Computational modeling reveals distinct effects of HIV and history of drug use on decision-making processes in women

Clustering of behavioral economic biases in decision-making and risk for cigarette smoking and other substance use in women and men

BACKGROUND

Low loss aversion (LA) and high delay discounting (DD) are behavioral-economic decision-making biases that independently predict cigarette smoking and other risky substance use. Here we examine (1) whether low-LA and high-DD co-occur, (2) does co-occurrence increase the odds of current smoking and other substance use compared to only low-LA, high-DD, or neither; and (3) potential gender differences in these associations.

METHOD

Data are from five studies with U.S. adults who currently smoked or never-smoked cigarettes recruited using online convenience sampling matching on gender and education. Participants completed identical sociodemographic, substance use (cigarette, other drugs, alcohol), and LA (hypothetical 50-50 gambles) and DD (monetary-choice questionnaire) measures. LA and DD scores were dichotomized as low and high using Receiver-Operating-Characteristic Curve logistic regression.

RESULTS

LA and DD each independently predicted substance use and with few exceptions were not influenced by gender. Low-LA compared to high-LA predicted two-fold greater odds of co-occurring high-DD (AOR = 2.120, 95%CI:1.749-2.571, p < .0001). Similarly, high-DD compared to low DD predicted two-fold greater odds of low-LA (AOR = 2.118, 95%CI:1.747-2.568, p < .0001). Among those with co-occurring low-LA and high-DD, odds of substance use were 5-10 times greater than those exhibiting neither, and 2-3 times greater than those exhibiting only low-LA or high-DD.

CONCLUSIONS

Low-LA and high-DD cluster in women and men such that exhibiting one of these decision-making biases doubles the odds of exhibiting the other. These results demonstrate reliable clustering of low-LA and high-DD and a striking increase in risk for substance use relative to having only one or neither decision-making bias.

Decision-making deficits in obsessive-compulsive disorder are associated with abnormality of recency and response consistency parameter in prospect valence learning model

Background

Patients with obsessive-compulsive disorder (OCD) have deficits in decision-making in the Iowa Gambling Task (IGT). However, no study has investigated the parameters of the prospect valence learning (PVL) model in the IGT for OCD.

Aims

This study aimed to investigate deficits in decision-making in OCD using the PVL model and identify whether the parameters of the PVL model were associated with obsessive-compulsive severity.

Methods

Forty-seven medication-free patients with OCD were compared with 47 healthy controls (HCs). Decision-making was measured using the total net and block net scores of the IGT. A PVL model with a decay-reinforcement learning rule (PVL-DecayRI) was used to investigate the parameters of the model. Correlation analysis was conducted between each parameter of the PVL-DecayRL and obsessive-compulsive symptoms.

Results

The total net score of patients with OCD was significantly lower than that of the HCs. The block net scores of the OCD group did not differ across the five blocks, whereas in the HCs, the fifth block net score was significantly higher than the block net scores of the first and second blocks. The values of the recency and response consistency parameters of the PVL-DecayRI in patients with OCD were significantly lower than those in HCs. The recency parameter positively correlated with the Y-BOCS obsessive score. Meanwhile, there was no correlation between consistency parameter values and symptom severity in OCD.

Conclusion

Our detailed analysis of the decision-making deficit in OCD suggests that the most recent outcome has a small influence on the expectancy of prospect valence, as indicated by the lower recency parameter, and is characterized by more impulsive choices, as indicated by the lower consistency parameter.

Effects of substance use on monetary delay discounting among people who use stimulants with and without HIV: An ecological momentary assessment study

Exploration of the real-time relationship between substance use and delay discounting may reveal potential mechanisms driving high-risk behaviors. We conducted an ecological momentary assessment (EMA) study to investigate the effects of substance use on delay discounting in a sample of people who use stimulants (HIV+: 30; HIV-: 34). Participants completed multiple EMAs throughout the day for 28 days. The EMAs collected data on delay discounting and substance use (time since last substance use and level of intoxication). Delay discounting was assessed using a brief Monetary Choice Questionnaire (MCQ). Analyses were conducted using linear mixed effects modeling. Most participants (99.1%) used cocaine as their primary stimulant. Among participants without HIV, MCQ score remained relatively stable during the first 2 hr after stimulant use, followed by an increase during 2-6 hr (p < .05), before decreasing again. For alcohol and marijuana, the MCQ score was stable during the first 4 hr after use, with a sharp increase at 4-6 hr (p < .05), before decreasing again. Among participants with HIV, there were no changes in MCQ score as a function of time since recent substance use. These findings provide evidence of a plausible connection between delay discounting and acute withdrawal that may have relevance for risky behaviors. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Component Processes of Decision Making in a Community Sample of Precariously Housed Persons: Associations With Learning and Memory, and Health-Risk Behaviors

The Iowa Gambling Task (IGT) is a widely used measure of decision making, but its value in signifying behaviors associated with adverse, "real-world" consequences has not been consistently demonstrated in persons who are precariously housed or homeless. Studies evaluating the ecological validity of the IGT have primarily relied on traditional IGT scores. However, computational modeling derives underlying component processes of the IGT, which capture specific facets of decision making that may be more closely related to engagement in behaviors associated with negative consequences. This study employed the Prospect Valence Learning (PVL) model to decompose IGT performance into component processes in 294 precariously housed community residents with substance use disorders. Results revealed a predominant focus on gains and a lack of sensitivity to losses in these vulnerable community residents. Hypothesized associations were not detected between component processes and self-reported health-risk behaviors. These findings provide insight into the processes underlying decision making in a vulnerable substance-using population and highlight the challenge of linking specific decision making processes to "real-world" behaviors.

