Kaileigh A. Byrne

Decomposing the roles of perseveration and expected value representation in models of the Iowa gambling task

Models of human behavior in the Iowa Gambling Task (IGT) have played a pivotal role in accounting for behavioral differences during decision-making. One critical difference between models that have been used to account for behavior in the IGT is the inclusion or exclusion of the assumption that participants tend to persevere, or stay with the same option over consecutive trials. Models that allow for this assumption include win-stay-lose-shift (WSLS) models and reinforcement learning (RL) models that include a decay learning rule where expected values for each option decay as they are chosen less often. One shortcoming of RL models that have included decay rules is that the tendency to persevere by sticking with the same option has been conflated with the tendency to select the option with the highest expected value because a single term is used to represent both of these tendencies. In the current work we isolate the tendencies to perseverate and to select the option with the highest expected value by including them as separate terms in a Value-Plus-Perseveration (VPP) RL model. Overall the VPP model provides a better fit to data from a large group of participants than models that include a single term to account for both perseveration and the representation of expected value. Simulations of each model show that the VPP models simulated choices most closely resemble the decision-making behavior of human subjects. In addition, we also find that parameter estimates of loss aversion are more strongly correlated with performance when perseverative tendencies and expected value representations are decomposed as separate terms within the model. The results suggest that the tendency to persevere and the tendency to select the option that leads to the best net payoff are central components of decision-making behavior in the IGT. Future work should use this model to better examine decision-making behavior.

State-based versus reward-based motivation in younger and older adults.

Recent decision-making work has focused on a distinction between a habitual, model-free neural system that is motivated toward actions that lead directly to reward and a more computationally demanding goal-directed, model-based system that is motivated toward actions that improve one’s future state. In this article, we examine how aging affects motivation toward reward-based versus state-based decision making. Participants performed tasks in which one type of option provided larger immediate rewards but the alternative type of option led to larger rewards on future trials, or improvements in state. We predicted that older adults would show a reduced preference for choices that led to improvements in state and a greater preference for choices that maximized immediate reward. We also predicted that fits from a hybrid reinforcement-learning model would indicate greater model-based strategy use in younger than in older adults. In line with these predictions, older adults selected the options that maximized reward more often than did younger adults in three of the four tasks, and modeling results suggested reduced model-based strategy use. In the task where older adults showed similar behavior to younger adults, our model-fitting results suggested that this was due to the utilization of a win-stay–lose-shift heuristic rather than a more complex model-based strategy. Additionally, within older adults, we found that model-based strategy use was positively correlated with memory measures from our neuropsychological test battery. We suggest that this shift from state-based to reward-based motivation may be due to age related declines in the neural structures needed for more computationally demanding model-based decision making.

Dopamine, depressive symptoms, and decision-making: the relationship between spontaneous eye blink rate and depressive symptoms predicts Iowa Gambling Task performance

Depressive symptomatology has been associated with alterations in decision-making, although conclusions have been mixed, with depressed individuals showing impairments in some contexts but advantages in others. The dopaminergic system may link depressive symptoms with decision-making performance. We assessed the role of striatal dopamine D2 receptor density, using spontaneous eye blink rates, in moderating the relationship between depressive symptoms and decision-making performance in a large undergraduate sample that had not been screened for mental illness (N = 104). The regression results revealed that eye blink rate moderated the relationship between depressive symptoms and advantageous decisions on the Iowa Gambling Task, in which individuals with more depressive symptomatology and high blink rates (higher striatal dopamine D2 receptor density) performed better on the task. Our computational modeling results demonstrated that depressive symptoms alone were associated with enhanced loss-aversive behavior, whereas individuals with high blink rates and elevated depressive symptoms tended to persevere in selecting options that led to net gains (avoiding options with net losses). These findings suggest that variation in striatal dopamine D2 receptor availability in individuals with depressive symptoms may contribute to differences in decision-making behavior.

Striatal Dopamine, Externalizing Proneness, and Substance Abuse Effects on Wanting and Learning During Reward-Based Decision Making

We examined whether striatal dopamine moderates the impact of externalizing proneness (disinhibition) on reward-based decision making. Participants completed disinhibition and substance abuse subscales of the brief form Externalizing Spectrum Inventory and then performed a delay discounting task to assess preference for immediate rewards along with a dynamic decision making task that assessed long-term reward learning (i.e., inclination to choose larger delayed versus smaller immediate rewards). Striatal tonic dopamine levels were operationalized using spontaneous eyeblink rate. Regression analyses revealed that high disinhibition predicted greater delay discounting among participants with lower levels of striatal dopamine only, whereas substance abuse was associated with poorer long-term learning among individuals with lower levels of striatal dopamine, but better long-term learning in those with higher levels of striatal dopamine. These results suggest that disinhibition is more strongly associated with the wanting component of reward-based decision making, whereas substance abuse behavior is associated more with learning of long-term action-reward contingencies.

Dopaminergic genetic polymorphisms predict rule-based category learning

Dopaminergic genes play an important role in cognitive function. DRD2 and DARPP-32 dopamine receptor gene polymorphisms affect striatal dopamine binding potential, and the Val158Met single-nucleotide polymorphism of the COMT gene moderates dopamine availability in the pFC. Our study assesses the role of these gene polymorphisms on performance in two rule-based category learning tasks. Participants completed unidimensional and conjunctive rule-based tasks. In the unidimensional task, a rule along a single stimulus dimension can be used to distinguish category members. In contrast, a conjunctive rule utilizes a combination of two dimensions to distinguish category members. DRD2 C957T TT homozygotes outperformed C allele carriers on both tasks, and DARPP-32 AA homozygotes outperformed G allele carriers on both tasks. However, we found an interaction between COMT and task type where Met allele carriers outperformed Val homozygotes in the conjunctive rule task, but both groups performed equally well in the unidimensional task. Thus, striatal dopamine binding may play a critical role in both types of rule-based tasks, whereas prefrontal dopamine binding is important for learning more complex conjunctive rule tasks. Modeling results suggest that striatal dopaminergic genes influence selective attention processes whereas cortical genes mediate the ability to update complex rule representations.

Ostracism reduces reliance on poor advice from others during decision making

Decision-making is rarely context-free, and often both social information and non-social information are weighed into ones decisions. Incorporating information into a decision can be influenced by previous experiences. Ostracism has extensive effects, including taxing cognitive resources and increasing social monitoring. In decision-making situations, individuals are often faced with both objective and social information and must choose which information to include or filter out. How will ostracism affect the reliance on objective and social information during decision-making? Participants (N=245) in Experiment 1 were randomly assigned to be included or ostracized in a standardized, group task. They then performed a dynamic decision-making task that involved the presentation of either non-social (i.e. biased reward feedback) or social (i.e., poor advice from a previous participant) misleading information. In Experiment 2, participants (N=105) completed either the ostracism non-social condition or social misleading information condition with explicit instructions stating that the advice given was from an individual who did not partake in the group task. Ostracized individuals relied more on non-social misleading information and performed worse than included individuals. However, ostracized individuals discounted misleading social information and outperformed included individuals. Results of Experiment 2 replicated the findings of Experiment 1. Across two experiments, ostracized individuals were more critical of advice from others, both individuals who may have ostracized them and unrelated individuals. In other words, compared to included individuals, ostracized individuals underweighted advice from another individual, but overweighted non-social information during decision-making. We conclude that when deceptive objective information is present, ostracism results in disadvantageous decision-making.