Use of the Exponential and Exponentiated Demand Equations to Assess the Behavioral Economics of Negative Reinforcement

A mild impairment in reversal learning in a bowl-digging substrate deterministic task but not other cognitive tests in the Dlg2+/- rat model of genetic risk for psychiatric disorder

Variations in the Dlg2 gene have been linked to increased risk for psychiatric disorders, including schizophrenia, autism spectrum disorders, intellectual disability, bipolar disorder, attention deficit hyperactivity disorder, and pubertal disorders. Recent studies have reported disrupted brain circuit function and behaviour in models of Dlg2 knockout and haploinsufficiency. Specifically, deficits in hippocampal synaptic plasticity were found in heterozygous Dlg2+/- rats suggesting impacts on hippocampal dependent learning and cognitive flexibility. Here, we tested these predicted effects with a behavioural characterisation of the heterozygous Dlg2+/- rat model. Dlg2+/- rats exhibited a specific, mild impairment in reversal learning in a substrate deterministic bowl-digging reversal learning task. The performance of Dlg2+/- rats in other bowl digging task, visual discrimination and reversal, novel object preference, novel location preference, spontaneous alternation, modified progressive ratio, and novelty-suppressed feeding test were not impaired. These findings suggest that despite altered brain circuit function, behaviour across different domains is relatively intact in Dlg2+/- rats, with the deficits being specific to only one test of cognitive flexibility. The specific behavioural phenotype seen in this Dlg2+/- model may capture features of the clinical presentation associated with variation in the Dlg2 gene.

Behavioral economic relationship between cannabis flower and concentrates: Evidence from simulated purchase tasks

Cannabis users use different forms of cannabis, which are associated with distinct public health concerns. Policies that aim to regulate one specific form may have unintended impacts on other forms. This study examined the behavioral economic relationship between flower and concentrates, the two most common forms of cannabis. We surveyed 605 adult cannabis users (21+) who lived in one of the U.S. states that had legalized recreational cannabis by the time of interview in 2019. The participants completed simulated purchase tasks, which asked how much cannabis flower and concentrates they would purchase in the next 30 days at escalating prices. We estimated (a) demand indices and own-price elasticities using nonlinear exponential demand models and (b) group- and individual-level cross-price elasticities using log-linear demand models. The estimated rate of change in demand elasticity (α) was 0.00066 for cannabis flower (SE = 0.00002, p < .001) and 0.00058 for cannabis concentrate (SE = 0.00002, p < .001). Group-level cross-price elasticity estimate (slope = -0.075, SE = 0.0135, p < .001) indicated that cannabis flower and concentrates were weak complements. Individual-level cross-price elasticity estimates showed that flower and concentrates were treated as independent by 76.2% of the users, as complements by 19.0% of the users, and as substitutes by 4.8% of the users. The findings suggested that cannabis flower and concentrates were overall weak complements and for most adult cannabis users were treated as independent of each other. Price and tax policies regulating either cannabis form may have minimal impacts on the other form. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Applying Mixed-Effects Modeling to Behavioral Economic Demand: An Introduction

Behavioral economic demand methodology is increasingly being used in various fields such as substance use and consumer behavior analysis. Traditional analytical techniques to fitting demand data have proven useful yet some of these approaches require preprocessing of data, ignore dependence in the data, and present statistical limitations. We term these approaches "fit to group" and "two stage" with the former interested in group or population level estimates and the latter interested in individual subject estimates. As an extension to these regression techniques, mixed-effect (or multilevel) modeling can serve as an improvement over these traditional methods. Notable benefits include providing simultaneous group (i.e., population) level estimates (with more accurate standard errors) and individual level predictions while accommodating the inclusion of "nonsystematic" response sets and covariates. These models can also accommodate complex experimental designs including repeated measures. The goal of this article is to introduce and provide a high-level overview of mixed-effects modeling techniques applied to behavioral economic demand data. We compare and contrast results from traditional techniques to that of the mixed-effects models across two datasets differing in species and experimental design. We discuss the relative benefits and drawbacks of these approaches and provide access to statistical code and data to support the analytical replicability of the comparisons.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40614-021-00299-7.

