Comparing Discounting of Potentially Real Rewards and Losses by Means of Functional Magnetic Resonance Imaging

AimDelay discounting (DD) has often been investigated in the context of decision making whereby individuals attribute decreasing value to rewards in the distant future. Less is known about DD in the context of negative consequences. The aim of this pilot study was to identify commonalities and differences between reward and loss discounting on the behavioral as well as the neural level by means of computational modeling and functional Magnetic Resonance Imaging (fMRI). We furthermore compared the neural activation between anticipation of rewards and losses.MethodWe conducted a study combining an intertemporal choice task for potentially real rewards and losses (decision-making) with a monetary incentive/loss delay task (reward/loss anticipation). Thirty healthy participants (age 18-35, 14 female) completed the study. In each trial, participants had to choose between a smaller immediate loss/win and a larger loss/win at a fixed delay of two weeks. Task-related brain activation was measured with fMRI.ResultsHyperbolic discounting parameters of loss and reward conditions were correlated (r = 0.56). During decision-making, BOLD activation was observed in the parietal and prefrontal cortex, with no differences between reward and loss conditions. During reward and loss anticipation, dissociable activation was observed in the striatum, the anterior insula and the anterior cingulate cortex.ConclusionWe observed behavior concurrent with DD in both the reward and loss condition, with evidence for similar behavioral and neural patterns in the two conditions. Intertemporal decision-making recruited the fronto-parietal network, whilst reward and loss anticipation were related to activation in the salience network. The interpretation of these findings may be limited to short delays and small monetary outcomes

Intolerance of uncertainty and impulsivity in opioid dependency

Opioid abuse has reached epidemic status in the United States, and opioids are the leading cause of drug-related deaths in Australia and worldwide. One factor that has not received attention in the addiction literature is intolerance of uncertainty (IU). IU is personality trait characterised by exaggerated negative beliefs about uncertainty and its consequences. This thesis investigates the links between IU and impulsive decision-making in the context of opioid-dependency. Four experimental studies examined impulsive decision-making from multiple perspectives, and assessed for the first time how impulsivity interacts with IU in opioid-dependent individuals. Across all four studies, opioid-dependent adults reported markedly higher levels of IU compared to a healthy control group. This consistent result provides strong evidence that IU is a personality trait that is related to drug addiction, whether it may be a pre-morbid risk factor, a result of chronic drug use or a co-occurring phenomenon based on shared neural correlates. A common thread between studies was that IU and impulsivity were meaningfully related in opioid-dependent individuals, but not in control groups. Specifically, IU was correlated with self-reported impulsive personality traits, poor attentional control, risk taking for monetary losses and risk-aversion for health improvements. No meaningful correlations were found between IU and impulsivity in control participants. These findings have important implications for addiction prevention and therapy. It is commonly accepted that pharmaceutical opioids are a driving factor for the upsurge in heroin abuse, and IU may be helpful to screen for at-risk individuals. Furthermore, addiction treatment could benefit by addressing IU in order to improve faulty beliefs about and reactions to uncertainty

Better together? Social distance affects joint probability discounting

Deciding together is common in our everyday life. However, the process of this joint decision-making plays out across different levels, for example language, intonation, or non-verbal behaviour. Here we focused on non-verbal interaction dynamics between two participants in probability discounting. We applied a gamified decision-making task in which participants performed a series of choices between a small but safe and a large but risky reward. In two experiments, we found that joint decision-making resulted in lower discounting and higher efficiency. In order to understand the underlying mechanisms in greater detail, we studied through which process this variation occurred and whether this process would be modulated by the social distance between both participants. Our findings suggested that socially close participants managed to reduce their discounting by interactive processes while socially distant participants were influenced by the social context itself. However, a higher level of efficiency was achieved through interactive processes for both groups. In summary, this study served as a fine-grained investigation of collaborative interaction processes and its significant impact on the outcome of choices with probabilistic consequences. [Abstract copyright: © 2022. The Author(s).

