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Official websites use. Share sensitive information only on official, secure websites. Long-term cannabis and cocaine use has been associated with impairments in reversal learning. However, how acute cannabis and cocaine administration affect reversal learning in humans is not known. A double-blind placebo-controlled randomized 3-way crossover design was used. Sixty-one regular poly-drug users completed a deterministic reversal learning task under the influence of cocaine, cannabis, and placebo that enabled assessment of both reward- and punishment-based reversal learning. Proportion correct on the reversal learning task was increased by cocaine, but decreased by cannabis. COMT genotype did not modulate drug-induced effects on reversal learning. These data indicate that acute administration of cannabis and cocaine has opposite effects on reversal learning. The effects of cocaine, but not cannabis, depend on interindividual genetic differences in the dopamine D2 receptor gene. The online version of this article doi Reversal learning is the ability to flexibly adapt behavior in response to changing stimulus—outcome contingencies. It is a cognitive function that is frequently reported to be affected by drug use. Preclinical research has revealed that cannabis and cocaine are associated with impaired reversal learning Egerton et al. Furthermore, chronic cocaine use in human addicted individuals has been associated with impaired flexible behavior Ersche et al. Impaired reversal learning is also a dimension of impulsivity-related traits. Trait impulsivity, which includes reversal learning, has been related to enhanced drug self-administration levels in rodents Cervantes et al. How acute effects of drugs of abuse causally affect reversal learning in humans is yet to be established. Especially for cocaine, acute effects are often fundamentally different from chronic use. Long-term studies often show impairments on cognitive functions, while acute administration most often yields cognitive enhancing effects Fillmore et al. Here, we examined reversal learning following the acute administration of cannabis and cocaine, the two most commonly used illicit drugs in Europe EMCDDA We also investigated drug-induced effects on reversal learning as a function of genetic variants in two common dopaminergic candidate genes. None of the previous studies on cannabis and cocaine have dissociated between reversal based on unexpected reward versus reversal based on unexpected punishment. This issue is pertinent, because cannabis and cocaine have been argued to act by way of modulating dopamine transmission, which is accompanied by a shift in learning from reward versus punishment Maia and Frank Increases in striatal dopamine transmission, as elicited by cocaine Volkow et al. In agreement, cocaine has been shown to enhance reward-magnitude in rats Roesch et al. This suggests that cocaine might increase the impact of unexpected reward on reversal learning—thus improving reward versus punishment reversal learning. Cannabis has also been associated with increases in striatal dopamine release Bossong et al. Current evidence has also suggested that cannabis reduces sensitivity to external reinforcing stimuli irrespective of their valence Lane et al. Individual differences in baseline levels of dopamine synthesis capacity have been shown to be predictive of the effects of dopaminergic drugs on reversal learning Cools et al. Accordingly, the effects of cannabis and cocaine might also depend on individual differences in baseline levels of dopamine de Wit Thus, we exploited common polymorphisms in dopamine genes to take into account such interindividual differences. Moreover, dopamine D2 receptor function—whether or not investigated by means of polymorphisms or pharmacology—has frequently been reported to be associated with individual differences in reversal learning Lee et al. Val homozygotes are thought to exhibit the largest cognitive benefit from dopamine-enhancing substances such as d -amphetamine and modafinil Mattay et al. In this study, we investigated the acute effects of cannabis and cocaine in healthy regular users of these drugs. All participants received cocaine, placebo, or cannabis in a placebo-controlled double-blind crossover study design. A reversal learning paradigm was employed that is well established to be sensitive to dopaminergic drug manipulations Cools et al. This paradigm enabled us to assess 1 whether cannabis and cocaine alter reward-based vs. In order to investigate the functional selectivity of the effects to reversal learning, we also investigated attention switch task AST and forward planning tower of London: ToL. Functional neuroimaging has most consistently identified the implication of the prefrontal cortex during set-switching Monsell Cocaine was predicted to enhance reward relative to punishment-based reversal learning. For cannabis, two hypotheses were deemed possible. First, cannabis might improve reward versus punishment reversal learning as a result of the dopamine-enhancing effects. Second, cannabis might have a valence-independent impairing effect on reversal learning, consistent with prior observations that cannabis reduces sensitivity to