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Studies applying this approach show that although behavioral performance may be similar across different clinical groups, the cognitive processes that underlie these behavioral profiles may vary across groups in clinically meaningful ways. Further, we still know very little about the reversibility of the observed neurocognitive deficits with abstinence, given that with few exceptions (Ersche et al.

The chronic relapsing nature of addiction suggests that some of the neurocognitive deficits, particularly those in decision-making, may persist with abstinence and may be critically implicated in increased susceptibility to relapse. In contrast, the amphetamine epidemic in Bulgaria started more recently in the new millennium when Bulgaria became a major center for production of synthetic amphetamine-type stimulants and is currently one of the top five highest-prevalence countries in Europe (European Monitoring Center for Drugs and Drug Addiction, 2011).

Hence, amphetamine users are typically younger-normally in their late teens or early 20s. Notably, few SDI use the two types of Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA concurrently. We compared the decision-making performance of heroin and amphetamine users to that of healthy Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA (HC) without any history of substance dependence.

We followed these behavioral analyses by applying a computational modeling Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA, in order to better characterize their decision-making styles and to disentangle the distinct neurocognitive processes underlying the decision-making performance of heroin and amphetamine users. The modeling results and their interpretations depend on which model Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA use.

Therefore, we first identified the best-fitting model by comparing three existing computational models using a Bayesian model comparison technique, a simulation method, and parameter recovery tests (see Materials and Methods below for more details). Then, we compared groups in a Bayesian way using the best-fitting model, but also tested whether we would observe similar group differences with the reverse vasectomy models.

Based on previous animal and human studies, we hypothesized that amphetamine and heroin users would show distinct decision-making profiles. In light of the growing evidence for the relationship of externalizing and internalizing Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA traits and disorders with decision-making and drug addiction, in exploratory analyses we considered the relationship between impulsivity and psychopathy (externalizing spectrum) Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA depression and anxiety (internalizing spectrum) with decision-making.

We hypothesized that externalizing but not internalizing traits and states would be associated with compromised decision-making.

Study participants included 129 individuals, enrolled in g st larger study of impulsivity in heroin and amphetamine users in Sofia, Bulgaria. Potential participants were recruited via flyers placed at substance abuse clinics, cafes, bars, and night clubs in Sofia and screened via telephone and in-person on their medical Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA substance use histories.

SDI had lifetime DSM-IV histories of opiate or stimulant dependence. Demographically similar individuals with no history Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA substance dependence were included as controls.

Study participants included 38 amphetamine users, 43 heroin users, and 48 HC. Inclusion criteria consisted of age between 18 and 50 years, minimum of 8 years of formal education, ability to speak and read Bulgarian, estimated IQ greater than 80, negative breathalyzer test for alcohol and negative rapid urine toxicology screen for opiates, cannabis, amphetamines, methamphetamines, benzodiazepines, barbiturates, cocaine, MDMA, and methadone.

Exclusion criteria included history of neurologic illness or injury, history of psychotic disorders, and current opioid substitution therapy (OST). All participants were HIV-seronegative, as verified by rapid HIV test. All participants provided written informed consent.

Study procedures were approved by the Institutional Review Boards of the University of Illinois at Chicago and the Medical University in Sofia on behalf of the Bulgarian Addictions Institute. The Raven's Progressive Matrices was administered to index estimated IQ. For the exploratory analyses, we also tabulated several substance use characteristics including number of years of drug use, length of abstinence from the primary drug of dependence, number of DSM-IV criteria met for the primary drug of dependence, severity of nicotine dependence, and history of past cannabis dependence.

Decision-making was measured with the computerized IGT (Bechara et al. The task requires participants to select cards from one of Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA decks with the goal of maximizing profits.

In the modified version of the IGT (Bechara et al. Human penis frequencies of punishment are identical to those in the original IGT version. Participants have to learn the task contingencies by trial-and-error. Healthy participants typically learn to select cards from the advantageous decks as the task progresses, thereby achieving a higher cumulative reward value.

Behavioral performance analyses were based on the total net score, calculated by subtracting the number of disadvantageous deck selections from the number of advantageous deck selections. From a statistical perspective, the IGT is a four-armed bandit problem (Berry and Fristedt, 1985), a special case of reinforcement learning (RL) problems in which an agent needs to learn an environment by choosing actions and experiencing the outcomes of those actions.

We compared three of the most promising models of build confidence IGT according to the literature (e. We also used a simulation method to examine whether a model with estimated parameters can generate the observed choice pattern (Ahn et al. We describe the mathematical details of all models, which are also available in the previous publication (Worthy et al.

The PVL models have three components. The PVL-Delta and PVL-DecayRI models are identical except that they use different learning rules. Based on the outcome of the chosen option, the expectancies of the Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA were computed using a learning rule.

On the other hand, in the delta rule, the Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA of only the selected deck is updated and the expectancies of the other Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA remain unchanged:A determines how much weight is placed on past experiences of the chosen deck vs. A low learning rate indicates that the most recent outcome has a small influence on the expectancy and forgetting is more gradual.

A high learning rate indicates that the recent outcome has a large influence on the expectancy of the chosen deck and forgetting is more rapid. Note that we used the same symbol (A) for the learning models tension headache the two PVL models, but A has different meaning in each learning model (i. The softmax choice rule (Luce, 1959) was then used to compute the probability of choosing each deck j. Recent Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA suggests that participants often use a simple win-stay-lose-switch (WSLS) or perseverative strategy on the IGT, which cares only about the very last trial's information for making a Nitrolingual Pumpspray (Nitroglycerin Lingual Spray)- FDA on the current trial (Worthy et al.

They showed that the PVL-DecayRI had the best model fits for about half of the subjects, whereas the WSLS model was the best-fitting model for the other half. Based on these findings, Worthy et al. The VPP model assumes that a participant keeps track of deck expectancies Ej(t) and perseverance strengths (Pj(t)). The expectancies are computed by the learning rule of the PVL-Delta model (Equation 3).

A positive value would indicate that the feedback reinforces a tendency to persevere on the same deck on the next trial whereas a negative value would indicate that the feedback reinforces a tendency to switch from the chosen deck. Unlike posterior distributions, frequentist p values depend on the sampling and testing intentions of the analyst. Bayesian methods also seamlessly provide posterior distributions for the type of complex hierarchical models we use here, more flexibly than deriving p values.

For clarity and to accommodate readers more familiar with NHST, we report in parallel NHST results whenever appropriate and when there are compatible NHST yagona available. We used the posterior means of individual parameters for NHST and regression analyses.



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