Individual differences & instance based decision making: putting “bounded rationality” to the test

Instance based risk taking behaviour allows relatively little time for information processing and may be responsible for unconsciously driven erratic behaviour in judgment and decision making. Previous theories that have explored the factors involved in risk taking behaviour include dispositional, decision-making, and neurocognitive functioning based theories. The present studies examine the contributions of age and gender, emotional intelligence, dispositional traits and affective states, involved in instance based decision-making. Participants were assessed using a binary choice task (study 1-A) and a double gamble risk taking task (study 1-B) which involved choices between financial gains with different pay-offs and risk levels, and an ignorance based task (study 2) which involved ignorance based judgments in the classic city size task. Participants were also administered the Trait Emotional Intelligence questionnaire, the Positive Affect Negative Affect Schedule, a self-report measure based on Gray’s behavioural activation and behavioural inhibition systems theory (BIS/BAS scale), and Dickman’s Impulsivity Inventory which distinguishes in functional and dysfunctional impulsivity. The purpose of these studies was to investigate whether individual differences in personality, emotional intelligence (EI) and affect predicted instance based risk taking behaviour. The participants were 64 (study 1-A), 68 (study 1-B), and 73 (study 2) university students; In study 1-A there were significant correlations between positive affect (PA), BAS Drive, BAS Fun-Seeking (FS), and total BAS and the number of risky choices in the binary choice task (r = .28, .25, .26, .31; p= .02, .04, .04, .01). In study 1-B there were significant correlations between PA, FS and total BAS and the number of risky choices in the binary choice double gamble task (r = .24, .25, .32; p = .04, .04, .01). There were no significant associations of trait EI or (functional or dysfunctional) impulsivity with the number of risky choices. These results indicate that individuals who are high in PA, BAS Drive and BAS Fun-Seeking tend to be riskier in decision making involving monetary incentives on an instance based decision making task. In study 2 there were significant correlations between functional impulsivity and negative affect and absolute scores of the Discrimination Index (r = .26, 33; p = .02, .01). These results indicate that individuals who are high in FI and NA tend to base their judgments and decision making on recognition heuristic use. The findings of the three studies indicate that dispositional variables and affective states may play a very important role in instance based risk taking behaviour. Also they indicate that affect is an important factor in instance based decision making, but the role of impulsivity is less clear. The findings in general imply a connection between personality and affective states and performance in professional risk laden domains such as the security, finances, and insurance sectors where individuals are called to take split second decisions

Time ambiguity during intertemporal decision-making is aversive, impacting choice and neural value coding

Contains fulltext : 196720.pdf (publisher's version ) (Open Access)We are often presented with choices that differ in their more immediate versus future consequences. Interestingly, in everyday-life, ambiguity about the exact timing of such consequences frequently occurs, yet it remains unknown whether and how time-ambiguity influences decisions and their underlying neural correlates. We developed a novel intertemporal fMRI choice task in which participants make choices between sooner-smaller (SS) versus later-larger (LL) monetary rewards with systematically varying levels of time-ambiguity. Across trials, delay information of the SS, the LL, or both rewards was either exact (e.g., in 5 weeks), of low ambiguity (4 week range: e.g., in 3-7 weeks), or of high ambiguity (8 week range: e.g., in 1-9 weeks). Choice behavior showed that the majority of participants preferred options with exact delays over those with ambiguous delays, indicating time-ambiguity aversion. Consistent with these results, the ventromedial prefrontal cortex showed decreased activation during ambiguous versus exact trials. In contrast, intraparietal sulcus activation increased during ambiguous versus exact trials. Furthermore, exploratory analyses suggest that more time-ambiguity averse participants show more insula and dorsolateral prefrontal cortex activation during subjective value (SV)-coding of ambiguous versus exact trials. Lastly, the best-fitting computational choice models indicate that ambiguity impacts the SV of options via time perception or via an additive ambiguity-related penalty term. Together, these results provide the first behavioral and neural signatures of time-ambiguity, pointing towards a unique profile that is distinct from impatience. Since time-ambiguity is ubiquitous in real-life, it likely contributes to shortsighted decisions above and beyond delay-discounting.9 p

Opioid and stimulant use among a sample of corrections-involved drug users : seeking an understanding of high-risk drug decisions within a system of constraint.