Effects of cocaine and HIV on decision-making abilities

Our study aimed to understand the impact of cocaine dependence on high-risk decision-making abilities in individuals with the human immunodeficiency virus (HIV) and individuals with cocaine dependence. We recruited 99 participants (27 HIV/Cocaine, 20 HIV Only, 26 Cocaine Only, and 26 Healthy Controls). The Iowa Gambling Task (IGT) was applied to assess decision-making abilities. Independent and interactive effects of HIV status and cocaine dependence were examined using 2 × 2 factorial ANCOVA with premorbid IQ (WRAT-4: WR) as the covariate. We found cocaine dependence had a significant adverse effect on overall IGT performance (p = 0.015). We also found individuals who were HIV-positive tended to have less total money at the end of the game than individuals who were HIV-negative (p = 0.032), suggesting individuals living with HIV had less focus on long-term gains and more focus on short-term gains. Our findings highlight the significant impact of cocaine dependence on decision-making abilities and the difficulty individuals with HIV have in adequately weighing the cost and benefits of their decisions and making appropriate changes for the future.

Hypoactivation in the precuneus and posterior cingulate cortex during ambiguous decision making in individuals with HIV

People with human immunodeficiency virus (HIV) often have neurocognitive impairment. People with HIV make riskier decisions when the outcome probabilities are known, and have abnormal neural architecture underlying risky decision making. However, ambiguous decision making, when the outcome probabilities are unknown, is more common in daily life, but the neural architecture underlying ambiguous decision making in people with HIV is unknown. Eighteen people with HIV and 20 controls completed a decision making task while undergoing functional magnetic resonance imaging scanning. Participants chose between a certain reward and uncertain reward with a known (risky) or unknown (ambiguous) probability of winning. There were three levels of risk: high, medium, and low. Ambiguous > risky brain activity was compared between groups. Ambiguous > risky brain activity was correlated with emotional/psychiatric functioning in people with HIV. Both groups were similarly ambiguity-averse. People with HIV were more risk-averse than controls and chose the high-risk uncertain option less often. People with HIV had hypoactivity in the precuneus, posterior cingulate cortex (PCC), and fusiform gyrus during ambiguous > medium risk decision making. Ambiguous > medium risk brain activity was negatively correlated with emotional/psychiatric functioning in individuals with HIV. To make ambiguous decisions, people with HIV underrecruit key regions of the default mode network, which are thought to integrate internally and externally derived information to come to a decision. These regions and related cognitive processes may be candidates for interventions to improve decision-making outcomes in people with HIV.

HIV-1 Tat and Morphine Differentially Disrupt Pyramidal Cell Structure and Function and Spatial Learning in Hippocampal Area CA1: Continuous versus Interrupted Morphine Exposure

About half the people infected with human immunodeficiency virus (HIV) have neurocognitive deficits that often include memory impairment and hippocampal deficits, which can be exacerbated by opioid abuse. To explore the effects of opioids and HIV on hippocampal CA1 pyramidal neuron structure and function, we induced HIV-1 transactivator of transcription (Tat) expression in transgenic mice for 14 d and co-administered time-release morphine or vehicle subcutaneous implants during the final 5 d (days 9-14) to establish steady-state morphine levels. Morphine was withheld from some ex vivo slices during recordings to begin to assess the initial pharmacokinetic consequences of opioid withdrawal. Tat expression reduced hippocampal CA1 pyramidal neuronal excitability at lower stimulating currents. Pyramidal cell firing rates were unaffected by continuous morphine exposure. Behaviorally, exposure to Tat or high dosages of morphine impaired spatial memory Exposure to Tat and steady-state levels of morphine appeared to have largely independent effects on pyramidal neuron structure and function, a response that is distinct from other vulnerable brain regions such as the striatum. By contrast, acutely withholding morphine (from morphine-tolerant ex vivo slices) revealed unique and selective neuroadaptive shifts in CA1 pyramidal neuronal excitability and dendritic plasticity, including some interactions with Tat. Collectively, the results show that opioid-HIV interactions in hippocampal area CA1 are more nuanced than previously assumed, and appear to vary depending on the outcome assessed and on the pharmacokinetics of morphine exposure.

Testing the factor structure underlying behavior using joint cognitive models: Impulsivity in delay discounting and Cambridge gambling tasks

Neurocognitive tasks are frequently used to assess disordered decision making, and cognitive models of these tasks can quantify performance in terms related to decision makers' underlying cognitive processes. In many cases, multiple cognitive models purport to describe similar processes, but it is difficult to evaluate whether they measure the same latent traits or processes. In this article, we develop methods for modeling behavior across multiple tasks by connecting cognitive model parameters to common latent constructs. This approach can be used to assess whether 2 tasks measure the same dimensions of cognition, or actually improve the estimates of cognitive models when there are overlapping cognitive processes between 2 related tasks. The approach is then applied to connecting decision data on 2 behavioral tasks that evaluate clinically relevant deficits, the delay discounting task and Cambridge gambling task, to determine whether they both measure the same dimension of impulsivity. We find that the discounting rate parameters in the models of each task are not closely related, although substance users exhibit more impulsive behavior on both tasks. Instead, temporal discounting on the delay discounting task as quantified by the model is more closely related to externalizing psychopathology like aggression, while temporal discounting on the Cambridge gambling task is related more to response inhibition failures. The methods we develop thus provide a new way to connect behavior across tasks and grant new insights onto the different dimensions of impulsivity and their relation to substance use. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Recollecting Cross-Cultural Evidences: Are Decision Makers Really Foresighted in Iowa Gambling Task?

The Iowa Gambling Task (IGT) has become a remarkable experimental paradigm of dynamic emotion decision making. In recent years, research has emphasized the "prominent deck B (PDB) phenomenon" among normal (control group) participants, in which they favor "bad" deck B with its high-frequency gain structure-a finding that is incongruent with the original IGT hypothesis concerning foresightedness. Some studies have attributed such performance inconsistencies to cultural differences. In the present review, 86 studies featuring data on individual deck selections were drawn from an initial sample of 958 IGT-related studies published from 1994 to 2017 for further investigation. The PDB phenomenon was found in 67.44% of the studies (58 of 86), and most participants were recorded as having adopted the "gain-stay loss-randomize" strategy to cope with uncertainty. Notably, participants in our sample of studies originated from 16 areas across North America, South America, Europe, Oceania, and Asia, and the findings suggest that the PDB phenomenon may be cross-cultural.

