A mixed-effects expectancy-valence model for the Iowa gambling task

Diurnal cortisol rhythm is associated with increased risky decision-making in older adults

Although past research has suggested a link between chronic stress and both physical and mental well-being in older adults, less is known about the degree to which neuroendocrine markers of stress are associated with higher-order cognitive processes such as decision-making. In a sample of healthy older adults (55-85 years), we tested the degree to which variation in the diurnal cortisol rhythm, an index of hypothalamic-adrenal-pituitary axis dynamics, was related to differences in risky decision-making. We found that diurnal cortisol fall predicted performance on the Cups Task, a risky decision-making task that independently tests risk-taking to achieve gains and risk-taking to avoid losses. For potential gains, we found that greater risk-taking was associated with lower diurnal cortisol fall, independent of age or sex of the participant. For risks to avoid potential losses, we found that lower diurnal fall was associated with suboptimal decision-making for men only. Compared with males with more typical diurnal fall, those who displayed lower diurnal fall made more risky choices and demonstrated lower sensitivity to the expected value of the risky choice. We integrate these results with the extant literature on the effects of stress on decision-making and cognitive aging.

Normal aging and decision-making: a systematic review of the literature of the last 10 years

Objective Conduct a systematic review to investigate whether healthy elderly have deficits in the decision-making process when compared to the young. Methods We performed a systematic search on SciELO, Lilacs, PsycINFO, Scopus and PubMed database with keywords decision making and aging (according to the description of Mesh terms) at least 10 years. Results We found nine studies from different countries, who investigated 441 young and 377 elderly. All studies used the IOWA Gambling Task as a way of benchmarking the process of decision making. The analysis showed that 78% of the articles did not have significant differences between groups. However, 100% of the studies that assessed learning did find relevant differences. Furthermore, studies that observed the behavior of individuals in the face of losses and gains, 60% of articles showed that the elderly has more disadvantageous choices throughout the task. Conclusion: The consulted literature showed no consensus on the existence of differences in performance of the decision-making process between old and young, but it is observed that the elderly has deficits in learning and a tendency to fewer advantageous choices.

Using cognitive modelling to investigate the psychological processes of the Go/NoGo discrimination task in male abstinent heroin misusers

AIMS

To use cognitive modelling to investigate psychological processes underlying decision-making in male abstinent heroin misusers (AHMs).

DESIGN

A case-control study design.

SETTING

A drug misuse treatment centre in Taiwan.

PARTICIPANTS

Eighty-eight male AHMs and 48 male controls.

MEASUREMENTS

Four parameters representing the attention to wins, learning rate, response sensitivity and incentive of heroin-related stimuli from the modified Go/NoGo discrimination task.

FINDINGS

A modified cue-dependent learning (CD) model with four parameters representing attention to wins, learning rate, response sensitivity and incentive of heroin-related stimuli had a lower value of the sum of Bayesian information criterion (showing a better fit) than the original CD model (9555.50 versus 11,192.22, P < 0.001). The AHM group had a higher value of the heroin-incentive parameter than the control group (0.26 versus -1.66, P < 0.05). The attention to wins and heroin-incentive parameters were associated positively with total commission rate and negatively with total omission rate in the AHM group (P < 0.001).

CONCLUSIONS

Male abstinent heroin misusers appear to be more influenced by heroin-related stimuli during decision-making than males with no history of heroin misuse.

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

The present study focuses on the role of frequency bias and expected value on the learning processes driving performance on the Iowa Gambling Task (IGT) in individuals between 5 and 89 years of age. As in previous studies, children performed poorly on the IGT, were increasingly influenced by frequency of losses during learning, and constantly changed their decisions. Decision-making strategies changed after childhood from erratic behavior to more consistent strategies that promoted expected value of deck choices. Performance deficits as well as a loss frequency bias were found in older adults. However, age-related deficits were distinct between children and older adults. Cognitive modeling analysis indicated that older adults were more likely to forget about recent outcomes and were more consistent than children when selecting decks. Cognitive ability was associated with a modeling parameter for memory as well as IGT performance, suggesting the involvement of a cognitive component in young and middle-aged adult decision making. The interactions of modeling parameters suggested that cognitive changes were the cause of lowered performance in older adults. These analyses suggest critical developments in decision processes during the adolescent years and decline in a cognitive process leading to decision-making deficits after age 60.

Twice random, once mixed: applying mixed models to simultaneously analyze random effects of language and participants

Psychologists, psycholinguists, and other researchers using language stimuli have been struggling for more than 30 years with the problem of how to analyze experimental data that contain two crossed random effects (items and participants). The classical analysis of variance does not apply; alternatives have been proposed but have failed to catch on, and a statistically unsatisfactory procedure of using two approximations (known as F(1) and F(2)) has become the standard. A simple and elegant solution using mixed model analysis has been available for 15 years, and recent improvements in statistical software have made mixed models analysis widely available. The aim of this article is to increase the use of mixed models by giving a concise practical introduction and by giving clear directions for undertaking the analysis in the most popular statistical packages. The article also introduces the DJMIXED: add-on package for SPSS, which makes entering the models and reporting their results as straightforward as possible.

Iowa gambling task: there is more to consider than long-term outcome. Using a linear equation model to disentangle the impact of outcome and frequency of gains and losses

The Iowa Gambling Task (IGT) has been widely used to assess differences in decision-making under uncertainty. Recently, several studies have shown that healthy subjects do not meet the basic predictions of the task (i.e., prefer options with positive long-term outcome), hence questioning its basic assumptions. Since choice options are characterized by gain and net loss frequency in addition to long-term outcome, we hypothesized that a combination of features rather than a single feature would influence participants’ choices. Offering an alternative way of modeling IGT data, we propose to use a system of linear equations to estimate weights that quantify the influence of each individual feature on decision-making in the IGT. With our proposed model it is possible to disentangle and quantify the impact of each of these features. Results from 119 healthy young subjects suggest that choice behavior is predominantly influenced by gain and loss frequency. Subjects preferred choices associated with high-frequency gains to those with low-frequency gains, regardless of long-term outcome. However, among options with low-frequency gains, subjects learned to distinguish between choices that led to advantageous and disadvantageous long-term consequences. This is reflected in the relationship between the weights for gain frequency (highest), loss frequency (intermediate), and long-term outcome (lowest). Further, cluster analysis of estimated feature weights revealed sub-groups of participants with distinct weight patterns and associated advantageous decision behavior. However, subjects in general do not learn to solely base their preference for particular decks on expected long-term outcome. Consequently, long-term outcome alone is not able to drive choice behavior on the IGT. In sum, our model facilitates a more focused conclusion about the factors guiding decision-making in the IGT. In addition, differences between clinical groups can be assessed for each factor individually.