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. Author manuscript; available in PMC: 2021 Apr 20.
Published in final edited form as: Prog Neuropsychopharmacol Biol Psychiatry. 2020 Jan 15;99:109864. doi: 10.1016/j.pnpbp.2020.109864

Maladaptive consequences of repeated intermittent exposure to uncertainty

Paola Mascia 1, Qiang Wang 1, Jason Brown 1, Kathryn M Nesbitt 2, Robert T Kennedy 3, Paul Vezina 1
PMCID: PMC7107980  NIHMSID: NIHMS1553929  PMID: 31952958

Abstract

Recently we reported that nucleus accumbens (NAcc) dopamine (DA) tracks uncertainty during operant responding for non-caloric saccharin. We also showed that repeated intermittent exposure to this uncertainty, like exposure to drugs of abuse, leads to sensitization of the locomotor and NAcc DA effects of amphetamine and promotes the subsequent self-administration of the drug. Here we review these findings together with others showing that NAcc glutamate signaling is similarly affected by uncertainty. Extracellular levels of glutamate in this site also track uncertainty in a task in which nose poking for saccharin on an escalating variable ratio schedule of reinforcement is associated with progressively increasing variance between performance of the operant and payout. Furthermore, sensitized behavioral responding to and for amphetamine following exposure to uncertainty is accompanied by increased levels of Ca2+/calmodulin-dependent protein kinase II (CaMKII) and protein kinase C (PKC) phosphorylation as well as altered protein levels of the transcription factor ΔFosB (increased) and glutamate transporter 1 (GLT1; decreased) in NAcc tissues. Notably, phosphorylation by CaMKII and PKC regulates AMPA receptor trafficking and function in this site, is elevated following psychostimulant exposure, and is necessary for the expression of enhanced drug taking. Increased ΔFosB and decreased GLT1 levels are observed following psychostimulant exposure, are associated with increased drug taking and seeking, and are known to modulate AMPA receptors and extracellular glutamate levels respectively. These adaptations in glutamate transmission as well as those observed with DA following repeated intermittent exposure to uncertainty are similar to those produced by exposure to abused drugs. Together, they point to the recruitment of both DA and glutamate signaling pathways in the NAcc in both drug and behavioral addictions. As uncertainty is central to games of chance, these findings have particular relevance for gambling disorders known to exhibit comorbidity with drug abuse.

Keywords: amphetamine, dopamine, gambling, glutamate, sensitization, uncertainty

1. Introduction

The last ten to fifteen years have witnessed a growing interest in potential commonalities between gambling and substance use disorders, an interest recently formalized by the reclassification of gambling disorders alongside substance use disorders in the fifth edition of the Diagnostic and Statistical Manual (DSM-5; APA, 2013). In this review, we examine these commonalities by focusing on the behavioral and neurobiological consequences of exposure either to abused psychostimulant drugs or operant uncertainty, a central feature of games of chance. A number of similarities are reviewed including neuroadaptations in dopamine (DA) overflow both during and following exposure to drugs or conditions of uncertainty. We also report new previously unpublished findings indicating that glutamate signaling is similarly affected. Given known DA-glutamate interactions in mesolimbic brain regions and their importance for the generation of motivated behaviors, these findings point to a novel common pathway to drug and behavioral addictions involving the joint participation of brain DA and glutamate signaling pathways.

2. Consequences of repeated intermittent exposure to abused drugs

Repeated exposure to abused drugs has consequences. For example, stimulant drugs like amphetamine and cocaine acutely increase DA overflow in the nucleus accumbens (NAcc), increase locomotor activity, and are readily self-administered by animals and humans. Repeated intermittent exposure to these drugs, whether passively administered or actively self-administered, leads to sensitization of these effects. Thus, a challenge drug injection now produces even greater elevations in NAcc DA overflow and a greater locomotor response. Further, if the opportunity is offered to self-administer the drug, more work is emitted to obtain it and as a result higher drug intake is observed than in animals not previously sensitized (Kalivas and Stewart, 1991; Vezina et al., 2002; Vezina, 2004; Kawa et al., 2016, 2019). These findings support theories of drug addiction positing that sensitization of midbrain DA neuron reactivity drives the transition from casual drug use to drug abuse in vulnerable individuals (Leyton and Vezina, 2013, 2014) by sensitizing the incentive properties of abused drugs as well as those of stimuli associated with them (Robinson and Berridge, 1993, 2008).