Changes in Loss Sensitivity During Treatment in Concurrent Disorders Inpatients: A Computational Model Approach to Assessing Risky Decision-Making

BACKGROUND

Recent studies have employed computational modeling to characterize deficits in aspects of decision-making not otherwise detected using traditional behavioral task outcomes. While prospect utility-based modeling has shown to differentiate decision-making patterns between users of different drugs, its relevance in the context of treatment has yet to be examined. This study investigated model-based decision-making as it relates to treatment outcome in inpatients with co-occurring mental health and substance use disorders.

METHODS

50 patients (Mage = 38.5, SD = 11.4; 16F) completed the Cambridge Gambling Task (CGT) within 2 weeks of admission (baseline) and 6 months into treatment (follow-up), and 50 controls (Mage = 31.9, SD = 10.0; 25F) completed CGT under a single outpatient session. We evaluated 4 traditional CGT outputs and 5 decisional processes derived from the Cumulative Model. Psychiatric diagnoses and discharge data were retrieved from patient health records.

RESULTS

Groups were similar in age, sex, and premorbid IQ. Differences in years of education were included as covariates across all group comparisons. All patients had ≥1 mental health diagnosis, with 80% having >1 substance use disorder. On the CGT, patients showed greater Deliberation Time and Delay Aversion than controls. Estimated model parameters revealed higher Delayed Reward Discounting, and lower Probability Distortion and Loss Sensitivity in patients relative to controls. From baseline to follow-up, patients (n = 24) showed a decrease in model-derived Loss Sensitivity and Color Choice Bias. Lastly, poorer Quality of Decision-Making and Choice Consistency, and greater Color Choice Bias independently predicted higher likelihood of treatment dropout, while none were significant in relation to treatment length of stay.

CONCLUSION

This is the first study to assess a computational model of decision-making in the context of treatment for concurrent disorders. Patients were more impulsive and slower to deliberate choice than controls. While both traditional and computational outcomes predicted treatment adherence in patients, findings suggest computational methods are able to capture treatment-sensitive aspects of decision-making not accessible via traditional methods. Further research is needed to confirm findings as well as investigate the relationship between model-based decision-making and post-treatment outcomes.

Insensitivity to Losses: A Core Feature in Patients With Anorexia Nervosa?

BACKGROUND

Patients with anorexia nervosa (AN) demonstrate aberrations in choice behavior, including impairments in laboratory measures of decision making. Although a wealth of studies suggest that these aberrations arise from alterations in value processing, it remains unclear by which core component of value processing this is mediated.

METHODS

We fit trial-by-trial data of patients with AN (n = 60 first cohort, n = 216 second cohort) and healthy control participants (n = 55) performing the Iowa Gambling Task to a computational model based on prospect utility theory. We determined, per participant, the best-fit model parameters and compared these between the groups.

RESULTS

Analyses revealed a decreased estimate of model parameter λ in patients with AN, indicative of an attenuation of loss-aversive behavior in the Iowa Gambling Task. In comparison, measures of reward sensitivity, value-based learning, and exploration versus exploitation were unaltered in patients with AN. A measurement in a second independent cohort replicated the finding that loss aversion, typically observed in healthy individuals, is reduced in patients with AN.

CONCLUSIONS

We show that patients with AN, in contrast to healthy control participants, demonstrate reduced loss-aversive behavior. This finding provides important fundamental insights into the decision-making capacity of patients with AN, suggesting alterations in the mechanisms involved in value processing related to negative feedback.

On the importance of avoiding shortcuts in applying cognitive models to hierarchical data

Psychological experiments often yield data that are hierarchically structured. A number of popular shortcut strategies in cognitive modeling do not properly accommodate this structure and can result in biased conclusions. To gauge the severity of these biases, we conducted a simulation study for a two-group experiment. We first considered a modeling strategy that ignores the hierarchical data structure. In line with theoretical results, our simulations showed that Bayesian and frequentist methods that rely on this strategy are biased towards the null hypothesis. Secondly, we considered a modeling strategy that takes a two-step approach by first obtaining participant-level estimates from a hierarchical cognitive model and subsequently using these estimates in a follow-up statistical test. Methods that rely on this strategy are biased towards the alternative hypothesis. Only hierarchical models of the multilevel data lead to correct conclusions. Our results are particularly relevant for the use of hierarchical Bayesian parameter estimates in cognitive modeling.

Impulsivities and addictions: a multidimensional integrative framework informing assessment and interventions for substance use disorders

Impulse control is becoming a critical survival skill for the twenty-first century. Impulsivity is implicated in virtually all externalizing behaviours and disorders, and figures prominently in the aetiology and long-term sequelae of substance use disorders (SUDs). Despite its robust clinical and predictive validity, the study of impulsivity is complicated by its multidimensional nature, characterized by a variety of trait-like personality dimensions, as well as by more state-dependent neurocognitive dimensions, with variable convergence across measures. This review provides a hierarchical framework for linking self-report and neurocognitive measures to latent constructs of impulsivity and, in turn, to different psychopathology vulnerabilities, including substance-specific addictions and comorbidities. Impulsivity dimensions are presented as novel behavioural targets for prevention and intervention. Novel treatment approaches addressing domains of impulsivity are reviewed and recommendations for future directions in research and clinical interventions for SUDs are offered. This article is part of the theme issue 'Risk taking and impulsive behaviour: fundamental discoveries, theoretical perspectives and clinical implications'.

