Literature DB >> 31023835

Salience-Driven Value Construction for Adaptive Choice under Risk.

Mehran Spitmaan1, Emily Chu1, Alireza Soltani2.   

Abstract

Decisions we face in real life are inherently risky and can result in one of many possible outcomes. However, most of what we know about choice under risk is based on studies that use options with only two possible outcomes (simple gambles), so it remains unclear how the brain constructs reward values for more complex risky options faced in real life. To address this question, we combined experimental and modeling approaches to examine choice between pairs of simple gambles and pairs of three-outcome gambles in male and female human subjects. We found that subjects evaluated individual outcomes of three-outcome gambles by multiplying functions of reward magnitude and probability. To construct the overall value of each gamble, however, most subjects differentially weighted possible outcomes based on either reward magnitude or probability. These results reveal a novel dissociation between how reward information is processed when evaluating complex gambles: valuation of each outcome is based on a combination of reward information whereas weighting of possible outcomes mainly relies on a single piece of reward information. We show that differential weighting of possible outcomes could enable subjects to make decisions more easily and quickly. Together, our findings reveal a plausible mechanism for how salience, in terms of possible reward magnitude or probability, can influence the construction of subjective values for complex gambles. They also point to separable neural mechanisms for how reward value controls choice and attention to allow for more adaptive decision making under risk.SIGNIFICANCE STATEMENT Real-life decisions are inherently risky and can result in one of many possible outcomes, but how does the brain integrate information from all these outcomes to make decisions? To address this question, we examined choice between pairs of gambles with multiple outcomes using various computational models. We found that subjects evaluated individual outcomes by multiplying functions of reward magnitude and probability. To construct the overall value of each gamble, however, they differentially weighted possible outcomes based on either reward magnitude or probability. By doing so, they were able to make decisions more easily and quickly. Our findings illustrate how salience, in terms of possible reward magnitude or probability, can influence the construction of subjective values for more adaptive choice.
Copyright © 2019 the authors.

Entities:  

Keywords:  attention; heuristics; prospect theory; reward; valuation

Year:  2019        PMID: 31023835      PMCID: PMC6595946          DOI: 10.1523/JNEUROSCI.2522-18.2019

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


  38 in total

1.  Précis of Simple heuristics that make us smart.

Authors:  P M Todd; G Gigerenzer
Journal:  Behav Brain Sci       Date:  2000-10       Impact factor: 12.579

2.  On the shape of the probability weighting function.

Authors:  R Gonzalez; G Wu
Journal:  Cogn Psychol       Date:  1999-02       Impact factor: 3.468

3.  Competitive mechanisms subserve attention in macaque areas V2 and V4.

Authors:  J H Reynolds; L Chelazzi; R Desimone
Journal:  J Neurosci       Date:  1999-03-01       Impact factor: 6.167

Review 4.  The neural basis of biased competition in human visual cortex.

Authors:  S Kastner; L G Ungerleider
Journal:  Neuropsychologia       Date:  2001       Impact factor: 3.139

5.  Multialternative decision field theory: a dynamic connectionist model of decision making.

Authors:  R M Roe; J R Busemeyer; J T Townsend
Journal:  Psychol Rev       Date:  2001-04       Impact factor: 8.934

6.  Prospect relativity: how choice options influence decision under risk.

Authors:  Neil Stewart; Nick Chater; Henry P Stott; Stian Reimers
Journal:  J Exp Psychol Gen       Date:  2003-03

Review 7.  What attributes guide the deployment of visual attention and how do they do it?

Authors:  Jeremy M Wolfe; Todd S Horowitz
Journal:  Nat Rev Neurosci       Date:  2004-06       Impact factor: 34.870

8.  Stimulus context modulates competition in human extrastriate cortex.

Authors:  Diane M Beck; Sabine Kastner
Journal:  Nat Neurosci       Date:  2005-07-10       Impact factor: 24.884

9.  Deciding how to decide: ventromedial frontal lobe damage affects information acquisition in multi-attribute decision making.

Authors:  Lesley K Fellows
Journal:  Brain       Date:  2006-02-02       Impact factor: 13.501

10.  Gaze bias both reflects and influences preference.

Authors:  Shinsuke Shimojo; Claudiu Simion; Eiko Shimojo; Christian Scheier
Journal:  Nat Neurosci       Date:  2003-11-09       Impact factor: 24.884

View more
  2 in total

1.  Combinations of low-level and high-level neural processes account for distinct patterns of context-dependent choice.

Authors:  Mehran Spitmaan; Oihane Horno; Emily Chu; Alireza Soltani
Journal:  PLoS Comput Biol       Date:  2019-10-14       Impact factor: 4.475

2.  Orbitofrontal signals for two-component choice options comply with indifference curves of Revealed Preference Theory.

Authors:  Alexandre Pastor-Bernier; Arkadiusz Stasiak; Wolfram Schultz
Journal:  Nat Commun       Date:  2019-10-25       Impact factor: 14.919

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.