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These results suggest that PD tendencies are associated with rigid beliefs and prevent adaptive use of social information in "safe" contexts. This supports previous proposals of a link between PD and aberrant social inference. (PsycInfo Database Record (c) 2020 APA, all rights reserved).In this brief review, we describe current computational models of drug-use and addiction that fall into 2 broad categories mathematically based models that rely on computational theories, and brain-based models that link computations to brain areas or circuits. Across categories, many are models of learning and decision-making, which may be compromised in addiction. Several mathematical models take predictive coding approaches, focusing on Bayesian prediction error. Other models focus on learning processes and (traditional) prediction error. Brain-based models have incorporated prefrontal cortex, basal ganglia, and the dopamine system, based on the effects of drugs on dopamine, motivation, and executive control circuits. Several models specifically describe how behavioral control may transition from habitual to goal-directed systems, consistent with computational accounts of compromised "model-based" control. Some brain-based models have linked this to the transition of behavioral control from ventral to dorsal striatum. Overall, we propose that while computational models capture some aspects of addiction and have advanced our thinking, most have focused on the effects of drug use rather than addiction per se, most have not been tested on and/or supported by human data, and few capture multiple stages and symptoms of addiction. We conclude by suggesting a path forward for computational models of addiction. (PsycInfo Database Record (c) 2020 APA, all rights reserved).The predictive processing framework (PPF) attempts to tackle deep philosophical problems, including how the brain generates consciousness, how our bodies influence cognition, and how cognition alters perception. As such, it provides a zeitgeist that incorporates concepts from physics, computer science, mathematics, artificial intelligence, economics, psychology, and neuroscience, leveraging and, in turn, influencing recent advances in reinforcement learning and deep learning that underpin the artificial intelligence in many of the applications with which we interact daily. PPF purports to provide no less than a grand unifying theory of mind and brain function, underwriting an account of perception, cognition, and action and their dynamic relationships. While mindful of legitimate criticisms of the framework, to which we return below, an important test of PPF is its utility in accounting for individual differences such as psychopathology. These, then, are the central concern of this special section of the Journal of Abnormal Psychology What is the state of the art with regards to applying the PPF to the symptoms of mental illness? How might we leverage its insights to elevate and systematize our explanations, and ideally treatments, of those symptoms? And, conversely, can we refine and refute aspects of the PPF by considering the particular challenges that our patients experience as departures from the parametric estimates of the PPF? (PsycInfo Database Record (c) 2020 APA, all rights reserved).Orexin has been suggested to play a role in regulating the reward circuits and enhancing drug-seeking behaviors; however, its role in methamphetamine (METH) addiction remains unclear. We previously found that blood orexin-A levels are upregulated in individuals with recent METH exposure. Whether the levels would be altered following withdrawal is unknown. In this study, we compared the levels of serum orexin-A in individuals who use METH between the acute withdrawal (AW) phase and the subacute withdrawal (SAW) phase at baseline (T1) and examined the alterations in these levels after 2 weeks of abstinence (T2). In total, 60 participants (51 men and 9 women) were enrolled in the study; 20 participants with METH-positive urine test results were included in the AW group, and 40 participants with METH-negative urine test results who had self-reportedly last taken METH within the preceding 1-2 months were included in the SAW group. Serum orexin-A levels were measured using enzyme-linked immunosorbent assay. [https://www.selleckchem.com/products/perhexiline-maleate.html find more] No significant differences in orexin-A levels were observed between the AW and SAW groups at baseline (p = .06). After 2 additional weeks of abstinence, the levels decreased significantly in the SAW group (0.58 ± 0.13 ng/mL) but not in the AW group (0.50 ± 0.14 ng/mL, p = .004). Our results demonstrated that orexin-A levels might decrease after a longer period of METH withdrawal, indicating that the orexin system is dysregulated in the addictive process of METH. (PsycInfo Database Record (c) 2020 APA, all rights reserved).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 less then .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 less then .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) 2020 APA, all rights reserved).