The Outcome-Representation Learning Model: A Novel Reinforcement Learning Model of the Iowa Gambling Task

The Iowa Gambling Task (IGT) is widely used to study decision-making within healthy and psychiatric populations. However, the complexity of the IGT makes it difficult to attribute variation in performance to specific cognitive processes. Several cognitive models have been proposed for the IGT in an effort to address this problem, but currently no single model shows optimal performance for both short- and long-term prediction accuracy and parameter recovery. Here, we propose the Outcome-Representation Learning (ORL) model, a novel model that provides the best compromise between competing models. We test the performance of the ORL model on 393 subjects' data collected across multiple research sites, and we show that the ORL reveals distinct patterns of decision-making in substance-using populations. Our work highlights the importance of using multiple model comparison metrics to make valid inference with cognitive models and sheds light on learning mechanisms that play a role in underweighting of rare events.

Using Bayesian regression to test hypotheses about relationships between parameters and covariates in cognitive models

An important tool in the advancement of cognitive science are quantitative models that represent different cognitive variables in terms of model parameters. To evaluate such models, their parameters are typically tested for relationships with behavioral and physiological variables that are thought to reflect specific cognitive processes. However, many models do not come equipped with the statistical framework needed to relate model parameters to covariates. Instead, researchers often revert to classifying participants into groups depending on their values on the covariates, and subsequently comparing the estimated model parameters between these groups. Here we develop a comprehensive solution to the covariate problem in the form of a Bayesian regression framework. Our framework can be easily added to existing cognitive models and allows researchers to quantify the evidential support for relationships between covariates and model parameters using Bayes factors. Moreover, we present a simulation study that demonstrates the superiority of the Bayesian regression framework to the conventional classification-based approach.

Frontostriatal Dysfunction During Decision Making in Attention-Deficit/Hyperactivity Disorder and Obsessive-Compulsive Disorder

Background

The aim of the current paper is to provide the first comparison of computational mechanisms and neurofunctional substrates in adolescents with attention-deficit/hyperactivity disorder (ADHD) and adolescents with obsessive-compulsive disorder (OCD) during decision making under ambiguity.

Methods

Sixteen boys with ADHD, 20 boys with OCD, and 20 matched control subjects (12–18 years of age) completed a functional magnetic resonance imaging version of the Iowa Gambling Task. Brain activation was compared between groups using three-way analysis of covariance. Hierarchical Bayesian analysis was used to compare computational modeling parameters between groups.

Results

Patient groups shared reduced choice consistency and relied less on reinforcement learning during decision making relative to control subjects, while adolescents with ADHD alone demonstrated increased reward sensitivity. During advantageous choices, both disorders shared underactivation in ventral striatum, while OCD patients showed disorder-specific underactivation in the ventromedial orbitofrontal cortex. During outcome evaluation, shared underactivation to losses in patients relative to control subjects was found in the medial prefrontal cortex and shared underactivation to wins was found in the left putamen/caudate. ADHD boys showed disorder-specific dysfunction in the right putamen/caudate, which was activated more to losses in patients with ADHD but more to wins in control subjects.

Conclusions

The findings suggest shared deficits in using learned reward expectancies to guide decision making, as well as shared dysfunction in medio-fronto-striato-limbic brain regions. However, findings of unique dysfunction in the ventromedial orbitofrontal cortex in OCD and in the right putamen in ADHD indicate additional, disorder-specific abnormalities and extend similar findings from inhibitory control tasks in the disorders to the domain of decision making under ambiguity.

Non-medical Cannabis Self-Exposure as a Dimensional Predictor of Opioid Dependence Diagnosis: A Propensity Score Matched Analysis

Background: The impact of increasing non-medical cannabis use on vulnerability to develop opioid use disorders has received considerable attention, with contrasting findings. A dimensional analysis of self-exposure to cannabis and other drugs, in individuals with and without opioid dependence (OD) diagnoses, may clarify this issue. Objective: To examine the age of onset of maximal self-exposure to cannabis, alcohol, cocaine, and heroin, in volunteers diagnosed with OD, using a rapidly administered instrument (the KMSK scales). To then determine whether maximal self-exposure to cannabis, alcohol, and cocaine is a dimensional predictor of odds of OD diagnoses. Methods: This outpatient observational study examined maximal self-exposure to these drugs, in volunteers diagnosed with DSM-IV OD or other drug diagnoses, and normal volunteers. In order to focus more directly on opioid dependence diagnosis as the outcome, volunteers who had cocaine dependence diagnoses were excluded. Male and female adults of diverse ethnicity were consecutively ascertained from the community, and from local drug treatment programs, in 2002-2013 (n = 574, of whom n = 94 had OD diagnoses). The age of onset of maximal self-exposure of these drugs was examined. After propensity score matching for age at ascertainment, gender, and ethnicity, a multiple logistic regression examined how increasing self-exposure to non-medical cannabis, alcohol and cocaine affected odds of OD diagnoses. Results: Volunteers with OD diagnoses had the onset of heaviest use of cannabis in the approximate transition between adolescence and adulthood (mean age = 18.9 years), and onset of heaviest use of alcohol soon thereafter (mean age = 20.1 years). Onset of heaviest use of heroin and cocaine was detected later in the lifespan (mean ages = 24.7 and 25.3 years, respectively). After propensity score matching for demographic variables, we found that the maximal self-exposure to cannabis and cocaine, but not to alcohol, was greater in volunteers with OD diagnoses, than in those without this diagnosis. Also, a multiple logistic regression detected that increasing self-exposure to cannabis and cocaine, but not alcohol, was a positive predictor of OD diagnosis. Conclusions/Importance: Increasing self-exposure to non-medical cannabis, as measured with a rapid dimensional instrument, was a predictor of greater odds of opioid dependence diagnosis, in propensity score-matched samples.