external reinforcing stimuli and impairs other executive functions e. Sixty-four healthy regular non-addicted poly-drug users, aged 18—40 years were recruited through advertisements on the Internet, university campuses, and word-of-mouth referrals. A total of 61 subjects remained in the study, because 3 had to be excluded. One withdrew consent after the first testing day, one had a cardiovascular reaction to the blood draw and study discontinuation was decided by the investigators, and one did not adhere to the abstinence instructions as confirmed by high baseline cannabinoid levels for each testing day. All subjects reported regular cannabis use i. They had to be in good physical health and be of normal weight body mass index 18— Further exclusion criteria were alcohol or substance dependence or history of psychiatric or neurological disorders as assessed during a clinical interview M. Not all subjects completed all tasks in all three drug conditions. Of the 61, 3 subjects did not complete the attention switch task and 5 did not complete the tower of London in the cannabis drug condition because of adverse events. There were 14 missing datasets for the reversal learning due to adverse events or lack of motivation 13 cannabis, 1 cocaine. The study was part of a multicenter trial, but the current results were collected at one study site. The reversal learning task, attention switch task, and the tower of London were administered as part of a larger cognitive test battery see Dutch Trial Register, trial number NTR; results will be published elsewhere. The study was conducted according to the code of ethics on human experimentation established by the Declaration of Helsinki , amended in Seoul , and was approved by the Medical Ethics Committee of Maastricht University and the regional ethics committee for the University Medical Center of the Radboud University. A permit for obtaining, storing, and administering cocaine and cannabis was obtained from the Dutch Drug Enforcement Administration. Prior to starting the testing days, all participants were invited for a screening and practice day where they gave informed consent and received a medical examination including assessment of blood and urine samples for standard chemistry and hematology, electrocardiogram ECG , and interview of medical and drug use history. All subjects completed shortened versions of all cognitive paradigms in a practice session. After study inclusion, subjects completed a series of cognitive tests on three separate testing days that were separated by at least a week. Subjects were asked to abstain from caffeine and nicotine on the testing day and from cannabis and alcohol at least 24 h prior to each testing day. Figure 1 shows the timeline of procedures on a testing day. The testing day started with a light breakfast non-caffeinated tea or water, up to four sandwiches and performance of a urine drug screen, pregnancy test women only , and alcohol breath analyzer. This was followed by pre-drug baseline vital sign recordings, subjective questionnaires, and blood draws see supplementary material 1 for drug metabolites and see van Wel et al. The delay of 45 min was based on prior observations that the capsule needs about 45 min before plasma concentrations start to increase Fillmore et al. Conversely, cannabis was anticipated to be absorbed immediately Grotenhermen After T1, the first block of behavioral tasks was assessed block 1 during which the attention switch task and tower of London were completed. Next, the second block block 2 of behavioral tasks was administered. The reversal learning task was at the end of this second block. Vital sign recordings, subjective questionnaires, and blood draws were obtained 5 min after drug administration T1 and T2 and at the end of the testing day. An extra vital sign recording was performed before T2 to assess the safety of administering the potential booster. Timeline in minutes of the course of a testing day. The black triangles represent the moment of cocaine or placebo capsule administration and the gray triangles represent the moment of cannabis or placebo vapor administration. Of the 59 subjects who completed the reversal learning task in the cocaine condition, 16 did not receive the second booster capsule. Five subjects did not receive a second cocaine dosage, because the decision to include a second booster dosage was made after the start of the study and approval for this amendment had to be awaited. Supplementary analyses of the effects of cocaine after exclusion of these 16 subjects revealed a similar pattern of the results. Of the 46 subjects who completed the reversal learning task in the cannabis condition, 6 did not receive a second administration 3 refused, 3 exceeded vital sign limits. This study used a double-blind, double-dummy, placebo-controlled, three-way crossover design. A herbal mixture containing hemp flowers was used as placebo for cannabis. The vapor was stored in a polythene bag equipped with a valved mouthpiece. Subjects were instructed to inhale deeply, to hold their breath for 10 s after each inhalation and to take as much time as needed to empty the bag in order to minimize the occurrence of adverse events. Cocaine HCl and matching placebo cocaine were encapsulated