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

ABSTRACT: 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.

SUBMITTER: Ahn WY

PROVIDER: S-EPMC4129374 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Project description:Background: Psychopathy and substance use disorders (SUDs) are both characterized by neurocognitive impairments reflecting higher levels of impulsivity such as reward-driven decision-making and deficient inhibitory control. Previous studies suggest that psychopathy may exacerbate decision-making deficits, but it may be unrelated to other neurocognitive impairments among substance dependent individuals (SDIs). The aim of the present study was to examine the role of psychopathy and its interpersonal-affective and impulsive-antisocial dimensions in moderating the relationships between dependence on different classes of drugs and neurocognitive domains of impulsivity. Method: We tested 693 participants (112 heroin mono-dependent individuals, 71 heroin polysubstance dependent individuals, 115 amphetamine mono-dependent individuals, 76 amphetamine polysubstance dependent individuals, and 319 non-substance dependent control individuals). Participants were administered the Psychopathy Checklist: Screening Version (PCL:SV) and seven neurocognitive tasks measuring impulsive choice/decision-making (Iowa Gambling Task; Cambridge Gambling Task; Kirby Delay Discounting Task; Balloon Analog Risk Task), and impulsive action/response inhibition (Go/No-Go Task, Immediate Memory Task, and Stop Signal Task). Results: A series of hierarchical multiple regressions revealed that the interpersonal-affective dimension of psychopathy moderated the association between decision-making, response inhibition and both amphetamine and heroin dependence, albeit differently. For amphetamine users, low levels of interpersonal-affective traits predicted poor decision-making on the Iowa Gambling Task and better response inhibition on the Stop Signal task. In contrast, in heroin users high interpersonal-affective psychopathy traits predicted lower risk taking on the Cambridge Gambling Task and better response inhibition on the Go/No-Go task. The impulsive-antisocial dimension of psychopathy predicted poor response inhibition in both amphetamine and heroin users. Conclusions: Our findings reveal that psychopathy and its dimensions had both common and unique effects on neurocognitive function in heroin and amphetamine dependent individuals. Our results suggest that the specific interactions between psychopathy dimensions and dependence on different classes of drugs may lead to either deficient or superior decision-making and response inhibition performance in SDIs, suggesting that psychopathy may paradoxically play a protective role for some neurocognitive functions in specific subtypes of substance users.

Project description:Aims: Chronic cannabis users show impairments on laboratory measures of decision making which reflect risk factors for initiation and continued use of cannabis. However, the differential sensitivity of these tasks to cannabis use has not been established. Moreover, studies to date have often lacked assessment of psychiatric histories and use of other illicit substances, both of which may influence decision making outcomes. The current study aimed to address these limitations by (1) including multiple types of decision making tasks, (2) implementing the Probabilistic Reversal Learning Task, a measure of decision making under uncertainty, for the first time in cannabis users, (3) including young adult cannabis users with no other psychiatric disorders, and (4) conducting urinalysis to exclude users of other illicit drugs. Methods: Thirty-three current cannabis users without comorbid psychiatric disorders and 35 cannabis non-users completed behavioral measures of decision-making (Iowa Gambling Task), reward discounting (Delay Discounting Task), choice-outcome learning (the Probabilistic Reversal Learning Task) and a questionnaire assessment of impulsivity (Barratt Impulsiveness Scale). Results: Relative to non-users, cannabis users demonstrated greater preference for immediate vs. delayed rewards on the Delay Discounting Task, made fewer advantageous decisions on the Iowa Gambling Task, and endorsed greater impulsivity on the Barratt Impulsiveness Scale scales. Cannabis users and non-users showed comparable performance on the Probabilistic Reversal Learning Task. Frequency of past-month cannabis use and total years of use did not predict decision making or impulsivity. Conclusions: Young adult cannabis users demonstrated higher discounting rates and impairments in learning cost-benefit contingencies, while reversal learning was unaffected. Self-reported impulsivity was elevated as well. None of these measures correlated with current or lifetime estimates of cannabis use, arguing against a dose-relationship. Interventions that target improvement in affected components of decision making may be helpful in reducing cannabis use and relapse.

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

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