Decision-Making Deficits Are Associated With Learning Impairments in Female College Students at High Risk for Anorexia Nervosa: Iowa Gambling Task and Prospect Valence Learning Model

This study investigated deficits in decision-making ability in female college students at high risk for anorexia nervosa (AN) using the Iowa Gambling Task (IGT) and the prospect valence learning (PVL) model. Based on scores on the Korean version of the Eating Attitude Test-26 (KEAT-26), participants were assigned to either the high risk for AN group (n = 42) or the control group (n = 43). The high risk for AN group exhibited significantly lower total net scores and block net scores on the third, fourth, and fifth blocks of the IGT than the control group did. The high risk for AN group selected cards significantly more often from the disadvantageous A and B decks and less often from the advantageous D deck than the control group did. In addition, the block net scores of the high risk for AN group did not differ across the five blocks, whereas those of the control group increased as the trials progressed. There was a significant negative correlation between IGT total net score and total score on the KEAT-26. The high risk for AN group had significantly lower values than the control group on the learning and response consistency parameters of the PVL model. These results indicate that female college students at high risk for AN have deficits in decision-making ability, and that these deficits are related to difficulties in remembering experience obtained from earlier trials and applying it to later trials. These difficulties further lead them to make decisions randomly.

Reduced loss aversion in pathological gambling and alcohol dependence is associated with differential alterations in amygdala and prefrontal functioning

Diagnostic criteria for pathological gambling and alcohol dependence (AD) include repeated addictive behavior despite severe negative consequences. However, the concept of loss aversion (LA) as a facet of value-based decision making has not yet been used to directly compare these disorders. We hypothesized reduced LA in pathological gamblers (PG) and AD patients, correlation of LA with disorder severity, and reduced loss-related modulation of brain activity. 19 PG subjects, 15 AD patients and 17 healthy controls (HC) engaged in a LA task in a functional magnetic resonance imaging setting. Imaging analyses focused on neural gain and loss sensitivity in the meso-cortico-limbic network of the brain. Both PG and AD subjects showed reduced LA. AD subjects showed altered loss-related modulation of activity in lateral prefrontal regions. PG subjects showed indication of altered amygdala-prefrontal functional connectivity. Although we observed reduced LA in both a behavioral addiction and a substance-related disorder our neural findings might challenge the notion of complete neuro-behavioral congruence of substance-use disorders and behavioral addictions.

A pilot study of loss aversion for drug and non-drug commodities in cocaine users

BACKGROUND

Numerous studies in behavioral economics have demonstrated that individuals are more sensitive to the prospect of a loss than a gain (i.e., loss aversion). Although loss aversion has been well described in "healthy" populations, little research exists in individuals with substance use disorders. This gap is notable considering the prominent role that choice and decision-making play in drug use. The purpose of this pilot study was to evaluate loss aversion in active cocaine users.

METHODS

Current cocaine users (N=38; 42% female) participated in this within-subjects laboratory pilot study. Subjects completed a battery of tasks designed to assess loss aversion for drug and non-drug commodities under varying risk conditions. Standardized loss aversion coefficients (λ) were compared to theoretically and empirically relevant normative values (i.e., λ=2).

RESULTS

Compared to normative loss aversion coefficient values, a precise and consistent decrease in loss aversion was observed in cocaine users (sample λ≈1). These values were observed across drug and non-drug commodities as well as under certain and risky conditions.

CONCLUSIONS

These data represent the first systematic study of loss aversion in cocaine-using populations and provide evidence for equal sensitivity to losses and gains or loss equivalence. Futures studies should evaluate the specificity of these effects to a history of cocaine use as well as the impact of manipulations of loss aversion on drug use to determine how this phenomenon may contribute to intervention development efforts.

Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the hBayesDM Package

Reinforcement learning and decision-making (RLDM) provide a quantitative framework and computational theories with which we can disentangle psychiatric conditions into the basic dimensions of neurocognitive functioning. RLDM offer a novel approach to assessing and potentially diagnosing psychiatric patients, and there is growing enthusiasm for both RLDM and computational psychiatry among clinical researchers. Such a framework can also provide insights into the brain substrates of particular RLDM processes, as exemplified by model-based analysis of data from functional magnetic resonance imaging (fMRI) or electroencephalography (EEG). However, researchers often find the approach too technical and have difficulty adopting it for their research. Thus, a critical need remains to develop a user-friendly tool for the wide dissemination of computational psychiatric methods. We introduce an R package called hBayesDM (hierarchical Bayesian modeling of Decision-Making tasks), which offers computational modeling of an array of RLDM tasks and social exchange games. The hBayesDM package offers state-of-the-art hierarchical Bayesian modeling, in which both individual and group parameters (i.e., posterior distributions) are estimated simultaneously in a mutually constraining fashion. At the same time, the package is extremely user-friendly: users can perform computational modeling, output visualization, and Bayesian model comparisons, each with a single line of coding. Users can also extract the trial-by-trial latent variables (e.g., prediction errors) required for model-based fMRI/EEG. With the hBayesDM package, we anticipate that anyone with minimal knowledge of programming can take advantage of cutting-edge computational-modeling approaches to investigate the underlying processes of and interactions between multiple decision-making (e.g., goal-directed, habitual, and Pavlovian) systems. In this way, we expect that the hBayesDM package will contribute to the dissemination of advanced modeling approaches and enable a wide range of researchers to easily perform computational psychiatric research within different populations.