in white opaque capsules. The placebo capsules contained only filling material of equivalent weight. The capsules were taken orally with ml of water. The sequence of the drug conditions was counterbalanced. Blood samples were obtained by venipuncture, and DNA was isolated using the following standard protocols. Genotypes were scored using the algorithm and software supplied by the manufacturer Applied Biosystems. The COMT genotype could not be determined for two subjects. A deterministic reversal learning paradigm was used see Fig. One of these stimuli was associated with reward and the other with punishment. Subjects were instructed to learn these deterministic stimulus—outcome associations by predicting the outcome of the stimulus that was highlighted by a black border. Outcome predictions were made by pressing either a red for punishment or green for reward button with the index finger of the left and the right hand counterbalanced between subjects. One second after the button press, the outcome was presented for ms at the location of the stimulus. Subjects did not get any monetary rewards. The task was self-paced and no response deadlines were employed. After 4—6 consecutive correct predictions, the stimulus—outcome contingency reversed. This was signaled by either an unexpected reward, presented after the previously punished stimulus was highlighted, or an unexpected punishment, presented after the previously rewarded stimulus was highlighted. After unexpected outcomes, the same stimulus was highlighted again, such that behavioral and cognitive requirements were matched between valence conditions. The deterministic reversal learning task. On each trial, subjects are presented with a face and a landscape. One of the images is surrounded by a black border. After the response had been made, the subject saw the actual outcome. The reversals are indicated by an unexpected reward or unexpected punishment trial. Each participant performed four experimental blocks that contained trials: two blocks in which reversals were signaled by unexpected rewards reward valence and two blocks in which reversals were signaled by unexpected punishment punishment valence. Accuracy on the trials directly following these unexpected outcomes switch trials represents how well subjects updated their stimulus—outcome associations. The remainder of the trials consisted of non-switch trials in which subjects simply had to predict if the trial was associated with reward non-switch reward or punishment non-switch punishment. Thus, in total, there were three trial types switch, non-switch reward, non-switch punishment across two valence levels reward, punishment. Proportion correct is the main outcome measure in this task. This task is an adjusted version of the task reported by Kramer et al. The AST consists of two non-switch blocks and one switch block. During the task, four stimulus types were randomly presented on the screen 1, 3, , or The non-switch blocks included 40 randomly presented trials each, consisting of 10 stimuli of each stimulus type. The switch block included 80 randomly presented trials and 20 stimuli of each stimulus type. The questions were presented for ms, after which a stimulus was presented for ms. After this, a ms response interval occurred before the next instruction appeared. The dependent variables were mean proportion correct and reaction time. The tower of London task provides a measure of forward planning Shallice The original version of the Tower of London consists of three colored balls, which must be arranged on three sticks to match the target configuration on a picture while only one ball can be moved at a time. The present version consisted of computer-generated images of begin- and end-arrangements of the balls. The subjects were asked to decide as quickly as possible, by pushing a coded button, whether the end arrangement could be accomplished in 2, 3, 4, 5, or 6 steps from the begin arrangement Veale et al. The complexity of the task was dependent on the minimal number of steps in which the rearrangement could be achieved. To avoid guessing, only the trials of two to five steps are analyzed. Proportion of correct decisions and mean reaction time per step were the main outcome measures. To assess drug effects on reversal learning, a linear-mixed model LMM was constructed with subject as a random factor and drugs cocaine, placebo, cannabis ; valence reward, punishment ; and trial type switch, non-switch reward, non-switch punishment as fixed factors in each of the analyses. To measure drug effects on AST and ToL performance, LMMs were constructed with subject as a random factor and drugs cocaine, placebo, cannabis ; block switch, non-switch, for AST ; or step steps 2, 3, 4, and 5, for ToL as fixed factors. We present and plot raw data in tables and figures for illustrative purposes. A significant interaction effect was followed by drug—placebo contrasts to establish the separate effects of cannabis and cocaine and their interaction with genotype. Mixed model analysis of variance rather than ANOVA was chosen because subjects for whom data were unavailable for one or two of the three drug conditions could be included in the analysis by assuming values were missing at random. Table 1 shows