Older Adults as Adaptive Decision Makers: Evidence From the Iowa Gambling Task.

Older adults process emotional information differently than younger adults and may demonstrate less of a negativity bias on cognitive tasks. The Iowa Gambling Task designed by A. Bechara, H. Damasio, D. Tranel, and A. R. Damasio (1997) has been used to examine the integration of emotion and cognition in a risky-choice decision task and may give insight into differences in the decision-making strategies in younger and older adults. Eighty-eight younger adults (18-34 years) and 67 older adults (65-88 years) completed the Iowa Gambling Task. Using a theoretical decomposition of the task designed by J. R. Busemeyer and J. C. Stout (2002), the authors found that both groups were successful at solving the task but used very different strategies that reflected each group's strength. For younger adults, that strength was learning and memory. For older adults, that strength was an accurate representation of wins and losses (valence). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Application of a computational decision model to examine acute drug effects on human risk taking.

In 3 previous experiments, high doses of alcohol, marijuana, and alprazolam acutely increased risky decision making by adult humans in a 2-choice (risky vs. nonrisky) laboratory task. In this study, a computational modeling analysis known as the expectancy valence model (J. R. Busemeyer & J. C. Stout, 2002) was applied to individual-participant data from these studies, for the highest administered dose of all 3 drugs and corresponding placebo doses, to determine changes in decision-making processes that may be uniquely engendered by each drug. The model includes 3 parameters: responsiveness to rewards and losses (valence or motivation); the rate of updating expectancies about the value of risky alternatives (learning/memory); and the consistency with which trial-by-trial choices match expected outcomes (sensitivity). Parameter estimates revealed 3 key outcomes: Alcohol increased responsiveness to risky rewards and decreased responsiveness to risky losses (motivation) but did not alter expectancy updating (learning/memory); both marijuana and alprazolam produced increases in risk taking that were related to learning/memory but not motivation; and alcohol and marijuana (but not alprazolam) produced more random response patterns that were less consistently related to expected outcomes on the 2 choices. No significant main effects of gender or dose by gender interactions were obtained, but 2 dose by gender interactions approached significance. These outcomes underscore the utility of using a computational modeling approach to deconstruct decision-making processes and thus better understand drug effects on risky decision making in humans. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Analysis of multiplicative combination rules when the causal variables are measured with error.

Evaluates the validity of the observational method used to test multiplicative combination rules with respect to 2 measurement issues: measurement level (i.e., the effects produced by allowing monotonic transformations of the measures) and measurement error (i.e., the effects produced by using unreliable measures of the causal variables). The evaluation is based on a theoretical distinction between the structural model (the set of equations relating theoretical constructs to each other) and the measurement model (the set of equations relating the theoretical constructs to the observed measures). It is concluded that hierarchical regression analysis is inadequate for determining whether the structural model is additive or multiplicative for 2 reasons: First, an additive structural model may produce multiplicative effects through a nonlinear measurement model. Second, a multiplicative structural model may produce nondetectable multiplicative effects because of multiplicative measurement error. Some alternatives to hierarchical regression analysis are described. (35 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An adaptive approach to human decision making: Learning theory, decision theory, and human performance.

Describes a general model of decision rule learning, the rule competition model, composed of 2 parts: an adaptive network model that describes how individuals learn to predict the payoffs produced by applying each decision rule for any given situation and a hill-climbing model that describes how individuals learn to fine tune each rule by adjusting its parameters. The model was tested and compared with other models in 3 experiments on probabilistic categorization. The 1st experiment was designed to test the adaptive network model using a probability learning task, the 2nd was designed to test the parameter search process using a criterion learning task, and the 3rd was designed to test both parts of the model simultaneously by using a task that required learning both category and cutoff criteria. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Decision field theory: A dynamic-cognitive approach to decision making in an uncertain environment.

Decision field theory provides for a mathematical foundation leading to a dynamic, stochastic theory of decision behavior in an uncertain environment. This theory is used to explain (1) violations of stochastic dominance, (2) violations of strong stochastic transitivity, (3) violations of independence between alternatives, (4) serial position effects on preference, (5) speed–accuracy trade-off effects in decision making, (6) the inverse relation between choice probability and decision time, (7) changes in the direction of preference under time pressure, (8) slower decision times for avoidance as compared with approach conflicts, and (9) preference reversals between choice and selling price measures of preference. The proposed theory is compared with 4 other theories of decision making under uncertainty. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Temporal discounting of rewards in patients with bipolar disorder and schizophrenia.