Dorsolateral prefrontal cortex contributes to the impaired behavioral adaptation in alcohol dependence

Substance-dependent individuals often lack the ability to adjust decisions flexibly in response to the changes in reward contingencies. Prediction errors (PEs) are thought to mediate flexible decision-making by updating the reward values associated with available actions. In this study, we explored whether the neurobiological correlates of PEs are altered in alcohol dependence. Behavioral, and functional magnetic resonance imaging (fMRI) data were simultaneously acquired from 34 abstinent alcohol-dependent patients (ADP) and 26 healthy controls (HC) during a probabilistic reward-guided decision-making task with dynamically changing reinforcement contingencies. A hierarchical Bayesian inference method was used to fit and compare learning models with different assumptions about the amount of task-related information subjects may have inferred during the experiment. Here, we observed that the best-fitting model was a modified Rescorla-Wagner type model, the “double-update” model, which assumes that subjects infer the knowledge that reward contingencies are anti-correlated, and integrate both actual and hypothetical outcomes into their decisions. Moreover, comparison of the best-fitting model's parameters showed that ADP were less sensitive to punishments compared to HC. Hence, decisions of ADP after punishments were loosely coupled with the expected reward values assigned to them. A correlation analysis between the model-generated PEs and the fMRI data revealed a reduced association between these PEs and the BOLD activity in the dorsolateral prefrontal cortex (DLPFC) of ADP. A hemispheric asymmetry was observed in the DLPFC when positive and negative PE signals were analyzed separately. The right DLPFC activity in ADP showed a reduced correlation with positive PEs. On the other hand, ADP, particularly the patients with high dependence severity, recruited the left DLPFC to a lesser extent than HC for processing negative PE signals. These results suggest that the DLPFC, which has been linked to adaptive control of action selection, may play an important role in cognitive inflexibility observed in alcohol dependence when reinforcement contingencies change. Particularly, the left DLPFC may contribute to this impaired behavioral adaptation, possibly by impeding the extinction of the actions that no longer lead to a reward.

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Alcohol-dependent patients (ADP) had difficulty adapting to the reversals.

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The impaired adaptation was associated with a decrease in punishment sensitivity.

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The dorsolateral prefrontal cortex (DLPFC) of ADP failed to track prediction errors.

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A reduced tracking of the negative prediction error was present in the left DLPFC.

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The clinical severity of dependence was correlated with abnormal DLPFC activity.

Sex and HIV serostatus differences in decision making under risk among substance-dependent individuals

HIV+ individuals with and without substance use disorders make significantly poorer decisions when information about the probability and magnitude of wins and losses is not available. We administered the Game of Dice Task, a measure of decision making under risk that provides this information explicitly, to 92 HIV+ and 134 HIV- substance-dependent men and women. HIV+ participants made significantly poorer decisions than HIV- participants, but this deficit appeared more prominent among HIV+ women. These data indicate that decision making under risk is impaired among HIV+ substance-dependent individuals (SDIs). Potential factors for the HIV+ women's relatively greater impairment are discussed.

Compensatory activation in fronto-parietal cortices among HIV-infected persons during a monetary decision-making task

HIV infection can cause direct and indirect damage to the brain and is consistently associated with neurocognitive disorders, including impairments in decision-making capacities. The tendency to devalue rewards that are delayed (temporal discounting) is relevant to a range of health risk behaviors. Making choices about delayed rewards engages the executive control network of the brain, which has been found to be affected by HIV. In this case-control study of 18 HIV-positive and 17 HIV-negative adults, we examined the effects of HIV on brain activation during a temporal discounting task. Functional MRI (fMRI) data were collected while participants made choices between smaller, sooner rewards and larger, delayed rewards. Choices were individualized based on participants' unique discount functions, so each participant experienced hard (similarly valued), easy (disparately valued), and control choices. fMRI data were analyzed using a mixed-effects model to identify group-related differences associated with choice difficulty. While there was no difference between groups in behavioral performance, the HIV-positive group demonstrated significantly larger increases in activation within left parietal regions and bilateral prefrontal regions during easy trials and within the right prefrontal cortex and anterior cingulate during hard trials. Increasing activation within the prefrontal regions was associated with lower nadir CD4 cell count and risk-taking propensity. These results support the hypothesis that HIV infection can alter brain functioning in regions that support decision making, providing further evidence for HIV-associated compensatory activation within fronto-parietal cortices. A history of immunosuppression may contribute to these brain changes. Hum Brain Mapp 37:2455-2467, 2016. © 2016 Wiley Periodicals, Inc.

Neurocognitive and psychiatric dimensions of hot, but not cool, impulsivity predict HIV sexual risk behaviors among drug users in protracted abstinence

BACKGROUND

Impulsivity is an important risk factor for HIV risky drug and sexual behaviors. Research identifies hot (i.e. affectively-mediated, reward-based) and cool (motoric, attentional, independent of context) neurocognitive and psychiatric dimensions of impulsivity, though the impact of specific drugs of abuse on these varieties of impulsivity remains an open question.

OBJECTIVES

The present study examined the associations of neurocognitive and psychiatric varieties of hot and cool impulsivity with measures of lifetime and recent sexual risk behaviors among users of different classes of drugs.

METHODS

The study sample was comprised of drug users in protracted (> 1 year) abstinence: heroin mono-dependent (n = 61), amphetamine mono-dependent (n = 44), and polysubstance dependent (n = 73). Hot impulsivity was operationalized via neurocognitive tasks of reward-based decision-making and symptoms of psychopathy. Cool impulsivity was operationalized via neurocognitive tasks of response inhibition and symptoms of attention deficit/hyperactivity disorder (ADHD).

RESULTS

Hot impulsivity was associated with sexual risk behaviors among heroin and amphetamine users in protracted abstinence, whereas cool impulsivity was not associated with sexual risk behaviors among any drug-using group. Neurocognitive hot impulsivity was associated with recent (past 30-day) sexual risk behaviors, whereas psychopathy was associated with sexual risk behaviors during more remote time-periods (past 6 month and lifetime) and mediated the association between heroin dependence and past 6-month sexual risk behaviors.

CONCLUSION

Assessments and interventions aimed at reducing sexual risk behaviors among drug users should focus on hot neurocognitive and psychiatric dimensions of impulsivity, such as decision-making and psychopathy. Cool dimensions of impulsivity such as response inhibition and ADHD were not related to sexual risk behaviors among drug users in protracted abstinence.