the subject characteristics for gender, age, education and drug use history stratified for genotype. There was a significant DRD2 genotype effect on occasions of cocaine use in the past year. However, the A1 carrier group contained one outlier. There were no other significant genotype effects. The average proportions of correct responses are shown in Table 2. Mixed model analysis revealed a significant main effect of drugs F 2, Thus, cocaine improved, while cannabis impaired performance on the reversal learning task in a non-valence specific manner and the effects extended to the non-switch trials. Post-hoc analyses of the two-way interaction between valence and trial types showed a significant effect of valence for switch trials, i. The average proportion of correct responses and reaction times for the attention switch and the tower of London tasks are shown in Table 3. Analysis revealed the expected switch effect as indicated by a decreased proportion of correct in the switch compared with the non-switch block 0. There was also a main effect of drugs on proportion correct F 2, Pairwise comparisons revealed that subjects made more errors under the influence of cannabis compared with placebo 0. There were no differences between the cocaine and placebo condition 0. In addition, in terms of reaction times, there was also a main effect of switch F 1, Subjects took longer to respond to trials in the switch compared with the non-switch block vs. The analyses on the reaction times in the ToL showed the expected decrease in proportion correct with increasing number of steps F 3, There was also a significant effect of drugs F 2, Likewise, there was a significant main effect of steps on reaction time F 3 , In addition, a main effect of drugs F 2 , The main findings of this study are that 1 cocaine and cannabis exerted opposite effects on reversal learning that are non-specific with respect to valence. Cocaine increased proportion correct whereas cannabis decreased proportion correct. These effects were observed across all trials: switch and non-switch; 2 drug effects on reversal learning did not vary with the valence of the outcome reward vs. Furthermore, this was irrespective of switch or non-switch trials, suggesting that this effect reflects modulation of reinforcement learning rather than reversal learning specifically. The finding that cocaine had greater beneficial effects in subjects with genetically determined lower dopamine D2 receptor density concurs with prior pharmacogenetic studies also showing greater effects of dopaminergic drugs in such subjects Cohen et al. For example, in the work by Cohen et al. The results also accord with a recent pharmacological PET study in healthy individuals Ersche et al. Although cocaine is pharmacologically different from the dopamine precursor l -dopa and the dopamine receptor agonists investigated in the aforementioned studies Cohen et al. Cannabis has a unique and complicated pharmacological profile, involving many neurotransmission systems such as dopamine, GABA, and acetylcholine Bossong et al. More extensive future studies should address the pharmacogenetic effects of cannabis on cognition. Whether individual differences in acute drug effects on reversal learning could provide information with relevance for drug-using individuals is an intriguing question. Our results showed that the A1 carriers showed the largest cognitive benefits after cocaine. The higher benefit from cocaine for A1 carriers perhaps means that the reinforcing effects are larger for this group. This fits well with studies showing that lowered expression of D2 receptors is associated with stronger pleasurable responses to stimulants Volkow et al. This lack of significant association might be due to a lack of statistical power, which is a common problem in gene-cognition studies. This includes failures to replicate seminal pharmacogenetic findings on which our hypotheses were based Mattay et al. The current results thus suggest that better powered studies are needed to establish the role of the COMT gene in cognition in general and in combination with pharmacological substances. Specifically, these studies indicated that carriers of the gene variant associated with presumably lower D2 receptor density show impaired performance on reinforcement learning Klein et al. This also concurs with prior observations from pharmacological work showing that reversal learning performance depends on the degree of dopamine D2 receptor availability van der Schaaf et al. This contrasts with studies that have linked the DRD2 polymorphisms to learning from punishment or avoidance learning specifically Frank and Hutchison ; Klein et al. However, we note that the paradigms used in the various studies are very different: where we employed a deterministic paradigm in which the outcome was dependent on the stimulus, previous work commonly used a probabilistic reversal learning paradigm in which the outcome was dependent on the response. Cocaine is a powerful stimulant and the observed improvement on the reversal learning task is in the same direction as the effects of other stimulant drugs such as amphetamine and modafinil on learning tasks in humans Pessiglione et al. Stimulant drugs share comparable pharmacological