The IGT is an executive functions task, which simulates real life decision making in the way that it factors reward and punishment (Bechara et al., 1994). Individuals choose between four decks of cards labeled A, B, C, and D, with the objective to win as much money as possible. In decks A and B (“disadvantageous decks”), choosing a card is followed by an immediately high gain of money, but at unpredictable trials the selection is followed by a high loss, leading to a net loss over time. In decks C and D (“advantageous decks”), the immediate gain is smaller, but the future loss is also smaller, leading to a net gain over time. Other versions of the IGT have been developed, where, for instance, the contingencies are reversed (Bechara et al., 2002).

Originally, findings on the IGT showed that patients suffering from lesions in the ventromedial prefrontal cortex (sometimes referred to as the orbitofrontal cortex) have a higher preference for immediate rewards despite negative future consequences (Bechara et al., 1994, 2000). These findings led to the suggestion that lesion patients suffer from insensitivity to future consequences. The findings of impaired decision-making in lesion patients were replicated in individuals suffering from substance use disorders, suggesting that these individuals prefer immediate rewards despite negative long-term consequences (Bechara et al., 2001; Bechara, 2003). The impairments were linked to prefrontal cortex dysfunctions, based on the evidence from lesion patients. The findings were later extended to gambling disorder, where gambling disorder sufferers show decision-making impairments similar to individuals suffering from substance use disorders (Grant et al., 2000; Petry, 2001; Cavedini et al., 2002; Goudriaan et al., 2005, 2006a; Linnet et al., 2006).

Linnet et al. (2006) investigated “chasing one's losses,” a key diagnostic symptom of gambling disorder. The authors compared 61 gambling disorder sufferers with 39 healthy controls. Gambling disorder sufferers were recruited through a treatment center, and healthy controls were selected from a pool of first-year psychology students. All participants completed a modified version of the IGT called the “Mouse Game” where individuals had to help a mouse gather cheese, rather than winning money. The contingencies were the same as the IGT, but units were converted into grams of cheese and the winning and losing sounds were removed, in order to reduce the association with gambling. The decks on the Mouse Game were stacked with 100 cards, such that participants could not deplete the decks during trials; the last 40 cards were added to the original 60-card stack on the IGT.

The study aimed at developing a quantifiable behavioral measure of chasing in a gambling situation where decision-making and skill would determine the outcome of the game. It was hypothesized that gambling disorder sufferers would have impaired IGT performance and increased episodic chasing (i.e., sequences of persistent poor choices leading to losses) compared with healthy controls, suggesting that they would be less likely to use negative feedback to change their behavior. To define chasing on the IGT, an index of behavior focused on choice sequences was compiled. Advantageous choice sequence was defined as five consecutive advantageous decisions (cards from deck C or D) and a disadvantageous choice sequence as five consecutive disadvantageous decisions (cards from deck A or B). The chance of choosing five consecutive good or bad cards at random is 2⁻⁵ = 0.03125 (p < 0.05).

The result showed that gambling disorder sufferers had significantly higher chasing on the IGT than healthy controls (df = 4, F = 3.61, p ≤ 0.01). The advantageous and disadvantageous chasing episodes were distributed evenly throughout the game. In other words, individuals did not solely have, e.g., advantageous decision-making sequences in the beginning of the game and disadvantageous sequences toward the end of the game. Rather, a pattern emerged for players with several behavior episodes in which both advantageous and disadvantageous decisions were present at the beginning of the game, developing into a “learning curve” of predominantly advantageous or disadvantageous sequences as the game unfolded. These results are consistent with the notion that gambling disorder sufferers are more impulsive and less likely to adopt a long term advantageous strategy, even in the face of negative feedback, than healthy controls. They are also consistent with the notion of reduced PFC functions and/or dopamine dysfunctions in the disorder.

Using drugs such as cocaine, amphetamine, and methamphetamine increases extracellular dopamine in the synaptic cleft, and binds more dopamine to the dopamine receptors of the synapses (Stahl, 2006). In healthy individuals increased dopamine binding to dopamine D_2/3 receptors is associated with a higher self-reported hedonic pleasure (Volkow et al., 2002a). The hedonic pleasure from drug liking is linked to two factors: (1) the baseline level of dopamine receptor availability before drug use; and (2) the change in dopamine receptor availability following drug use. Dopamine receptor availability is measured using, for instance, PET, where a radioactive ligand such as [¹¹C]raclopride is injected into the blood stream, and measured based on its binding properties. Raclopride binds to available dopamine D_2/3 receptors in the brain, and the raclopride binding potential is an index of dopamine receptor availability: (1)BPND=Bmax−BVdKd where Bmax is the maximum binding capacity of the receptors, B is the binding of the radioligand, V_d is the volume distribution, and K_d is the ligand's half-saturation concentration.