Decision-making deficits in patients with chronic schizophrenia: Iowa Gambling Task and Prospect Valence Learning model

PURPOSE

Decision-making is the process of forming preferences for possible options, selecting and executing actions, and evaluating the outcome. This study used the Iowa Gambling Task (IGT) and the Prospect Valence Learning (PVL) model to investigate deficits in risk-reward related decision-making in patients with chronic schizophrenia, and to identify decision-making processes that contribute to poor IGT performance in these patients.

MATERIALS AND METHODS

Thirty-nine patients with schizophrenia and 31 healthy controls participated. Decision-making was measured by total net score, block net scores, and the total number of cards selected from each deck of the IGT. PVL parameters were estimated with the Markov chain Monte Carlo sampling scheme in OpenBugs and BRugs, its interface to R, and the estimated parameters were analyzed with the Mann-Whitney U-test.

RESULTS

The schizophrenia group received significantly lower total net scores compared to the control group. In terms of block net scores, an interaction effect of group × block was observed. The block net scores of the schizophrenia group did not differ across the five blocks, whereas those of the control group increased as the blocks progressed. The schizophrenia group obtained significantly lower block net scores in the fourth and fifth blocks of the IGT and selected cards from deck D (advantageous) less frequently than the control group. Additionally, the schizophrenia group had significantly lower values on the utility-shape, loss-aversion, recency, and consistency parameters of the PVL model.

CONCLUSION

These results indicate that patients with schizophrenia experience deficits in decision-making, possibly due to failure in learning the expected value of each deck, and incorporating outcome experiences of previous trials into expectancies about options in the present trial.

Cocaine choice procedures in animals, humans, and treatment-seekers: Can we bridge the divide?

Individuals with cocaine use disorder chronically self-administer cocaine to the detriment of other rewarding activities, a phenomenon best modeled in laboratory drug-choice procedures. These procedures can evaluate the reinforcing effects of drugs versus comparably valuable alternatives under multiple behavioral arrangements and schedules of reinforcement. However, assessing drug-choice in treatment-seeking or abstaining humans poses unique challenges: for ethical reasons, these populations typically cannot receive active drugs during research studies. Researchers have thus needed to rely on alternative approaches that approximate drug-choice behavior or assess more general forms of decision-making, but whether these alternatives have relevance to real-world drug-taking that can inform clinical trials is not well-understood. In this mini-review, we (A) summarize several important modulatory variables that influence cocaine choice in nonhuman animals and non-treatment seeking humans; (B) discuss some of the ethical considerations that could arise if treatment-seekers are enrolled in drug-choice studies; (C) consider the efficacy of alternative procedures, including non-drug-related decision-making and 'simulated' drug-choice (a choice is made, but no drug is administered) to approximate drug choice; and (D) suggest opportunities for new translational work to bridge the current divide between preclinical and clinical research.

Probabilistic reward- and punishment-based learning in opioid addiction: Experimental and computational data

Addiction is the continuation of a habit in spite of negative consequences. A vast literature gives evidence that this poor decision-making behavior in individuals addicted to drugs also generalizes to laboratory decision making tasks, suggesting that the impairment in decision-making is not limited to decisions about taking drugs. In the current experiment, opioid-addicted individuals and matched controls with no history of illicit drug use were administered a probabilistic classification task that embeds both reward-based and punishment-based learning trials, and a computational model of decision making was applied to understand the mechanisms describing individuals' performance on the task. Although behavioral results showed that opioid-addicted individuals performed as well as controls on both reward- and punishment-based learning, the modeling results suggested subtle differences in how decisions were made between the two groups. Specifically, the opioid-addicted group showed decreased tendency to repeat prior responses, meaning that they were more likely to "chase reward" when expectancies were violated, whereas controls were more likely to stick with a previously-successful response rule, despite occasional expectancy violations. This tendency to chase short-term reward, potentially at the expense of developing rules that maximize reward over the long term, may be a contributing factor to opioid addiction. Further work is indicated to better understand whether this tendency arises as a result of brain changes in the wake of continued opioid use/abuse, or might be a pre-existing factor that may contribute to risk for addiction.

The role of decision-making in cannabis-related problems among young adults

BACKGROUND

Deficits in decision-making and episodic memory are often reported among heavy cannabis users, yet little is known on how they influence negative consequences from cannabis use. Individual differences in decision-making may explain, in part, why some individuals experience significant problems from their cannabis use whereas others do not. We hypothesized that poor decision-making would moderate relationships between amount of cannabis use and problems from cannabis use whereas episodic memory performance would not.

METHOD

Young adult cannabis users (n=52) with cannabis as their drug of choice and with minimal comorbidities completed semi-structured interviews, self-report questionnaires, and measures of neurocognitive functioning, with decision-making accessed via the Iowa Gambling Task (IGT), episodic memory via the Hopkins Verbal Learning Test - Revised (HVLT) and problems from cannabis use with the Marijuana Problems Scale.

RESULTS

Strong relationships were observed between amount of cannabis use (lifetime, 12-month, and 30-day) and problems reported from use, but only among participants with low (impaired) decision-making (R(2)=.39 to .51; p<.01). No significant relationships were observed among those with better (low average to high average) decision-making performance (p>.05). In contrast, episodic memory performance was not a significant moderator of the relationship between amount of cannabis use and cannabis problems (p>.05).

CONCLUSIONS

Cannabis users with poor decision-making may be at greater risk for experiencing significant negative consequences from their cannabis use. Our results lend further support to emerging evidence of decision-making as a risk factor for addiction and extend these findings to cannabis users.

Decision making under explicit risk is impaired in individuals with human immunodeficiency virus (HIV)

INTRODUCTION

Human immunodeficiency virus (HIV) can affect the frontal-striatal brain regions, which are known to subserve decision-making functions. Previous studies have reported impaired decision making among HIV+ individuals using the Iowa Gambling Task, a task that assesses decision making under ambiguity. Previous study populations often had significant comorbidities such as past or present substance use disorders and/or hepatitis C virus coinfection, complicating conclusions about the unique contributions of HIV-infection to decision making. Decision making under explicit risk has very rarely been examined in HIV+ individuals and was tested here using the Game of Dice Task (GDT).