2.1. Consequences for NAcc glutamate signaling

Known DA-glutamate interactions in the cell body and terminal regions of brain DA systems have also led to a greater appreciation of the role played by brain glutamate in the expression of sensitization by psychostimulant drugs (Wolf, 1998; Vanderschuren and Kalivas, 2000). Beyond enhanced drug-induced increases in NAcc DA and glutamate overflow (Pierce et al., 1996; Kim et al., 2005), however, a number of additional long-lasting adaptations in glutamate signaling have also been described in the NAcc following drug exposure.

These adaptations include the functional upregulation of AMPA receptors (Suto et al., 2004). This upregulation has been argued to stem from at least two different signaling cascades to promote AMPA receptor membrane insertion and increase conductance. In one case, prolonged withdrawal from cocaine increases mGluR1-dependent formation of calcium permeable AMPA receptors leading to increased reactivity of neurons in the NAcc to drug-related cues (Conrad et al., 2008; Loweth et al., 2014). In another, repeated exposure to amphetamine increases DA receptor-dependent (Rashid et al., 2007; Anderson et al., 2008; Medvedev et al., 2013) phosphorylation of the AMPA receptor GluA1 subunit by calcium/calmodulin-dependent protein kinase II (CaMKII) and protein kinase C (PKC) (Lin et al., 2009; Loweth et al., 2010, 2013; Vezina et al., 2017). In the latter case, both CaMKII and PKC phosphorylation of GluA1 residues is necessary for the expression of sensitized locomotion and drug self-administration by psychostimulants (Pierce et al., 1998; Loweth et al., 2008, 2010, 2013; Vezina et al., 2017).

Exposure to many drugs of abuse, including psychostimulants, increases protein levels of the transcription factor ΔFosB in the NAcc, an effect also linked to the expression of sensitized locomotor responding to these drugs as well as to their enhanced self-administration (Kelz et al., 1999; Colby et al., 2003; Singer et al., 2016). Elevated ΔFosB levels can regulate AMPA receptor mediated glutamatergic transmission indirectly by upregulating transcription of CaMKII (Robison et al., 2013) or by directly inducing transcription of the GluA2 AMPA receptor subunit which has been associated with enhanced reward (Kelz et al., 1999; Todtenkopf et al., 2006).

Decreased protein levels of glutamate transporter 1 (GLT1) have also been reported in the NAcc following repeated exposure to cocaine (Knackstedt et al., 2010). These have been proposed to reflect, with corresponding decreases in cysteine-glutamate exchange (Baker et al., 2003), impaired extracellular glutamate homeostasis that, by decreasing basal extracellular glutamate levels and permitting enhanced drug-evoked glutamate overflow, enable reinstatement of cocaine seeking (Kalivas, 2009). By restoring levels of GLT1 and cystine-glutamate exchange, these effects are reversed and reinstatement is prevented (Baker et al., 2003; Knackstedt et al., 2010).

While not exhaustive, these findings indicate that there are long-lasting consequences of repeated exposure to drugs of abuse for glutamate signaling that, with sensitized DA neurotransmission, can increase and maintain their pursuit and self-administration.

3. Consequences of repeated intermittent exposure to uncertainty

The reclassification of gambling disorders alongside substance use disorders in the fifth edition of the Diagnostic and Statistical Manual (DSM-5; APA, 2013) recognized not only the immense cost to individuals and societies of behavioral addictions (Yau and Potenza, 2015) but also a growing appreciation of the similarities between the two. According to this classification, both gambling and substance use disorders are associated with loss of control, progressive compulsion, and continued use despite harmful consequences. Not surprisingly, comorbidity between the two is common (Grant and Chamberlain, 2019, present issue). For example, alcohol- and cocaine-dependent individuals are more likely to suffer from gambling disorder than would be expected in the general population (Hall et al., 2000; Baldo et al., 2006). Conversely, pathological gamblers show rates of alcohol and other drug problems 4–7 times higher than nongamblers or recreational gamblers (Grant and Chamberlain, 2019, present issue).