A higher baseline raclopride binding potential is interpreted as a higher number of dopamine receptors available for binding; a higher (positive) change in raclopride binding potential from a baseline to an experimental condition is interpreted as an increased release of dopamine because more dopamine is bound to the receptors in the experimental condition. Substance use disorders are associated with lower baseline dopamine receptor availability and reduced dopamine release from drug use.

The dopamine system is sensitive to behavioral stimulation related to monetary reward (Koepp et al., 1998; Breiter et al., 2001; Zald et al., 2004). For instance, Koepp et al. (1998) found that skilled video game players had significant dopamine release in the striatum when playing a video game for money.

Another line of evidence of the role of dopamine in gambling disorder comes from the literature on gambling disorder in Parkinson's disease sufferers in agonist treatment. Parkinson's disease sufferers, who are treated with dopamine agonists, have significantly higher prevalence of gambling disorder than individuals who receive other forms of treatment (Grosset et al., 2006; Lu et al., 2006; Weintraub et al., 2006). Agonist treatment is also associated with other impulse control disturbances such as hypersexuality, compulsive shopping, and compulsive eating (Steeves et al., 2009). These data suggest that certain changes to the dopamine system is associated with increased risk of addiction and impulse control disorders, including gambling disorder. While the dopaminergic mechanism behind the increased risk of gambling disorder is currently unknown, Steeves et al. (2009) found significant dopamine release in the ventral striatum of Parkinson's disease patients suffering from gambling disorder who gambled for money. Furthermore, de la Fuente-Fernandez et al. (2002) found significant dopamine release in the ventral striatum of Parkinson's patients expecting a drug reward in placebo trials. The authors concluded that the dopamine release was mediated by the expectation of reward. Unlike gambling disorder sufferers, Parkinson's disease sufferers in agonist treatment with gambling disorder have reduced binding potentials as a consequence of Parkinson's disease, and they therefore represent an atypical case of gambling disorder. For this reason the present review predominantly focuses on dopaminergic dysfunctions in gambling disorder without Parkinson's disease.

While use of substances such as cocaine is associated with dopamine release throughout the striatum, the ventral striatum is specifically involved in drug expectation and monitoring of reward (Delgado et al., 2000; de la Fuente-Fernandez et al., 2002), and this region appears to be central to gambling disorder and substance use disorder (Reuter et al., 2005; Abler et al., 2006; Linnet et al., 2010; 2011a,b). Evidence from the animal literature also supports the involvement of the ventral striatum in drug seeking and addictive behavior (Dalley et al., 2007; Uhl, 2007; Doya, 2008). Dopaminergic dysfunctions in the ventral striatum might therefore contribute to the decision making impairments on the IGT seen in gambling disorder. However, while substance use disorder and gambling disorder may share a common neurobiological basis, there might be differences in dopaminergic dysfunctions related to drug use and gambling.

The present review examines similarities and differences in dopaminergic dysfunctions between substance use disorder and gambling disorder based on a series of articles investigating the relation between dopaminergic neurotransmission and IGT performance in gambling disorder (Linnet et al., 2010, 2011a,b, 2012). In the study we scanned gambling disorder sufferers and healthy controls with PET using the radioligand [¹¹C]raclopride to measure dopaminergic neurotransmission during a baseline and a gambling condition of the IGT. In the baseline condition participants played a non-decision IGT similar to that of Bolla et al. (2003, 2004), where the computer automatically instructed the participants which cards to choose, and no winning or losing sounds were used; during the gambling scan participants chose freely between the decks, and received auditory feedback when winning or losing. Since each PET scan lasted 60 min, and it only takes ~20 min to administer the IGT, three versions of the IGT were used: the regular ABCD version, and subsequent KLMN and QRST versions, where the contingencies between decks become increasingly ambiguous. Raclopride binding potentials (BP_ND) and change in binding potential (ΔBP_ND) between baseline and gambling condition were recorded. Higher raclopride binding potentials (BP_ND) indicate a higher number of D_2/3 receptors available for dopamine binding. Decreased raclopride binding potentials from baseline to gambling condition indicate dopamine release because dopamine occupies more receptors during gambling and leaves fewer receptors available for raclopride binding. Raclopride binding potentials were measured using the ERLiBiRD method (Gjedde et al., 2005), and a ventral striatum mask using criteria similar to those of Mawlawi et al. (2001) was used to determine the anatomical location of the ventral striatum. Other masks were used for the putamen and caudate nucleus. The raclopride emission recordings were co-registered with structural MR images for each individual using MNI tools, and transformed into a common stereotaxic coordinate space (Talairach and Tournoux, 1988).

