Literature DB >> 24523519

Intelligence moderates neural responses to monetary reward and punishment.

Daniel R Hawes1, Colin G DeYoung, Jeremy R Gray, Aldo Rustichini.   

Abstract

The relations between intelligence (IQ) and neural responses to monetary gains and losses were investigated in a simple decision task. In 94 healthy adults, typical responses of striatal blood oxygen level-dependent (BOLD) signal after monetary reward and punishment were weaker for subjects with higher IQ. IQ-moderated differential responses to gains and losses were also found for regions in the medial prefrontal cortex, posterior cingulate cortex, and left inferior frontal cortex. These regions have previously been identified with the subjective utility of monetary outcomes. Analysis of subjects' behavior revealed a correlation between IQ and the extent to which choices were related to experienced decision outcomes in preceding trials. Specifically, higher IQ predicted behavior to be more strongly correlated with an extended period of previously experienced decision outcomes, whereas lower IQ predicted behavior to be correlated exclusively to the most recent decision outcomes. We link these behavioral and imaging findings to a theoretical model capable of describing a role for intelligence during the evaluation of rewards generated by unknown probabilistic processes. Our results demonstrate neural differences in how people of different intelligence respond to experienced monetary rewards and punishments. Our theoretical discussion offers a functional description for how these individual differences may be linked to choice behavior. Together, our results and model support the hypothesis that observed correlations between intelligence and preferences may be rooted in the way decision outcomes are experienced ex post, rather than deriving exclusively from how choices are evaluated ex ante.

Entities:  

Keywords:  decision making; intelligence; punishment; reinforcement learning; reward; risk

Mesh:

Year:  2014        PMID: 24523519      PMCID: PMC4044365          DOI: 10.1152/jn.00393.2013

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  22 in total

1.  Tracking the hemodynamic responses to reward and punishment in the striatum.

Authors:  M R Delgado; L E Nystrom; C Fissell; D C Noll; J A Fiez
Journal:  J Neurophysiol       Date:  2000-12       Impact factor: 2.714

2.  Interaction of COMT val158met and externalizing behavior: relation to prefrontal brain activity and behavioral performance.

Authors:  Zarrar Shehzad; Colin G DeYoung; Yoona Kang; Elena L Grigorenko; Jeremy R Gray
Journal:  Neuroimage       Date:  2012-01-28       Impact factor: 6.556

3.  Childhood intelligence, educational attainment and adult body mass index: findings from a prospective cohort and within sibling-pairs analysis.

Authors:  D A Lawlor; H Clark; G Davey Smith; D A Leon
Journal:  Int J Obes (Lond)       Date:  2006-03-21       Impact factor: 5.095

Review 4.  Reward-related responses in the human striatum.

Authors:  Mauricio R Delgado
Journal:  Ann N Y Acad Sci       Date:  2007-03-07       Impact factor: 5.691

5.  Neuroeconomics: what have we found, and what should we search for.

Authors:  Aldo Rustichini
Journal:  Curr Opin Neurobiol       Date:  2009-11-04       Impact factor: 6.627

6.  Puzzlingly High Correlations in fMRI Studies of Emotion, Personality, and Social Cognition.

Authors:  Edward Vul; Christine Harris; Piotr Winkielman; Harold Pashler
Journal:  Perspect Psychol Sci       Date:  2009-05

7.  The neural correlates of subjective utility of monetary outcome and probability weight in economic and in motor decision under risk.

Authors:  Shih-Wei Wu; Mauricio R Delgado; Laurence T Maloney
Journal:  J Neurosci       Date:  2011-06-15       Impact factor: 6.167

8.  How instructed knowledge modulates the neural systems of reward learning.

Authors:  Jian Li; Mauricio R Delgado; Elizabeth A Phelps
Journal:  Proc Natl Acad Sci U S A       Date:  2010-12-20       Impact factor: 11.205

9.  Reinforcement learning signals in the human striatum distinguish learners from nonlearners during reward-based decision making.

Authors:  Tom Schönberg; Nathaniel D Daw; Daphna Joel; John P O'Doherty
Journal:  J Neurosci       Date:  2007-11-21       Impact factor: 6.167

Review 10.  FSL.

Authors:  Mark Jenkinson; Christian F Beckmann; Timothy E J Behrens; Mark W Woolrich; Stephen M Smith
Journal:  Neuroimage       Date:  2011-09-16       Impact factor: 6.556

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  3 in total

1.  Subcortical intelligence: caudate volume predicts IQ in healthy adults.

Authors:  Rachael G Grazioplene; Sephira G Ryman; Jeremy R Gray; Aldo Rustichini; Rex E Jung; Colin G DeYoung
Journal:  Hum Brain Mapp       Date:  2014-12-09       Impact factor: 5.038

Review 2.  Intelligence moderates reinforcement learning: a mini-review of the neural evidence.

Authors:  Chong Chen
Journal:  J Neurophysiol       Date:  2014-09-03       Impact factor: 2.714

3.  Evaluation of the Social Motivation Hypothesis of Autism: A Systematic Review and Meta-analysis.

Authors:  Caitlin C Clements; Alisa R Zoltowski; Lisa D Yankowitz; Benjamin E Yerys; Robert T Schultz; John D Herrington
Journal:  JAMA Psychiatry       Date:  2018-08-01       Impact factor: 21.596

  3 in total

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