3.1. NAcc DA and behavior

Perhaps the most compelling data aligning these two disorders comes from clinical and pre-clinical studies indicating common neuronal substrates. Focusing on brain DA systems associated with motivation for drug taking, human imaging studies have consistently reported neuronal activation in mid-brain DA cell body regions as well as their subcortical forebrain terminal projection fields during unpredictable reward gambling tasks (Elliot et al., 2003; D’Ardenne et al., 2008; Linnet et al., 2011). Amphetamine, with well characterized DA releasing properties, increases motivation to gamble (Zack and Poulos, 2004) and produces enhanced striatal DA release in pathological gamblers (Boileau et al., 2014). As uncertainty of outcome is central to the ability of games of chance to maintain engagement and pursuit (Costikyan, 2013), the latter finding in particular suggests that the effects of exposure to conditions of uncertainty can cross-sensitize to those of abused drugs like amphetamine, as argued earlier (Zack and Poulos, 2009; Thomsen et al., 2014). It is also consistent with the argument that uncertainty in itself possesses reinforcing properties that can promote gambling (Clark et al., 2019) and provides a DA sensitization mechanism for escalation of the behavior to gambling disorder. Different models have proposed that DA release, evoked either phasically by uncertain reward delivery (reward prediction error) or tonically by the prediction of uncertainty, or both, may provide the reinforcement signal leading to the incentive draw of cues associated with the risk and uncertainty of gambling (Clark et al., 2019; Linnet, 2019, present issue; see Section 4 below).

These possibilities led a number of pre-clinical studies to more directly explore whether exposure to repeated intermittent uncertainty can produce behavioral and neurochemical adaptations similar to those normally observed following exposure to psychostimulant drugs. Indeed, recent studies have demonstrated that prior exposure to conditions of uncertainty in fact leads to enhanced locomotor responding to amphetamine (Singer et al., 2012; Zack et al., 2014; Zeeb et al., 2017).

More recently, Mascia et al. (2019) replicated these findings in experiments manipulating uncertainty by exposing rats to either uncertain saccharin reinforcement under variable ratio (VR) schedules of reinforcement or certain reinforcement under fixed ratio (FR) schedules (see Section 4 below for a more detailed discussion of these methods). In tests conducted two to three weeks later, they showed that prior exposure to uncertainty not only sensitized the locomotor response to amphetamine but also enhanced amphetamine-induced NAcc DA overflow as well as work output directed at self-administering the drug (Figure 1). All three effects are identical to those observed in animals previously exposed to amphetamine (Vezina, 2004) and demonstrate direct effects of exposure to uncertainty. The direct effect on enhanced amphetamine-induced NAcc DA overflow of prior exposure to uncertainty is important because the previous demonstration of enhanced striatal DA release following amphetamine in human pathological gamblers (Boileau et al., 2014) could not distinguish whether the effect was present before the diagnosis of gambling disorder or was due to exposure to the prolonged experience of gambling in these individuals (Thomsen et al., 2014). The evidence for cross-sensitization between the effects of uncertainty and those of psychostimulant drugs appears to be bi-directional. Thus, in addition to the above findings, prior exposure to uncertainty also increases risky decision-making in a rodent gambling task that models deficiencies in decision-making common to both gambling and substance use disorders (Zeeb et al., 2017). Conversely, prior exposure to psychostimulants leads to enhanced responding to and for amphetamine (Vezina, 2004) and increased risky decision-making (Kim et al., 2017). Noting that the incentive salience of normally unattractive and conditioned cues is enhanced by uncertainty (Anselme et al., 2013; Robinson et al., 2014, 2015), Mascia et al. (2019) argued that the above findings together support a novel unified pathway to addiction in which incentive sensitization drives the excessive work output and intake observed in both drug and behavioral addictions such as gambling disorder.

Figure 1.

Figure 1.

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Animals previously exposed to conditions of Uncertain saccharin reinforcement under VR schedules show enhanced locomotor (A) and NAcc DA (B) responding to a challenge injection of amphetamine (arrow at abscissa), as well as enhanced work output and self-administration of the drug (C) compared to rats previously exposed to Certain reinforcement under FR schedules. Numbers in parentheses indicate n/group. *, p<0.05, **, p<0.01, compared to Certain at specified time. Adapted from Mascia et al. (2019).