The study findings gave rise to the notion of the three “fallacies” of the role of dopamine in gambling disorders. Specifically, we found no support for the hypotheses that: (1) gambling disorder sufferers have lower baseline dopamine receptor availability; (2) gambling disorder sufferers have increased dopamine release when gambling; and (3) gambling disorder sufferers have increased dopamine release when winning.

Reward prediction error in the dopamine system refers to a mechanism that updates positive and negative reward predictions of a stimulus. The mechanism constitutes a neural correlate of the mathematical and behavioral Rescorla-Wagner learning rule (Schultz, 2006). For instance, in random binary outcome situations (e.g., reward vs. no-reward) the expected value (EV) is the average value that can be expected from a given stimulus, which is a linear function of reward probability (Figure 3A). In contrast, uncertainty, defined as the variance (σ²) of the probability distribution is the mean squared deviation from the expected value, which is an inverted quadratic function of reward probability (Schultz et al., 2008) (Figure 3B).

Midbrain and striatal dopamine coding of expected value and uncertainty follow linear and quadratic functions similar to their mathematical expressions (Fiorillo et al., 2003; Preuschoff et al., 2006; Schultz, 2006). Fiorillo et al. (2003) found distinct phasic and sustained midbrain activation toward reward probability in monkeys using electrophysiological measures of dopamine neurons in the ventral midbrain areas A8, A9, and A10. Phasic dopamine activation was larger in anticipation of stimuli with larger reward probability, and smaller in anticipation of stimuli with smaller reward probability. The sustained activation was largest toward stimuli with maximum uncertainty (P = 0.5) and declined toward higher and lower probabilities. The phasic and sustained activation patterns were distinct both in terms of timing of signal and dopamine neurons coding the response.

Preuschoff et al. (2006) found distinct neural coding of expected value and uncertainty in the ventral striatum of healthy men and women in a monetary card-guessing task. Expected value was linearly associated with early anticipatory blood oxygen level dependent (BOLD) activation, such that higher reward probabilities were associated with higher anticipatory BOLD activation, and lower reward probabilities were associated with lower anticipatory BOLD activation. In contrast, uncertainty showed an inverse quadratic association with late anticipatory BOLD activation, such that the highest BOLD activation was seen around maximum uncertainty (P = 0.5) and the lowest BOLD activation was seen around maximum certainty (P = 1.0 and P = 0.0).

Linnet et al. (2012) hypothesized that dopaminergic coding of outcome uncertainty on the IGT in gambling disorder would follow the reward prediction error signal, i.e., have the properties of an inverted U-shaped curve. The IGT consists of two “advantageous” and two “disadvantageous” decks that will lead to long-term gains and losses, respectively. The person is free to chose between decks, and the IGT performance can therefore be expressed as the probability (P) of advantageous deck selection, such that the variance is (1 − P)* P.

The results confirmed the hypothesis of a significant inverse quadratic relationship between dopamine release and IGT performance among gambling disorder sufferers, which was strongest in the combined striatum, F_{(2, 15)} = 9.28, p = 0.002 (see Figure 3C). The quadratic relationship between dopamine release and IGT performance did not reach significance level in the healthy control group.

These results have implications for the findings by Steeves et al. (2009) and Linnet et al. (2010). In the study by Steeves et al. (2009) the computer program used a random sequence generator to determine the card sequence, and the outcome was therefore random, or uncertain, even though it always resulted in an overall gain. It is therefore possible that the dopaminergic coding in gambling disorder was also related to the variance of the task and not solely to the overall gain. The findings by Linnet et al. (2010) that gambling disorder sufferers had increased dopamine release during periods of losing—not winning—could suggest that dopamine release reinforces the gambling behavior despite losses, and preclude the individual from inhibiting the gambling behavior in order to stop gambling or avoid further losses. Both studies can be explained in terms of dopaminergic coding of reward prediction and uncertainty.