Cues conditioned to withdrawal and negative reinforcement: Neglected but key motivational elements driving opioid addiction

Opioid use disorder (OUD) is a debilitating disorder that affects millions of people. Neutral cues can acquire motivational properties when paired with the positive emotional effects of drug intoxication to stimulate relapse. However, much less research has been devoted to cues that become conditioned to the aversive effects of opioid withdrawal. We argue that environmental stimuli promote motivation for opioids when cues are paired with withdrawal (conditioned withdrawal) and generate opioid consumption to terminate conditioned withdrawal (conditioned negative reinforcement). We review evidence that cues associated with pain drive opioid consumption, as patients with chronic pain may misuse opioids to escape physical and emotional pain. We highlight sex differences in withdrawal-induced stress reactivity and withdrawal cue processing and discuss neurocircuitry that may underlie withdrawal cue processing in dependent individuals. These studies highlight the importance of studying cues associated with withdrawal in dependent individuals and point to areas for exploration in OUD research.

A reinforcement-learning model of active avoidance behavior: Differences between Sprague Dawley and Wistar-Kyoto rats

Avoidance behavior is a typically adaptive response performed by an organism to avert harmful situations. Individuals differ remarkably in their tendency to acquire and perform new avoidance behaviors, as seen in anxiety disorders where avoidance becomes pervasive and inappropriate. In rodent models of avoidance, the inbred Wistar-Kyoto (WKY) rat demonstrates increased learning and expression of avoidance compared to the outbred Sprague Dawley (SD) rat. However, underlying mechanisms that contribute to these differences are unclear. Computational modeling techniques can help identify factors that may not be easily decipherable from behavioral data alone. Here, we utilize a reinforcement learning (RL) model approach to better understand strain differences in avoidance behavior. An actor-critic model, with separate learning rates for action selection (in the actor) and state evaluation (in the critic), was applied to individual data of avoidance acquisition from a large cohort of WKY and SD rats. Latent parameters were extracted, such as learning rate and subjective reinforcement value of foot shock, that were then compared across groups. The RL model was able to accurately represent WKY and SD avoidance behavior, demonstrating that the model could simulate individual performance. The model determined that the perceived negative value of foot shock was significantly higher in WKY than SD rats, whereas learning rate in the actor was lower in WKY than SD rats. These findings demonstrate the utility of computational modeling in identifying underlying processes that could promote strain differences in behavioral performance.

The role of orexin-1 receptor signaling in demand for the opioid fentanyl

The orexin system is a potential treatment target for drug addiction. Orexin-1 receptor (OxR1) antagonism reduces demand for cocaine and remifentanil, indicating that orexin-based therapies may reduce demand for many classes of abused drugs. However, pharmacokinetics vary greatly among opioids and it is unclear if OxR1 antagonism would reduce demand for all opioids, particularly ones with high abuse liability. Here, we established a behavioral economics (BE) procedure to assess the effects of OxR1 antagonism on demand for the highly abused opioid fentanyl. We also investigated the utility of our procedure to predict OxR1 antagonism efficacy and relapse propensity. Demand parameters α (demand elasticity or price sensitivity of consumption, an inverse measure of drug motivation) and Q_o (drug consumption at null cost) were assessed. The OxR1 antagonist SB-334867 (SB) decreased motivation (increased α) for fentanyl without affecting Q_o. Baseline α values predicted SB efficacy, such that SB was most effective at reducing motivation (increasing α) in highly motivated rats. Baseline α values predicted the amount of cued reinstatement of fentanyl seeking; this reinstatement behavior was attenuated by SB administration. These results highlight the promise of the orexin system as a treatment target for opioid addiction and emphasize the usefulness of BE procedures in the study of opioid abuse.