The above behavioral consequences of exposure to uncertainty and their resemblance to those produced by exposure to drugs of abuse has led in turn to investigations of the neurochemical adaptations produced. The finding that NAcc DA overflow is enhanced following exposure to either uncertainty or amphetamine is significant in establishing a common neuronal substrate between the two exposure regimens. However, it needs to be extended to other neuronal systems known to contribute to the expression of sensitization. As described above, brain glutamate provides an important target for investigation.

3.2. NAcc glutamate signaling

While the consequences of exposure to uncertainty on drug-induced NAcc glutamate overflow have yet to be assessed, new findings obtained by us and described below show significant effects of this exposure regimen on glutamate signaling. In the course of conducting their experiments, Mascia et al. (2019) also trained a subset of Long-Evans rats to nose-poke for saccharin under the escalating VR or FR schedules of reinforcement, ultimately to maintain this operant responding under the VR20 (exposure to uncertain conditions; n=6) or FR20 (exposure to conditions of certainty; n=5) schedules for close to 25 sessions (see Section 4 below for a more detailed discussion of these methods). Two weeks later, these rats were sacrificed and NAcc tissues prepared for Western blot assays to test for changes in CaMKII and PKC phosphorylation as well as protein levels of ΔFosB and GLT1. NAcc core and shell tissues were harvested and subjected to immunoblotting using methods described in Wang et al. (2017). NAcc shell tissues were assayed for CaMKII, PKC, and ΔFosB, while NAcc core tissues were assayed for GLT1 as robust effects have been described following drug exposure in these subregions for these molecules (Knackstedt et al., 2010; Loweth et al., 2010; Robison et al., 2013; Vezina et al., 2017). Tissues were incubated overnight in primary antibody [GluA1, 1:500; pGluA1(S831), 1:500 (GluA1-CaMKII substrate); Ng, 1:5000; pNg(S36), 1:1000 (neurogranin-PKC substrate); ΔFosB, 1:1000; GLT1, 1:1000; tubulin, 1:100,000] followed by an HRP-conjugated secondary antibody. Protein bands were visualized using a chemiluminescence detection system and protein levels analyzed using independent t-tests. Technical problems during immunoblotting led to slightly lower n/group for ΔFosB and GLT1.

These additional previously unpublished experiments allowed us to further assess changes in glutamate signaling following exposure to uncertainty. As reviewed above, phosphorylation by CaMKII and PKC of residues on the GluA1 subunit regulates AMPA receptor trafficking and function in the NAcc, is enhanced following exposure to psychostimulants, and is necessary for expression of sensitized amphetamine-induced locomotion and enhanced self-administration of the drug. Similarly, increased ΔFosB and decreased GLT1 protein levels are observed following psychostimulant exposure, modulate AMPA receptors and extracellular glutamate levels, respectively, and are associated with increased drug taking and seeking. As illustrated in Figure 2, prior exposure to uncertainty led to long-lasting (2 weeks) effects. When compared to animals previously exposed to conditions of certain reinforcement, rats previously exposed to conditions of uncertainty showed significant increases in phosphorylation by CaMKII (t9=2.91, p<0.01) and PKC (t9=1.95, p<0.05) as well as significant increases in ΔFosB (t7=2.66, p<0.05) and decreases in GLT1 (t8=2.36, p<0.05) protein levels. These effects again are identical to those observed in animals previously exposed to psychostimulant drugs, they extend the findings showing enhanced drug-induced DA overflow, and provide additional support for the idea that exposure to uncertainty and exposure to drugs of abuse have common important consequences for both DA and glutamate signaling that could enable the escalation and maintenance of drug as well as behavioral addictions.

Figure 2.

Figure 2.

