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Abnormal modulation of reward versus punishment learning by a dopamine D2-receptor antagonist in pathological gamblers.

Janssen LK, Sescousse G, Hashemi MM, Timmer MH, ter Huurne NP, Geurts DE, Cools R - Psychopharmacology (Berl.) (2015)

Bottom Line: Moreover, pervasive theoretical accounts suggest a key role for dopamine in reversal learning.In line with previous studies, blockade of D2 receptors with sulpiride impaired reward versus punishment reversal learning in controls.By contrast, sulpiride did not have any outcome-specific effects in gamblers.

View Article: PubMed Central - PubMed

Affiliation: Donders Institute for Brain, Cognition and Behavior, Radboud University, PO Box 9101, 6500 HB, Nijmegen, The Netherlands, l.k.janssen@donders.ru.nl.

ABSTRACT

Rationale: Pathological gambling has been associated with dopamine transmission abnormalities, in particular dopamine D2-receptor deficiency, and reversal learning deficits. Moreover, pervasive theoretical accounts suggest a key role for dopamine in reversal learning. However, there is no empirical evidence for a direct link between dopamine, reversal learning and pathological gambling.

Objective: The aim of the present study is to triangulate dopamine, reversal learning, and pathological gambling.

Methods: Here, we assess the hypothesis that pathological gambling is accompanied by dopamine-related problems with learning from reward and punishment by investigating effects of the dopamine D2-receptor antagonist sulpiride (400 mg) on reward- and punishment-based reversal learning in 18 pathological gamblers and 22 healthy controls, using a placebo-controlled, double-blind, counter-balanced design.

Results: In line with previous studies, blockade of D2 receptors with sulpiride impaired reward versus punishment reversal learning in controls. By contrast, sulpiride did not have any outcome-specific effects in gamblers.

Conclusion: These data demonstrate that pathological gambling is associated with a dopamine-related anomaly in reversal learning from reward and punishment.

No MeSH data available.


Related in: MedlinePlus

Sample trial of the reversal learning task. On each trial, participants were presented with two gambling cards. One of the cards was selected by computer and highlighted. Participants then had to predict, with a left or right button press, whether the card would be followed by a reward (a smiling emoticon, +100€ sign, and a high-pitch tone) or punishment (a sad emoticon, −100€ sign, and a low-pitch tone). After a short delay, the outcome was presented. The card-outcome associations were deterministic, and reversed after five to nine correct responses
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Fig1: Sample trial of the reversal learning task. On each trial, participants were presented with two gambling cards. One of the cards was selected by computer and highlighted. Participants then had to predict, with a left or right button press, whether the card would be followed by a reward (a smiling emoticon, +100€ sign, and a high-pitch tone) or punishment (a sad emoticon, −100€ sign, and a low-pitch tone). After a short delay, the outcome was presented. The card-outcome associations were deterministic, and reversed after five to nine correct responses

Mentions: We employed a deterministic reversal learning task similar to that described elsewhere (Cools et al. 2006; van der Schaaf et al. 2014). The task was programmed with Presentation software (Version 16, Neurobiobehavioral Systems, Inc.). The layout of the task was adjusted to fit the original instructions of a casino setting (see Cools et al. 2006) and to be more intuitive for gamblers. On each trial, subjects were presented with two gambling cards simultaneously (Fig. 1). One of the two cards was associated with upcoming reward, the other one with upcoming punishment. Unlike classic instrumental reversal learning tasks, subjects did not choose between the two stimuli. Instead one card was highlighted, and subjects had to learn to predict the outcome associated with this preselected card by trial-and-error. Responses were made by pressing one of two buttons—one for reward, the other for punishment—with the right index or middle finger (counterbalanced across subjects), and were self-paced. After a 1,000-ms post-response delay the outcome was presented for 500-ms followed by a 500-ms intertrial interval. Note that the outcomes were not contingent on the subjects’ responses, but on the highlighted stimulus; thus, contingencies were Pavlovian rather than instrumental. The stimulus-outcome contingency reversed after five to nine consecutive correct predictions. Subjects performed two blocks, each consisting of two runs of 120 trials (i.e. a total of 480 trials). In one block, reversals were always signaled by unexpected rewards (“reward block”), and in the other block reversals were always signaled by unexpected punishments (“punishment block”). Reward consisted of a smiling emoticon with a “+€100” sign. Punishment consisted of a sad emoticon with a “−€100” sign. The order of blocks was counterbalanced between sessions and across subjects. Error rate on the trials immediately after reversals (i.e. unexpected reward or punishment) indexes the ability to update predictions of reward and punishment, i.e. how well subjects learned from either unexpected reward or unexpected punishment. On these reversal trials, the same stimulus was highlighted as on the previous unexpected outcome trial such that non-outcome-specific requirements for motor switching and prediction updating were matched between reward and punishment conditions. This enabled direct comparison between reward and punishment reversals. Subjects were instructed according to the original procedure by Cools et al. (2006) and were trained extensively before the experiment so that they understood the structure of the task and the Pavlovian, rather than instrumental, nature of the contingencies (for details see Supplementary Materials).Fig. 1


Abnormal modulation of reward versus punishment learning by a dopamine D2-receptor antagonist in pathological gamblers.