Inhibited Personality Temperaments Translated Through Enhanced Avoidance and Associative Learning Increase Vulnerability for PTSD

Although many individuals who experience a trauma go on to develop post-traumatic stress disorder (PTSD), the rate of PTSD following trauma is only about 15-24%. There must be some pre-existing conditions that impart increased vulnerability to some individuals and not others. Diathesis models of PTSD theorize that pre-existing vulnerabilities interact with traumatic experiences to produce psychopathology. Recent work has indicated that personality factors such as behavioral inhibition (BI), harm avoidance (HA), and distressed (Type D) personality are vulnerability factors for the development of PTSD and anxiety disorders. These personality temperaments produce enhanced acquisition or maintenance of associations, especially avoidance, which is a criterion symptom of PTSD. In this review, we highlight the evidence for a relationship between these personality types and enhanced avoidance and associative learning, which may increase risk for the development of PTSD. First, we provide the evidence confirming a relationship among BI, HA, distressed (Type D) personality, and PTSD. Second, we present recent findings that BI is associated with enhanced avoidance learning in both humans and animal models. Third, we will review evidence that BI is also associated with enhanced eyeblink conditioning in both humans and animal models. Overall, data from both humans and animals suggest that these personality traits promote enhanced avoidance and associative learning, as well as slowing of extinction in some training protocols, which all support the learning diathesis model. These findings of enhanced learning in vulnerable individuals can be used to develop objective behavioral measures to pre-identify individuals who are more at risk for development of PTSD following traumatic events, allowing for early (possibly preventative) intervention, as well as suggesting possible therapies for PTSD targeted on remediating avoidance or associative learning. Future work should explore the neural substrates of enhanced avoidance and associative learning for behaviorally inhibited individuals in both the animal model and human participants.

Avoidance Problems Reconsidered

Active avoidance is the prototypical paradigm for studying aversively-motivated instrumental behavior. However, avoidance research stalled amid heated theoretical debates and the hypothesis that active avoidance is essentially Pavlovian flight. Here I reconsider key "avoidance problems" and review neurobehavioral data collected with modern tools. Although the picture remains incomplete, these studies strongly suggest that avoidance has an instrumental component and is mediated by brain circuits that resemble appetitive instrumental actions more than Pavlovian fear reactions. Rapid progress may be possible if investigators consider important factors like safety signals, response-competition, goal-directed vs. habitual control and threat imminence in avoidance study design. Since avoidance responses likely contribute to active coping, this research has important implications for understanding human resilience and disorders of control.

A Transient Dopamine Signal Represents Avoidance Value and Causally Influences the Demand to Avoid

While an extensive literature supports the notion that mesocorticolimbic dopamine plays a role in negative reinforcement, recent evidence suggests that dopamine exclusively encodes the value of positive reinforcement. In the present study, we employed a behavioral economics approach to investigate whether dopamine plays a role in the valuation of negative reinforcement. Using rats as subjects, we first applied fast-scan cyclic voltammetry (FSCV) to determine that dopamine concentration decreases with the number of lever presses required to avoid electrical footshock (i.e., the economic price of avoidance). Analysis of the rate of decay of avoidance demand curves, which depict an inverse relationship between avoidance and increasing price, allows for inference of the worth an animal places on avoidance outcomes. Rapidly decaying demand curves indicate increased price sensitivity, or low worth placed on avoidance outcomes, while slow rates of decay indicate reduced price sensitivity, or greater worth placed on avoidance outcomes. We therefore used optogenetics to assess how inducing dopamine release causally modifies the demand to avoid electrical footshock in an economic setting. Increasing release at an avoidance predictive cue made animals more sensitive to price, consistent with a negative reward prediction error (i.e., the animal perceives they received a worse outcome than expected). Increasing release at avoidance made animals less sensitive to price, consistent with a positive reward prediction error (i.e., the animal perceives they received a better outcome than expected). These data demonstrate that transient dopamine release events represent the value of avoidance outcomes and can predictably modify the demand to avoid.