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Animals previously exposed to conditions of Uncertain saccharin reinforcement under VR schedules show increased levels of phosphorylation by CaMKII [pGluA1(S831)] (A) and PKC [pNg(S31)] (B) as well as increased protein levels of ΔFosB (C) and decreased protein levels of GLT1 (D) compared to rats previously exposed to Certain reinforcement under FR schedules. These adaptations observed in the NAcc are similar to those observed in animals previously exposed to psychostimulant drugs and are known to modulate AMPA receptor function (A-C) as well as extracellular levels of glutamate (D). NAcc tissues were harvested two weeks following the last saccharin exposure session. Data are shown as group mean (+SEM) % of Certain and normalized to phosphorylation substrate or tubulin as indicated. Numbers in parentheses indicate n/group. *, p<0.05, **, p<0.01, Uncertain vs Certain.

4. Exposure to uncertainty

In the four preclinical studies described above that investigated the effects of exposure to uncertainty, one used a Pavlovian approach to expose animals to conditioned stimuli that predicted reward with different probabilities (Zack et al. 2014) and three used an operant approach that exposed animals to escalating fixed (FR) or variable (VR) ratios of reinforcement to expose animals to certain (FR) and uncertain (VR) conditions of reward delivery (Singer et al., 2012; Zeeb et al., 2017; Mascia et al., 2019). All were fundamentally influenced by the work of Schultz and his colleagues.

4.1. Characterizing uncertainty using a Pavlovian approach: DA

In their seminal report using a Pavlovian approach in well trained monkeys, Fiorillo et al. (2003) showed that phasic midbrain DA neuron responses to conditioned stimuli increased linearly as a function of the probability of reward they predicted, a finding consistent with a linear relationship between expected reward and probability of reward (Figure 3A; dashed line). In these experiments, this relationship was established and maintained by the teaching signal afforded by reward prediction error over thousands of stimulus-reward parings. More germane to the present discussion, however, Fiorillo et al. (2003) also reported the additional finding that sustained tonic DA neuron activation in the period between presentation of the conditioned stimulus and potential reward increased as a function of the uncertainty predicted by the stimulus (Figure 3B). Thus, stimuli predicting a reward probability (p) of 0 or p=1 are associated with no uncertainty and produced little DA activation, those predicting p=0.25 or p=0.75 are associated with greater uncertainty and produced increasing DA activation, and those predicting p=0.5 are associated with maximal uncertainty and produced the greatest DA activation. As variance provides a measure of uncertainty (Schultz et al., 2008), the resulting inverted U function between uncertainty and probability of reinforcement can be determined by

variance=(1−P)P

where P is the probability of reinforcement predicted by the different stimuli (Figure 3A; solid curve). The inverted U function between DA and reinforcement probability has been demonstrated with different technologies using vastly different timescales, ranging from seconds in the case of single unit recordings (Fiorillo et al., 2013), BOLD measurements in human fMRI (Preuschoff et al., 2006), and voltammetric assessments of NAcc DA release (Hart et al., 2015) to minutes in the case of human PET studies estimating ventral striatal DA release (Linnet et al., 2012). Together, these studies indicate that brain DA signaling can track uncertainty over a wide temporal range.

Figure 3.

Figure 3.

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(A) Expected reinforcement (dashed line) and uncertainty (solid curve) as a function of the probability of reinforcement in a Pavlovian approach. Adapted from Schultz et al. (2008) where uncertainty as used here is labelled risk, denoting the degree of uncertainty inherent in known probability distributions that can be expressed as variance. (B) Median sustained activation of DA neurons as a function of reinforcement probability, indicating that DA tracks uncertainty according to the inverted U function outlined in (A). Adapted from Fiorillo et al. (2003).

4.2. Characterizing uncertainty using an operant approach: NAcc DA

As indicated earlier, a number of preclinical studies have used an operant approach to expose rats to uncertainty. This approach referred to above was characterized by Mascia et al. (2019) to reveal that it too supports a similar relationship between sustained DA activation and uncertainty. Noting that an earlier PET study in humans found that performance on a VR schedule of reinforcement significantly increased brain striatal DA release (Zald, 2004), they trained rats to nose-poke for non-caloric saccharin under either FR schedules (certain conditions of reinforcement) or VR schedules (uncertain conditions of reinforcement) for 55 1-hour sessions. Ratios were escalated from FR/VR1 to FR/VR20 (1, 2, 3, 5, 7, 10, 13, 16, 19, 20) with rats ultimately self-administering saccharin under FR20 or VR20 schedules for close to 25 sessions. These sessions constituted the period of prolonged intermittent exposure to certain (FR) or uncertain (VR) conditions in their experiments. As variance, a measure of uncertainty, reflects the deviation of a distribution from the mean, values could be determined by

