  Neural signatures of economic preferences for risk and ambiguity.

Authors:  Scott A Huettel; C Jill Stowe; Evan M Gordon; Brent T Warner; Michael L Platt
Journal:  Neuron       Date:  2006-03-02       Impact factor: 17.173

Review 4.  Understanding risk: a guide for the perplexed.

Authors:  Paul W Glimcher
Journal:  Cogn Affect Behav Neurosci       Date:  2008-12       Impact factor: 3.282

5.  Neural representation of subjective value under risk and ambiguity.

Authors:  Ifat Levy; Jason Snell; Amy J Nelson; Aldo Rustichini; Paul W Glimcher
Journal:  J Neurophysiol       Date:  2009-12-23       Impact factor: 2.714

6.  Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a cluster-size threshold.

Authors:  S D Forman; J D Cohen; M Fitzgerald; W F Eddy; M A Mintun; D C Noll
Journal:  Magn Reson Med       Date:  1995-05       Impact factor: 4.668

7.  Linear systems analysis of functional magnetic resonance imaging in human V1.

Authors:  G M Boynton; S A Engel; G H Glover; D J Heeger
Journal:  J Neurosci       Date:  1996-07-01       Impact factor: 6.167

8.  Neural systems responding to degrees of uncertainty in human decision-making.

Authors:  Ming Hsu; Meghana Bhatt; Ralph Adolphs; Daniel Tranel; Colin F Camerer
Journal:  Science       Date:  2005-12-09       Impact factor: 47.728

  8 in total
  10 in total

Review 1.  Computational psychiatry of impulsivity and risk: how risk and time preferences interact in health and disease.

Authors:  Silvia Lopez-Guzman; Anna B Konova; Paul W Glimcher
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-02-18       Impact factor: 6.237

2.  Computational Markers of Risky Decision-making for Identification of Temporal Windows of Vulnerability to Opioid Use in a Real-world Clinical Setting.

Authors:  Anna B Konova; Silvia Lopez-Guzman; Adelya Urmanche; Stephen Ross; Kenway Louie; John Rotrosen; Paul W Glimcher
Journal:  JAMA Psychiatry       Date:  2020-04-01       Impact factor: 21.596

3.  Neuroanatomy predicts individual risk attitudes.

Authors:  Sharon Gilaie-Dotan; Agnieszka Tymula; Nicole Cooper; Joseph W Kable; Paul W Glimcher; Ifat Levy
Journal:  J Neurosci       Date:  2014-09-10       Impact factor: 6.167

4.  POSTTRAUMATIC STRESS SYMPTOMS AND AVERSION TO AMBIGUOUS LOSSES IN COMBAT VETERANS.

Authors:  Lital Ruderman; Daniel B Ehrlich; Alicia Roy; Robert H Pietrzak; Ilan Harpaz-Rotem; Ifat Levy
Journal:  Depress Anxiety       Date:  2016-03-21       Impact factor: 6.505

5.  Monetary, Food, and Social Rewards Induce Similar Pavlovian-to-Instrumental Transfer Effects.

Authors:  Rea Lehner; Joshua H Balsters; Andreas Herger; Todd A Hare; Nicole Wenderoth
Journal:  Front Behav Neurosci       Date:  2017-01-04       Impact factor: 3.558

6.  Learning about the Ellsberg Paradox reduces, but does not abolish, ambiguity aversion.

Authors:  Ruonan Jia; Ellen Furlong; Sean Gao; Laurie R Santos; Ifat Levy
Journal:  PLoS One       Date:  2020-03-04       Impact factor: 3.240

7.  Experimentally revealed stochastic preferences for multicomponent choice options.

Authors:  Alexandre Pastor-Bernier; Konstantin Volkmann; Arkadiusz Stasiak; Fabian Grabenhorst; Wolfram Schultz
Journal:  J Exp Psychol Anim Learn Cogn       Date:  2020-07-27       Impact factor: 2.478

8.  Neuroanatomy accounts for age-related changes in risk preferences.

Authors:  Michael A Grubb; Agnieszka Tymula; Sharon Gilaie-Dotan; Paul W Glimcher; Ifat Levy
Journal:  Nat Commun       Date:  2016-12-13       Impact factor: 14.919

9.  Risk preferences impose a hidden distortion on measures of choice impulsivity.

Authors:  Silvia Lopez-Guzman; Anna B Konova; Kenway Louie; Paul W Glimcher
Journal:  PLoS One       Date:  2018-01-26       Impact factor: 3.240

10.  Blunted Ambiguity Aversion During Cost-Benefit Decisions in Antisocial Individuals.

Authors:  Joshua W Buckholtz; Uma Karmarkar; Shengxuan Ye; Grace M Brennan; Arielle Baskin-Sommers
Journal:  Sci Rep       Date:  2017-05-17       Impact factor: 4.379

  10 in total

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