Do individual differences in Iowa Gambling Task performance predict adaptive decision making for risky gains and losses?

2009 ◽  
Vol 32 (2) ◽  
pp. 141-150 ◽  
Author(s):  
Joshua A. Weller ◽  
Irwin P. Levin ◽  
Antoine Bechara
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Task Performance ◽  
Iowa Gambling Task ◽  
Gambling Task ◽  
Gains And Losses ◽  
Adaptive Decision Making

Decision-making and cognitive abilities: A review of associations between Iowa Gambling Task performance, executive functions, and intelligence

2010 ◽  
Vol 30 (5) ◽  
pp. 562-581 ◽  
Author(s):  
Maggie E. Toplak ◽  
Geoff B. Sorge ◽  
André Benoit ◽  
Richard F. West ◽  
Keith E. Stanovich
Keyword(s):  
Decision Making ◽  
Executive Functions ◽  
Task Performance ◽  
Cognitive Abilities ◽  
Iowa Gambling Task ◽  
Gambling Task

scholarly journals How structural brain network topologies associate with cognitive abilities in a value-based decision-making task

2019 ◽  
Author(s):  
Cristina Bañuelos ◽  
Timothy Verstynen
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Principal Components ◽  
Iowa Gambling Task ◽  
Brain Networks ◽  
Structural Connectivity ◽  
Brain Network ◽  
Gambling Task ◽  
Structural Brain Network ◽  
Structural Brain

Value-based decision-making relies on effective communication across disparate brain networks. Given the scale of the networks involved in adaptive decision-making, variability in how they communicate should impact behavior; however, precisely how the topological pattern of structural connectivity of individual brain networks influences individual differences in value-based decision-making remains unclear. Using diffusion MRI, we measured structural connectivity networks in a sample of community dwelling adults (N=124). We used standard graph theoretic measures to characterize the topology of the networks in each individual and correlated individual differences in these topology measures with differences in the Iowa Gambling Task. A principal components regression approach revealed that individual differences in brain network topology associate with differences in optimal decision-making, as well as associate with differences in each participant’s sensitivity to high frequency rewards. These findings show that aspects of structural brain network organization can constrain how information is used in value-based decision-making.AbbreviationsMRI - Magnetic Resonance Imaging; IGT – Iowa Gambling Task; DWI – Diffusion Weighted Imaging; QSDR – Q-Space Diffeomorphic Reconstruction; PCA – Principal Components Analysis; GLM – Generalized Linear Models

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