variance=Σ(x−x¯)2/N

where x is a data point in the distribution (here, the number of nose-pokes required to obtain a particular reinforcer), x¯ is the average number of nose-pokes required to obtain a reinforcer in the distribution, and N is the number of data points in the distribution, to provide an operant uncertainty index for each of the FR and VR ratios used (operant variance in Figure 4A). As can be seen, a constant variance of 0 is associated with the different escalating FR schedules as these all program a fixed certain relationship between nose-pokes and saccharin reinforcement regardless of the ratio level. Conversely, the different escalating VR schedules program an increasingly variable relationship between nose-pokes and payout and are thus associated with exponentially increasing variance (and uncertainty). In a manner paralleling the findings of Fiorillo et al. (2003) but now in an operant framework, Mascia et al. (2019) also found that NAcc DA overflow measured during operant responding for saccharin under the different reinforcement ratios and averaged throughout the sessions, tracked this measure of uncertainty (Figure 4B).

Figure 4.

Figure 4.

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NAcc DA overflow tracks uncertainty in an operant approach. (A) Mathematically derived curves of the variance associated with increasing FR and VR schedules of reinforcement. Variance (a measure of uncertainty) increases exponentially with the increasing VR schedules as these program an increasingly variable relationship between performance of an operant and payout. The variance associated with the different escalating FR schedules remains at 0 as these program a fixed relationship. (B) The patterns of DA overflow assessed in the NAcc with the different schedules showed a notable similarity to the exponential uncertainty (VR) and flat certainty (FR) curves in (A). From Mascia et al. (2019). n/group=4–8. ***, p<0.001, VR compared to FR at the specified ratios.

4.3. NAcc glutamate overflow during operant uncertainty

In order to determine whether the ability of NAcc DA to track uncertainty in this operant approach extended to glutamate and possibly other neurotransmitters in the NAcc, the HPLC-MS/MS data set collected by Mascia et al. (2019) was further analyzed to yield the additional previously unpublished results shown in Figure 5. HPLC-MS/MS was performed as described in Wong et al. (2016). Results were analyzed by between-groups ANOVA followed by post hoc Scheffé tests as described in Mascia et al. (2019).

Figure 5.

Figure 5.

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Non-DA compounds measured in the NAcc during exposure to uncertainty. Of the several compounds assessed in addition to DA following further analyses of the HPLC-MS/MS results obtained in Mascia et al. (2019), only glutamate (G) and the related excitatory amino acid aspartic acid (C) similarly tracked uncertainty. The extra-synaptically originating modulator adenosine (B) displayed a weaker but significant increase with increasing uncertainty. 5-HT and norepinephrine levels were too low to permit reliable measurement (see text). Data illustration and group affiliation [FR, open circles (Certain conditions); VR, filled circles (Uncertain conditions)] as in Figure 4. n/group=4–8. *, p<0.05, VR compared to FR at the specified ratios.

Remarkably, these further analyses revealed that NAcc glutamate overflow similarly tracked uncertainty in these experiments (Figure 5G). The ANOVA comparing the certain (FR) and uncertain (VR) conditions revealed a significant effect of groups (F1,28=5.13, p<0.05). At ratios 19–20, VR rats showed a 90% increase in glutamate overflow compared to FR rats (p<0.05). As with DA, glutamate levels increased exponentially with increasing VR schedules associated with increasing variance and uncertainty but remained at baseline even with increasing FR schedules. Importantly, these effects observed with DA and glutamate were specific to the variance of the scheduled ratios as they were not associated with group differences in emission of behavior or reinforcements obtained in the sessions. In addition, greater than baseline DA and glutamate overflow was observed in the NAcc throughout the 1-hour sessions, mimicking the time scale of the effects of amphetamine and cocaine in this site (Pierce et al., 1996; Kim et al., 2005) and rendering them amenable to detection in the microdialysis samples collected every two minutes in these experiments.

