Literature DB >> 35266414

Shuffle the Decks: Children Are Sensitive to Incidental Nonrandom Structure in a Sequential-Choice Task.

Alexander D S Breslav1, Nancy L Zucker2, Julia C Schechter2, Alesha Majors2, Tatyana Bidopia2, Bernard F Fuemmeler3, Scott H Kollins2, Scott A Huettel1.   

Abstract

As children age, they can learn increasingly complex features of environmental structure-a key prerequisite for adaptive decision-making. Yet when we tested children (N = 304, 4-13 years old) in the Children's Gambling Task, an age-appropriate variant of the Iowa Gambling Task, we found that age was negatively associated with performance. However, this paradoxical effect of age was found only in children who exhibited a maladaptive deplete-replenish bias, a tendency to shift choices after positive outcomes and repeat choices after negative outcomes. We found that this bias results from sensitivity to incidental nonrandom structure in the canonical, deterministic forms of these tasks-and that it would actually lead to optimal outcomes if the tasks were not deterministic. Our results illustrate that changes in decision-making across early childhood reflect, in part, increasing sensitivity to environmental structure.

Entities:  

Keywords:  decision-making; heuristics; learning; open data; open materials

Mesh:

Year:  2022        PMID: 35266414      PMCID: PMC9096196          DOI: 10.1177/09567976211042007

Source DB:  PubMed          Journal:  Psychol Sci        ISSN: 0956-7976


  34 in total

1.  Different underlying impairments in decision-making following ventromedial and dorsolateral frontal lobe damage in humans.

Authors:  Lesley K Fellows; Martha J Farah
Journal:  Cereb Cortex       Date:  2004-06-24       Impact factor: 5.357

2.  Deciding advantageously before knowing the advantageous strategy.

Authors:  A Bechara; H Damasio; D Tranel; A R Damasio
Journal:  Science       Date:  1997-02-28       Impact factor: 47.728

3.  From Creatures of Habit to Goal-Directed Learners: Tracking the Developmental Emergence of Model-Based Reinforcement Learning.

Authors:  Johannes H Decker; A Ross Otto; Nathaniel D Daw; Catherine A Hartley
Journal:  Psychol Sci       Date:  2016-04-15

4.  The REDCap consortium: Building an international community of software platform partners.

Authors:  Paul A Harris; Robert Taylor; Brenda L Minor; Veida Elliott; Michelle Fernandez; Lindsay O'Neal; Laura McLeod; Giovanni Delacqua; Francesco Delacqua; Jacqueline Kirby; Stephany N Duda
Journal:  J Biomed Inform       Date:  2019-05-09       Impact factor: 6.317

5.  Comparison of decision learning models using the generalization criterion method.

Authors:  Woo-Young Ahn; Jerome R Busemeyer; Eric-Jan Wagenmakers; Julie C Stout
Journal:  Cogn Sci       Date:  2008-12

6.  The Outcome-Representation Learning Model: A Novel Reinforcement Learning Model of the Iowa Gambling Task.

Authors:  Nathaniel Haines; Jasmin Vassileva; Woo-Young Ahn
Journal:  Cogn Sci       Date:  2018-10-05

7.  Complex decision-making in early childhood.

Authors:  Nancy Garon; Chris Moore
Journal:  Brain Cogn       Date:  2004-06       Impact factor: 2.310

8.  Performance on the Iowa Gambling Task: From 5 to 89 years of age.

Authors:  Kevin M Beitz; Timothy A Salthouse; Hasker P Davis
Journal:  J Exp Psychol Gen       Date:  2014-02-10

9.  The neuroscience of adolescent decision-making.

Authors:  Catherine A Hartley; Leah H Somerville
Journal:  Curr Opin Behav Sci       Date:  2015-10-01

10.  Folic acid supplementation before and during pregnancy in the Newborn Epigenetics STudy (NEST).

Authors:  Cathrine Hoyo; Amy P Murtha; Joellen M Schildkraut; Michele R Forman; Brian Calingaert; Wendy Demark-Wahnefried; Joanne Kurtzberg; Randy L Jirtle; Susan K Murphy
Journal:  BMC Public Health       Date:  2011-01-21       Impact factor: 3.295

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