METHOD

We examined decision making under explicit risk in the GDT in 20 HIV+ individuals without substance use disorder or HCV coinfection, including a demographically matched healthy control group (n = 20). Groups were characterized on a standard neuropsychological test battery. For the HIV+ group, several disease-related parameters (viral load, current and nadir CD4 T-cell count) were included. Analyses focused on the GDT and spanned between-group (t-tests; analysis of covariance, ANCOVA) as well as within-group comparisons (Pearson/Spearman correlations).

RESULTS

HIV+ individuals were impaired in the GDT, compared to healthy controls (p = .02). Their decision-making impairments were characterized by less advantageous choices and more random choice strategies, especially towards the end of the task. Deficits in the GDT in the HIV+ group were related to executive dysfunctions, slowed processing/motor speed, and current immune system status (CD4+ T-cell levels, ps < .05).

CONCLUSIONS

Decision making under explicit risk in the GDT can occur in HIV-infected individuals without comorbidities. The correlational patterns may point to underlying fronto-subcortical dysfunctions in HIV+ individuals. The GDT provides a useful measure to assess risky decision making in this population and should be tested in larger studies.

Risk behavior in opioid-dependent individuals after the administration of a therapeutic dose of methadone

BACKGROUND AND OBJECTIVES

Evidence suggests that methadone may play a protective role in the faulty decision-making in heroin-addicted individuals. This may reduce craving for opioids and the risky decisions associated with active opioid use.

METHODS

We tested the effect of a daily therapeutic dose of methadone on faulty decision-making in eighty (n = 80) individuals with a history of opioid addiction. We used the Iowa Gambling Task (IGT) and compared the score and response time before and after the daily methadone dosing.

RESULTS

The mean net IGT score before methadone dose was 10 (±22) and 22 (±23) after methadone dose (t = 4.23, p = .00006). These results reflect statistically significant improvement in faulty decisions after the administration of the daily methadone dose. The mean response time for the reward cards before methadone dose were 1,856 ms (±871) and 1,465 ms (±851) after methadone dose (t = 2.55, p = .012). The mean response time for the punishment cards before methadone dose were 1,688 ms (±911) and 1,399 ms (±827) after methadone dose (t = 1.86, p = .065). These results reflect statistically significant improvement in response time to a rewarding healthy decisions after the administration of the daily methadone dose.

CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE

This is the first study to report the effect of a therapeutic dose of methadone on improving faulty decisions for individuals with a long history of opioids addiction. This study demonstrated that the time to making a healthy decision was significantly shorter as a result of administration of methadone.

Decision-making in stimulant and opiate addicts in protracted abstinence: evidence from computational modeling with pure users

Substance dependent individuals (SDI) often exhibit decision-making deficits; however, it remains unclear whether the nature of the underlying decision-making processes is the same in users of different classes of drugs and whether these deficits persist after discontinuation of drug use. We used computational modeling to address these questions in a unique sample of relatively “pure” amphetamine-dependent (N = 38) and heroin-dependent individuals (N = 43) who were currently in protracted abstinence, and in 48 healthy controls (HC). A Bayesian model comparison technique, a simulation method, and parameter recovery tests were used to compare three cognitive models: (1) Prospect Valence Learning with decay reinforcement learning rule (PVL-DecayRI), (2) PVL with delta learning rule (PVL-Delta), and (3) Value-Plus-Perseverance (VPP) model based on Win-Stay-Lose-Switch (WSLS) strategy. The model comparison results indicated that the VPP model, a hybrid model of reinforcement learning (RL) and a heuristic strategy of perseverance had the best post-hoc model fit, but the two PVL models showed better simulation and parameter recovery performance. Computational modeling results suggested that overall all three groups relied more on RL than on a WSLS strategy. Heroin users displayed reduced loss aversion relative to HC across all three models, which suggests that their decision-making deficits are longstanding (or pre-existing) and may be driven by reduced sensitivity to loss. In contrast, amphetamine users showed comparable cognitive functions to HC with the VPP model, whereas the second best-fitting model with relatively good simulation performance (PVL-DecayRI) revealed increased reward sensitivity relative to HC. These results suggest that some decision-making deficits persist in protracted abstinence and may be mediated by different mechanisms in opiate and stimulant users.

Differential impairments underlying decision making in anorexia nervosa and bulimia nervosa: a cognitive modeling analysis

OBJECTIVE

This study examined the underlying processes of decision-making impairments in individuals with anorexia nervosa (AN) and bulimia nervosa (BN). We deconstructed their performance on the widely used decision task, the Iowa Gambling Task (IGT) into cognitive, motivational, and response processes using cognitive modeling analysis. We hypothesized that IGT performance would be characterized by impaired memory functions and heightened punishment sensitivity in AN, and by elevated sensitivity to reward as opposed to punishment in BN.

METHOD

We analyzed trial-by-trial data of IGT obtained from 224 individuals: 94 individuals with AN, 63 with BN, and 67 healthy comparison individuals (HC). The prospect valence learning model was used to assess cognitive, motivational, and response processes underlying IGT performance.

RESULTS

Individuals with AN showed marginally impaired IGT performance compared to HC. Their performance was characterized by impairments in memory functions. Individuals with BN showed significantly impaired IGT performance compared to HC. They showed greater relative sensitivity to gains as opposed to losses than HC. Memory functions in AN were positively correlated with body mass index.

DISCUSSION

This study identified differential impairments underlying IGT performance in AN and BN. Findings suggest that impaired decision making in AN might involve impaired memory functions. Impaired decision making in BN might involve altered reward and punishment sensitivity.