These results again show that exposure to uncertainty produces neuroadaptations in DA and glutamate signaling both during and following exposure. Indeed, the behavioral and neurochemical consequences of exposure to uncertainty may stem from its ability to mimic the effects of abused drugs on brain DA and glutamate signaling during exposure. This is consistent with a distinct role for tonic signaling by these neurotransmitters in the production of motivational states rather than learning (Cagniard et al., 2006) and the enhancement of these states following repeated intermittent exposure. Together, these findings point to a novel common pathway to drug and behavioral addictions.

It was recently reported that exposure to a gambling-like reward schedule failed to produce addiction-like symptoms in rats (Laskowski et al., 2019). However, as proposed by these authors, it is possible that the exposure to uncertainty phase in their experiments was not sufficiently long. Indeed, in pilot experiments performed by Singer et al. (2012), the magnitude of amphetamine-induced locomotor sensitization they observed was sensitive to the duration of the exposure to uncertainty phase. They found that while 55 sessions produced sensitization [FR (1543.22±98.78) vs VR (2231.52±110.09), t9=3.01, p<0.01; 3-hour total locomotor counts in response to 0.5 mg/kg amphetamine], as little as 12 sessions less (43) failed to do so [FR (1227.28±204.93) vs VR (1651.40±308.63), t10=1.41, ns].

The effects observed with DA and glutamate were selective as analyses of the other compounds detected by HPLC-MS/MS (neurotransmitters, neuromodulators, essential and non-essential amino acids) revealed mostly baseline levels with increasing ratios, independent of certain or uncertain condition (Figure 5). In addition to glutamate, only two other non-DA compounds appeared to track uncertainty: the glutamate related excitatory amino acid aspartic acid (Figure 5C) and the extra-synaptically originating modulator adenosine (Figure 5B). The ANOVA comparing the certain (FR) and uncertain (VR) conditions revealed significant effects of groups for both aspartic acid (F1,28=7.69, p<0.01) and adenosine (F1,28=5.75, p<0.05). VR rats achieved a 97% increase in aspartic acid overflow (p<0.05) and a more modest 52% increase in adenosine overflow (p<0.05) relative to FR rats at ratios 19–20.

While questions remain about the neurotransmitter role and autonomous glutamate-independent release of aspartic acid, or in the ionic form aspartate (Cavallero et al., 2009), a number of studies support a role for it in psychostimulant sensitization. For example, cocaine acutely increases extracellular levels in the NAcc not only of glutamate but of aspartate as well (Smith et al., 1995) and these are enhanced after exposure to repeated cocaine (Robinson et al., 1997). In addition, noting that aspartate is an agonist of NMDA receptors, others have shown that activation of these receptors is required in the NAcc for amphetamine sensitization (Degoulet et al., 2013; Beutler et al., 2011; cf, Vezina and Queen, 2000). Thus, like glutamate, aspartic acid may initiate neuroadaptations during exposure that ultimately lead to sensitized responding.

Adenosine displayed a weaker though significant increase that may have stemmed from the breakdown of its tri-phosphorylated form (ATP) originating in turn from the increased release of DA and glutamate into the NAcc. Similar compensatory increases in adenosine A2A receptors have been described in this site following extended cocaine self-administration (Marcellino et al., 2007). Consistent with these observations, stimulation of adenosine A2A receptors prevents the induction and expression of locomotor sensitization by cocaine (Filip et al., 2006).