properties such as increasing dopamine and noradrenaline levels in the brain and enhancement of arousal Kuczenski and Segal ; Berridge These results support the interpretation that cocaine facilitates overall learning due to its stimulant properties. By contrast, the cocaine-induced performance improvement contrasts with previous observations in rodents and humans showing that prior chronic use of cocaine is associated with impaired reversal learning Ersche et al. As such, the present results concur with previous findings showing that acute effects of cocaine can be opposite to the chronic effects of cocaine reviewed in Spronk et al. Moreover, this cocaine-induced improvement in learning was restricted to the reversal learning task and did not extend to the other tasks. Performance on the attentional switch task and tower of London were unaffected by cocaine, although reaction times on the AST were faster after cocaine. Other studies on stimulant drugs have also failed to show effects on forward planning and switching of attention van Wel et al. This suggests that cocaine enhances the more cognitive demanding process of reversal learning, but leaves basal functions such as attention switching and forward planning intact. Additionally, we observed that valence differentially affected learning. Participants seemed to learn better after punishment rather than reward predicting reversal. Most relevant to the current investigation, drugs did not differentially affect the degree of learning from reward versus punishment, but instead only revealed a general improvement on all trial types. For cocaine, the results contrasted with our hypothesis in which we expected relative enhanced improvement in reward versus punishment learning. These results are in striking contrast with previous findings showing opposite effects of dopaminergic agents on reward and punishment learning Cools et al. On the other hand, they seem to concur with recent pharmacological studies showing unidirectional effects on both reward and punishment learning Pessiglione et al. There are several reasons that may explain these contrasting results. One possible explanation may relate to the instrumental and Pavlovian learning components in our reversal learning task Van der Schaaf et al. This process depends on learned Pavlovian stimulus—outcome associations and is measured by the accuracy on the trials directly after a reversal signaled by unexpected rewards and unexpected punishments. Alternatively, subjects could improve on the task by detecting whether their action was correct or incorrect by means of a match or mismatch between their prediction action and the outcome. This process depends on instrumental action-outcome associations and may be reflected by general accuracy on all trials irrespective of outcome valence or reversal. Indeed, in previous studies, an instrumental learning task without reversals was used in which improvement in both reward-approach as well as punishment-avoid learning was observed Pessiglione et al. Taken together, our findings that cocaine improved general accuracy might reflect improvements on the instrumental component of our task, which could have overshadowed the expected valence-dependent effects. Alternatively, the lack of valence-specific effects after cocaine may imply enhanced saliency of both reward and punishment signals. Dopamine has been shown to code information related to salient events Bromberg-Martin et al. Accordingly, enhanced motivational salience due to elevated dopamine levels could thus have led to equally improved learning from both reward and punishment signals. Third, cocaine is different from the mostly agonists and antagonists that were administered in previous work and might therefore exert very different effects. Cocaine does not only enhance dopaminergic neurotransmission, but affects the serotonergic and noradrenergic systems as well Ritz et al. Therefore, not only the elevated dopamine levels, but also other cathecholamines might be responsible for non-specific alterations in learning Breitenstein et al. In other words, the general pharmacological effects of cocaine may have resulted in more general changes on our task by affecting multiple learning components of the tasks e. In contrast to cocaine, cannabis yielded an overall impairment in reversal learning task which was valence-independent. Furthermore, the cannabis-induced impairments were across switch and non-switch trials. We have also found impaired performance on the attention switch task and tower of London. The results also occur with studies cannabis administration studies on other executive functions like response inhibition and error monitoring, which show comparable impairments Spronk et al. Our results suggest that cannabis affects a generic process, rather than exerting any specific effects on cognitive functions. Diminished motivation, or decreased willingness to exert effort, is a well-known side effect of cannabis use Lynskey and Hall The results from the current study thus suggest that diminished motivation might underlie impaired performance under acute influence as well. A number of issues could have influenced the interpretation of our results. First, it is possible that ceiling effects occurred in the