Janssen LK, Sescousse G, Hashemi MM, Timmer MH, ter Huurne NP, Geurts DE, Cools R - Psychopharmacology (Berl.) (2015)

Sample trial of the reversal learning task. On each trial, participants were presented with two gambling cards. One of the cards was selected by computer and highlighted. Participants then had to predict, with a left or right button press, whether the card would be followed by a reward (a smiling emoticon, +100€ sign, and a high-pitch tone) or punishment (a sad emoticon, −100€ sign, and a low-pitch tone). After a short delay, the outcome was presented. The card-outcome associations were deterministic, and reversed after five to nine correct responses
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4537492&req=5

Fig1: Sample trial of the reversal learning task. On each trial, participants were presented with two gambling cards. One of the cards was selected by computer and highlighted. Participants then had to predict, with a left or right button press, whether the card would be followed by a reward (a smiling emoticon, +100€ sign, and a high-pitch tone) or punishment (a sad emoticon, −100€ sign, and a low-pitch tone). After a short delay, the outcome was presented. The card-outcome associations were deterministic, and reversed after five to nine correct responses
Mentions: We employed a deterministic reversal learning task similar to that described elsewhere (Cools et al. 2006; van der Schaaf et al. 2014). The task was programmed with Presentation software (Version 16, Neurobiobehavioral Systems, Inc.). The layout of the task was adjusted to fit the original instructions of a casino setting (see Cools et al. 2006) and to be more intuitive for gamblers. On each trial, subjects were presented with two gambling cards simultaneously (Fig. 1). One of the two cards was associated with upcoming reward, the other one with upcoming punishment. Unlike classic instrumental reversal learning tasks, subjects did not choose between the two stimuli. Instead one card was highlighted, and subjects had to learn to predict the outcome associated with this preselected card by trial-and-error. Responses were made by pressing one of two buttons—one for reward, the other for punishment—with the right index or middle finger (counterbalanced across subjects), and were self-paced. After a 1,000-ms post-response delay the outcome was presented for 500-ms followed by a 500-ms intertrial interval. Note that the outcomes were not contingent on the subjects’ responses, but on the highlighted stimulus; thus, contingencies were Pavlovian rather than instrumental. The stimulus-outcome contingency reversed after five to nine consecutive correct predictions. Subjects performed two blocks, each consisting of two runs of 120 trials (i.e. a total of 480 trials). In one block, reversals were always signaled by unexpected rewards (“reward block”), and in the other block reversals were always signaled by unexpected punishments (“punishment block”). Reward consisted of a smiling emoticon with a “+€100” sign. Punishment consisted of a sad emoticon with a “−€100” sign. The order of blocks was counterbalanced between sessions and across subjects. Error rate on the trials immediately after reversals (i.e. unexpected reward or punishment) indexes the ability to update predictions of reward and punishment, i.e. how well subjects learned from either unexpected reward or unexpected punishment. On these reversal trials, the same stimulus was highlighted as on the previous unexpected outcome trial such that non-outcome-specific requirements for motor switching and prediction updating were matched between reward and punishment conditions. This enabled direct comparison between reward and punishment reversals. Subjects were instructed according to the original procedure by Cools et al. (2006) and were trained extensively before the experiment so that they understood the structure of the task and the Pavlovian, rather than instrumental, nature of the contingencies (for details see Supplementary Materials).Fig. 1

Bottom Line: Moreover, pervasive theoretical accounts suggest a key role for dopamine in reversal learning.In line with previous studies, blockade of D2 receptors with sulpiride impaired reward versus punishment reversal learning in controls.By contrast, sulpiride did not have any outcome-specific effects in gamblers.

View Article: PubMed Central - PubMed

Affiliation: Donders Institute for Brain, Cognition and Behavior, Radboud University, PO Box 9101, 6500 HB, Nijmegen, The Netherlands, l.k.janssen@donders.ru.nl.

ABSTRACT

Rationale: Pathological gambling has been associated with dopamine transmission abnormalities, in particular dopamine D2-receptor deficiency, and reversal learning deficits. Moreover, pervasive theoretical accounts suggest a key role for dopamine in reversal learning. However, there is no empirical evidence for a direct link between dopamine, reversal learning and pathological gambling.

Objective: The aim of the present study is to triangulate dopamine, reversal learning, and pathological gambling.

Methods: Here, we assess the hypothesis that pathological gambling is accompanied by dopamine-related problems with learning from reward and punishment by investigating effects of the dopamine D2-receptor antagonist sulpiride (400 mg) on reward- and punishment-based reversal learning in 18 pathological gamblers and 22 healthy controls, using a placebo-controlled, double-blind, counter-balanced design.

Results: In line with previous studies, blockade of D2 receptors with sulpiride impaired reward versus punishment reversal learning in controls. By contrast, sulpiride did not have any outcome-specific effects in gamblers.

Conclusion: These data demonstrate that pathological gambling is associated with a dopamine-related anomaly in reversal learning from reward and punishment.

No MeSH data available.


Related in: MedlinePlus