In the United States, high-risk drug use remains a significant social problem. Opioids and stimulants are two drug classes that have contributed to substantial recent increases in drug-related arrests, overdose, and mortality. Kentucky has been particularly devastated by high rates of opioid and stimulant use. Opioid and stimulant effects, while highly rewarding, can result in adverse consequences. Still, some people choose to use these drugs, and choose to continue using even after experiencing adverse consequences, such as incarceration. The aim of this study was to explore high-risk drug use among a sample of corrections-involved adults in Kentucky and to identify endogenous and exogenous factors with the potential to have influenced drug-related decision-making prior and subsequent to incarceration. Attention was paid to understanding concomitant opioid and stimulant use and heroin use. Survey data collected as part of an ongoing corrections-based substance use treatment program outcomes study were examined. The final sample (N=1,563) included adults released into Kentucky counties between 2012-2017. Non-parametric statistical tests and multinomial logistic regression were used to identify factors associated with opioid, stimulant, and concomitant use; binary logistic regression was used to identify factors associated with heroin use. Results indicate that opioid and stimulant use was endemic in this sample, though rates of use subsequent to incarceration were lower than pre-incarceration rates. During the 30-day period prior to incarceration, 29.0% of participants reported concomitant use, 28.5% reported opioid use, and 18.0% reported stimulant use. During the one-year post-release period, 11.9% of participants reported concomitant use, 12.5% reported opioid use, and 8.3% reported stimulant use. During this post-release period, 10.7% reported heroin use. Concomitant and heroin use positively correlated with many factors with the potential to adversely influence cognition and constrain choice. Similar relationships between many of these factors and outcomes involving other drug or no drug use were not observed. Behavioral economics, a molar view of choice and behavior, was used to conceptualize how factors in the lives of participants had the potential to influence and constrain decision-making in respect to high-risk drugs. Findings are discussed in light of how they may inform future research, policy, and practice

Learning and memory systems supporting decision making in the human brain

We successfully navigate the world by making decisions based on what we have learned. In the brain, two prominent learning systems have been identified and each is likely to guide decisions in different ways. Research on decision making has primarily focused on a reward learning system in the striatum. These studies have illuminated the how repeated choices and rewards build representations that guide choices and actions when encountering the same situation again. However, in a constantly changing environment, choices may not repeat themselves. Further, the environment may have more structure than simple reward learning can navigate. In these situations, decisions may be guided by a different learning system, namely a flexible learning system in the hippocampus which encodes episodes, or more broadly, relations between stimuli. However, investigations into the role of a reward learning system and a relational learning system in decision making have developed largely independently of each other. In the studies described below, I explore the function of these learning systems in value-guided decision making. Complementarily, I also explore how ongoing reward learning may modulate memory formation in the hippocampal system. In these studies, I demonstrate that reward learning and decision making is influenced by relational learning, and that these effects are predicted by hippocampal-striatal connectivity during learning. Separately, I establish that episodic memory is, in turn, influenced by ongoing reward learning. Successful memory is predicted by modulations of reward and memory regions including the striatum and hippocampus. Overall, these results provide novel insights into the learning systems encoding memories for future adaptive behavior

The Multi-Dimensional Contributions of Prefrontal Circuits to Emotion Regulation during Adulthood and Critical Stages of Development

The prefrontal cortex (PFC) plays a pivotal role in regulating our emotions. The importance of ventromedial regions in emotion regulation, including the ventral sector of the medial PFC, the medial sector of the orbital cortex and subgenual cingulate cortex, have been recognized for a long time. However, it is increasingly apparent that lateral and dorsal regions of the PFC, as well as neighbouring dorsal anterior cingulate cortex, also play a role. Defining the underlying psychological mechanisms by which these functionally distinct regions modulate emotions and the nature and extent of their interactions is a critical step towards better stratification of the symptoms of mood and anxiety disorders. It is also important to extend our understanding of these prefrontal circuits in development. Specifically, it is important to determine whether they exhibit differential sensitivity to perturbations by known risk factors such as stress and inflammation at distinct developmental epochs. This Special Issue brings together the most recent research in humans and other animals that addresses these important issues, and in doing so, highlights the value of the translational approach