cocaine condition. This is of particular relevance for the interpretation of the DRD2 genotype interaction. Second, we used a statistical model linear-mixed model that assumes that missing values were missing at random. Most of the missing cases, however, were in the cannabis condition. However, we already found an impaired performance under cannabis. If anything, inclusion of those subjects would have demonstrated an even stronger impairment on the level of condition. Third, all subjects reported the use of other substances most notably XTC, amphetamine, alcohol, and nicotine. The required abstinence, of smoking in particular, could have yielded underperformance in each of the conditions. However, as this effect would have been the same in each of the three conditions, it is unlikely that this had a large effect on the outcomes. Ideally, future studies should address how cocaine and cannabis affect reversal learning in naive users, but ethical concerns limit the feasibility of such studies. Fourth, differences in pharmacodynamics and fatigue effects might have contributed to the dissociative effects on the AST and ToL versus the reversal learning task. The AST and ToL were assessed early in the testing day after the first drug administration, while the reversal learning task was assessed at the very end of the testing day after the second drug administration. Fifth, although our study is the largest of its kind, the power to detect effects of genotype is limited. We kindly thank the participants for taking part in the study and acknowledge the contribution of Jan Leijtens in data collection, and Michiel Kleinnijenhuis and Sean Fallon for providing valuable comments on the manuscript. Ramaekers and Robbert J. Ellen R. The funders had no role in study design, data collection and analyses, decision to publish, or preparation of the manuscript. This section collects any data citations, data availability statements, or supplementary materials included in this article. As a library, NLM provides access to scientific literature. Psychopharmacology Berl. Find articles by Marieke E Van der Schaaf. Find articles by Roshan Cools. Find articles by Barbara Franke. Find articles by Janelle H P van Wel. Find articles by Johannes G Ramaekers. Find articles by Robbert J Verkes. Received Mar 20; Accepted Sep 20; Issue date Open in a new tab. ESM 1 Similar articles. Add to Collections. Create a new collection. Add to an existing collection. 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How can I buy cocaine online in Zandam

In the Netherlands, it is against the law to possess, sell or produce drugs. Soft drugs are less damaging to health than hard drugs. Therefore, in the Netherlands, coffee shops are permitted to sell cannabis under certain strict conditions. A coffee shop is an establishment where cannabis is sold but no alcoholic drinks are sold or consumed. This is part of the Dutch policy of toleration. However, the Netherlands has a policy of toleration regarding soft drugs. This means that the sale of small quantities of soft drugs in coffee shops is a criminal offence but the Public Prosecution Service does not prosecute coffee shops for this offence. Neither does the Public Prosecution Service prosecute members of the public for possession of small quantities of soft drugs. These quantities are defined as follows:. Coffee shops:. Municipalities determine whether to allow coffee shops to operate within their boundaries, and if so, how many. They can also impose additional rules. The objective is to combat the nuisance and crime associated with coffee shops. Coffee shops must become smaller and focus on the local market. This policy will make Dutch coffee shops less attractive to drug users from abroad. To combat drug-related crime and nuisance, the Dutch government introduced a new toleration rule on 1 January only 'residents of the Netherlands' are permitted to visit coffee shops and purchase cannabis there. A resident of the Netherlands is someone who lives in a Dutch municipality and is registered there. Whether this rule is actively enforced differs from municipality to municipality. Coffee shop owners are required to check whether all those admitted to the shop, and allowed to purchase cannabis there, are residents of the Netherlands aged 18 years or older. They should check these facts, for instance, by asking the person to produce a valid identity document or residence permit, in combination with an extract from the municipal population register. It is against the law to grow marijuana and cannabis plants. In cases where no more than 5 plants are grown for personal consumption, the police will generally only seize the plants. If more than 5 plants are found, the Public Prosecution Service will prosecute. In combating cannabis growing, the police collaborate with organisations including housing associations, the Tax and Customs Administration, and energy companies. Tenants found to be growing cannabis may be evicted. The energy company will impose an additional retrospective assessment on those who illegally tap electricity. Toleration policy regarding soft drugs and coffee shops In the Netherlands, it is against the law to possess, sell or produce drugs.

How can I buy cocaine online in Zandam