Since variance is a common feature in all forms of gambling, and since uncertainty and variance is maximized in most forms of gambling, the dopaminergic response to maximum variance might reinforce the gambling behavior despite losses, and this might constitute a common underlying mechanism in gambling disorder. The odds structure in the most addictive forms of gambling are optimized toward maximum uncertainty and variance, where the payback percentage is around 80–99% (e.g., slot machines typically have payback rates of 82–90%, and black jack has payback rates as high as 99%). Since the odds only slightly favor the house, and the variance is maximized, these games provide the optimal conditions for dopaminergic coding of uncertainty and reinforcement of gambling behavior despite losses, which may underlie clinical behavior such as “chasing one's losses.”

From the perspective of gambling disorder, the outcome of winning or losing does not matter in the short term. What matters is that the game properties will always lead to losses in the long run, and the variance in outcome will always lead to dopaminergic reinforcement of the gambling behavior. This combination constitutes an inherent risk for gambling disorder sufferers and individuals at risk for developing gambling disorder.

Dopaminergic coding of reward prediction and uncertainty offers a model for explaining why: (1) gambling disorder sufferers are drawn toward the risk and uncertainty of gambling; (2) gambling disorder sufferers continue gambling despite losses; and (3) gambling disorder sufferers do not adapt an advantageous strategy despite negative feedback. At the same time it is clear that this model does not account for all behavior. For instance, our data are limited to PET and dopamine D2/3 receptors. While our findings are consistent with findings from fMRI studies (e.g., Preuschoff et al., 2006) the temporal resolution of PET does not allow us to differentiate between anticipation and outcome evaluation in gambling. Furthermore, it is possible that other dopamine receptors, e.g., D1-class receptors, might interact with- and contribute to the dopamine dysfunctions in gambling disorder. Finally, the IGT performance in healthy controls was not reinforced by dopaminergic coding of uncertainty. The following sections therefore addresses the possible differences of dopamine functions in IGT performance between gambling disorder sufferers and healthy controls.

To investigate adaptive learning functions of dopamine in IGT performance we (Linnet et al., 2011a) compared IGT performance in relation to dopamine release in the ventral striatum of 16 gambling disorder sufferers and 14 healthy controls. We used the regular ABCD version and the combined ABCD, KLMN and QRST versions, where group differences were measured as the average performance across the three different versions (ABCD + KLMN + QRST/3). The study compared overall group differences in IGT performance as well as group differences of IGT performance in relation to dopamine release in the ventral striatum.

A previous IGT study (Sevy et al., 2006) showed that pharmacological reduction of dopaminergic activity is associated with impaired IGT performance in healthy control volunteers, while increase of dopamine is associated with better IGT performance. We (Linnet et al., 2011a) therefore hypothesized that dopamine release in the ventral striatum would improve performance in healthy controls. Based on suggestions that risk and outcome uncertainty is associated with dopamine release in gambling disorder (Fiorillo et al., 2003), it was further hypothesized that dopamine release in the ventral striatum of gambling disorder sufferers would be associated with more risky decision-making, reflected in lower IGT performance.

The results showed that gambling disorder sufferers and healthy controls did not differ in IGT performance on the ABCD version or combined performance across the three tasks. However, when comparing IGT performance between gambling disorder sufferers and healthy controls dependent on dopamine release, a highly significant pattern emerged. Healthy controls with dopamine release in the ventral striatum had significantly higher IGT performance on the ABCD version than gambling disorder sufferers, F_{(4, 11)} = 14.40, p < 0.0005 (Figure 4A). In contrast, gambling disorder sufferers and healthy controls without dopamine release (dopamine inhibition) did not differ in IGT performance, F_{(4, 15)} = 1.78, ns (Figure 4B). Gambling disorder sufferers who released dopamine in the ventral striatum had significantly lower IGT performance than gambling disorder sufferers who did not release dopamine, F_{(4, 14)} = 8.25, p = 0.005, while healthy controls who released dopamine had significantly higher IGT performance than healthy controls who did not, F_{(4, 12)} = 4.85, p < 0.05.

The findings suggest that dopamine release was associated with adaptive behavior in healthy control individuals, but maladaptive behavior in gambling disorder sufferers. This might suggest that the function of dopamine differed between the two groups. Among gambling disorder sufferers the dopamine function appears to code uncertainty and reinforce risky and disadvantageous decision making. Among healthy controls the dopamine function appears to code outcome and reinforce adaptive and advantageous decision making. The dopamine dysfunctions and maladaptive gambling behavior in gambling disorder could further be fueled by the subjective experience of gambling. To address this aspect, the levels of gambling excitement were investigated.

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.