Patients with bipolar disorder (BD) and schizophrenia (SZ) often show decision-making deficits in everyday circumstances. A failure to appropriately weigh immediate versus future consequences of choices may contribute to these deficits. We used the delay discounting task in individuals with BD or SZ to investigate their temporal decision making. Twenty-two individuals with BD, 21 individuals with SZ, and 30 healthy individuals completed the delay discounting task along with neuropsychological measures of working memory and cognitive function. Both BD and SZ groups discounted delayed rewards more steeply than did the healthy group even after controlling for current substance use, age, gender, and employment. Hierarchical multiple regression analyses showed that discounting rate was associated with both diagnostic group and working memory or intelligence scores. In each group, working memory or intelligence scores negatively correlated with discounting rate. The results suggest that (a) both BD and SZ groups value smaller, immediate rewards more than larger, delayed rewards compared with the healthy group and (b) working memory or intelligence is related to temporal decision making in individuals with BD or SZ as well as in healthy individuals. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Psychological Processes Underlying Risky Decisions in Drug Abusers.

Decision-making deficits are considered to be a significant contributing factor for drug abuse. Drug abusers performed poorly on a simulated gambling task (A. Bechara, H. Damasio, D. Tranel, & S. Anderson, 1994); however, the psychological processes that contribute to these deficits are unknown. The authors used cognitive decision models with a simulated gambling task (SGT) to examine underlying processes of decision making in 66 drug abusers and 58 control participants. As expected, male drug abusers performed more poorly than male controls, and model results showed that male drug abusers placed greater emphasis on wins. The findings for women were less clear because control women performed at chance level on the SGT. Additional studies of gender differences on the SGT are needed to clarify these findings of discrepant performance in the control women. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effects of parent counseling on the family system.

To study the impact of a parent counseling program, all members of 11 experimental families and 9 lecture-control families were evaluated before and after 7 wkly counseling sessions and at a 6–8 mo follow-up. Parents in both conditions reflected a significant increase in perceived marital adjustment (Locke-Wallace Marital Adjustment Scale) at posttesting and at follow-up. The children of parents in both groups demonstrated significant increases in self-esteem (Self-Esteem Inventory) after treatment; improvement was maintained at follow-up. Findings suggest that for educated, middle-income families, the critical components in parent counseling may be the mere presentation of information and didactic instruction. (25 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A model-based fMRI analysis with hierarchical Bayesian parameter estimation.

A recent trend in decision neuroscience is the use of model-based functional magnetic resonance imaging (fMRI) using mathematical models of cognitive processes. However, most previous model-based fMRI studies have ignored individual differences because of the challenge of obtaining reliable parameter estimates for individual participants. Meanwhile, previous cognitive science studies have demonstrated that hierarchical Bayesian analysis is useful for obtaining reliable parameter estimates in cognitive models while allowing for individual differences. Here we demonstrate the application of hierarchical Bayesian parameter estimation to model-based fMRI using the example of decision making in the Iowa Gambling Task. First, we used a simulation study to demonstrate that hierarchical Bayesian analysis outperforms conventional (individual- or group-level) maximum likelihood estimation in recovering true parameters. Then we performed model-based fMRI analyses on experimental data to examine how the fMRI results depend on the estimation method. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Motivational Processing and Choice Behavior During Television Viewing: An Integrative Dynamic Approach

This study was designed to further our understanding of the central role of motivational activation in mediated information processing and media choice. To do this, a dynamic model was developed to formalize the dynamic effects of three basic motivational input variables (arousing content, positivity, and negativity) on four physiological output measures (heart rate, skin conductance level, corrugator activity, and zygomatic activity) and a behavioral choice measure of television channel selection. The input and output variables were selected based on extensive theoretical and empirical research that has explicated static relationships among these variables. In general, the findings of the dynamic modeling approach were consistent with the previous literature using traditional static statistical methods. However, this study also theoretically extended the previous work.