Literature DB >> 19228976

Neural response to reward anticipation under risk is nonlinear in probabilities.

Ming Hsu1, Ian Krajbich, Chen Zhao, Colin F Camerer.   

Abstract

A widely observed phenomenon in decision making under risk is the apparent overweighting of unlikely events and the underweighting of nearly certain events. This violates standard assumptions in expected utility theory, which requires that expected utility be linear (objective) in probabilities. Models such as prospect theory have relaxed this assumption and introduced the notion of a "probability weighting function," which captures the key properties found in experimental data. This study reports functional magnetic resonance imaging (fMRI) data that neural response to expected reward is nonlinear in probabilities. Specifically, we found that activity in the striatum during valuation of monetary gambles are nonlinear in probabilities in the pattern predicted by prospect theory, suggesting that probability distortion is reflected at the level of the reward encoding process. The degree of nonlinearity reflected in individual subjects' decisions is also correlated with striatal activity across subjects. Our results shed light on the neural mechanisms of reward processing, and have implications for future neuroscientific studies of decision making involving extreme tails of the distribution, where probability weighting provides an explanation for commonly observed behavioral anomalies.

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Year:  2009        PMID: 19228976      PMCID: PMC6666337          DOI: 10.1523/JNEUROSCI.5296-08.2009

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  80 in total

Review 1.  Common and distinct networks underlying reward valence and processing stages: a meta-analysis of functional neuroimaging studies.

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2.  Sleep deprivation is associated with attenuated parametric valuation and control signals in the midbrain during value-based decision making.

Authors:  Mareike M Menz; Christian Büchel; Jan Peters
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3.  Informatic parcellation of the network involved in the computation of subjective value.

Authors:  John A Clithero; Antonio Rangel
Journal:  Soc Cogn Affect Neurosci       Date:  2013-07-24       Impact factor: 3.436

Review 4.  The reward circuit: linking primate anatomy and human imaging.

Authors:  Suzanne N Haber; Brian Knutson
Journal:  Neuropsychopharmacology       Date:  2010-01       Impact factor: 7.853

Review 5.  Reinforcement learning, conditioning, and the brain: Successes and challenges.

Authors:  Tiago V Maia
Journal:  Cogn Affect Behav Neurosci       Date:  2009-12       Impact factor: 3.282

6.  Reward skewness coding in the insula independent of probability and loss.

Authors:  Christopher J Burke; Philippe N Tobler
Journal:  J Neurophysiol       Date:  2011-08-17       Impact factor: 2.714

Review 7.  Decision Making Under Objective Risk Conditions-a Review of Cognitive and Emotional Correlates, Strategies, Feedback Processing, and External Influences.

Authors:  Johannes Schiebener; Matthias Brand
Journal:  Neuropsychol Rev       Date:  2015-04-18       Impact factor: 7.444

8.  Dissociable effects of surprising rewards on learning and memory.

Authors:  Nina Rouhani; Kenneth A Norman; Yael Niv
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2018-03-19       Impact factor: 3.051

9.  Impulsive choice and response in dopamine agonist-related impulse control behaviors.

Authors:  Valerie Voon; Brady Reynolds; Christina Brezing; Cecile Gallea; Meliha Skaljic; Vindhya Ekanayake; Hubert Fernandez; Marc N Potenza; Raymond J Dolan; Mark Hallett
Journal:  Psychopharmacology (Berl)       Date:  2009-10-20       Impact factor: 4.530

10.  Reference and preference: how does the brain scale subjective value?

Authors:  John A Clithero; David V Smith
Journal:  Front Hum Neurosci       Date:  2009-07-08       Impact factor: 3.169

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