5. Current limitations and future directions

Importantly, in the Mascia et al. (2019) HPLC-MS/MS data set discussed above, 5-HT and norepinephrine failed to yield consistently detectible levels that could be measured reliably. As microdialysis was performed in the NAcc core subregion in these experiments, this outcome is consistent with the weaker noradrenergic and serotonergic innervation of this site relative to the NAcc shell (Van Bockstaele and Pickel, 1993; Van Bockstaele et al., 1996; Mitrano et al., 2012). Given that systemically administered antagonists for noradrenaline (Marshall et al., 2016) and serotonin receptors (Zeeb et al., 2009) have been shown to modulate responding on tasks performed under conditions of uncertainty, the above limitations underscore the need to investigate the contribution of other neurotransmitters and other sites. This is particularly pertinent for glutamate and related excitatory amino acids that are known to send projections to the cell body and terminal fields of the ascending mesencephalic DA systems from prefrontal cortex as well as limbic and pontine structures like the hippocampus, amygdala, and the laterodorsal and pedunculopontine tegmental nuclei (Christie et al., 1987; Meredith et al., 1993; Steidl et al., 2017). Some of these have been implicated in the effects of uncertainty (St. Onge et al., 2012; van Holstein et al., 2019, present issue). Together with the finding that NAcc glutamate overflow tracks uncertainty, changes in glutamate afferentation and regulation of midbrain DA neurons may help decipher how these neurons (and perhaps other neuronal systems) encode both reward value prediction and error as well as uncertainty, as proposed by Schultz et al. (2008).

Finally, gambling is a complex activity that incorporates a number of features including absence of gain, loss chasing, risk of loss, and loss of resources (see Zeeb et al., 2017, and references therein). While the operant approaches described above sought to isolate one of the critical features of gambling (temporal uncertainty of reinforcement delivery; Costikyan, 2013), it will be important to investigate whether and how these components might contribute to adaptations in the signaling of DA, glutamate, and other neuronal systems (e.g., Zack et al., 2019, present issue). This, together with assessments of different neurotransmitters and different nuclei, may help us better understand both drug and behavioral addictions and thus better inform the development of successful therapeutic interventions (Pettorruso et al., 2014).

6. Summary

Here we reviewed published findings and reported new results showing that exposure to conditions of uncertainty, a feature central to games of chance, produces behavioral and neurobiological adaptations similar to those produced by exposure to abused psychostimulant drugs. In particular, prior exposure to either drugs or operant uncertainty leads to sensitized locomotor responding to amphetamine, enhanced self-administration of the drug, and similar adaptations in DA and glutamate signaling in the forebrain NAcc. In addition, DA and glutamate overflow in the NAcc both track uncertainty in an operant task designed to manipulate it, thereby mimicking the acute effects of psychostimulants in this site during exposure. Together, these findings point to a novel common pathway to drug and behavioral addictions. Accordingly, DA and glutamate signaling pathways are recruited during exposure and consequential changes in DA and glutamate signaling are manifested following exposure thereby supporting the maladaptive expression of motivated behaviors.

Highlights.

  • Exposure to uncertainty leads to changes in brain dopamine and glutamate signaling

  • These adaptations are the same as those produced by exposure to psychostimulant drugs

  • Forebrain dopamine and glutamate track uncertainty during operant responding

  • These findings point to a novel common pathway to drug and behavioral addictions

  • It involves aberrant dopamine and glutamate signaling during and after exposure

Acknowledgements:

This work was supported by National Institutes of Health (NIH) grants to RTK (EB003320) and PV (DA034184, DA09397). Support was also provided by NIH T32 grant DA007268 (KMN).

Abbreviations:

ACh

acetylcholine

AMPA

a-amino-3-hydroxy-5-methylisoxazole-4-propionic acid

ANOVA

analysis of variance

CaMKII

Ca2+/calmodulin-dependent protein kinase II

DA

dopamine

FR

fixed ratio

GABA

g-aminobutyric acid

GLT1

glutamate transporter 1

HPLC-MS/MS

high performance liquid chromatography – tandem mass spectrometry

HRP

horseradish peroxidase

NAcc

nucleus accumbens

PKC

protein kinase C

VR

variable ratio

Footnotes

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Competing interests: The authors report no conflicts of interest.

Declaration of interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

  1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th edition Arlington, VA: American Psychiatric Publishing, 2013. [Google Scholar]
  2. Anderson SM, Famous KR, Sadri-Vakili G, Kumeresan V, Schmidt HD, Bass CE, Terwilliger EF, Cha J-HJ, Pierce RC. CaMKII: A biochemical bridge linking accumbens dopamine and glutamate systems in cocaine seeking. Nature Neurosci 2008; 11: 344–353. [DOI] [PubMed] [Google Scholar]
  3. Anselme P, Robinson MJF, Berridge KC. Reward uncertainty enhances incentive salience attribution as sign-tracking. Behav Brain Res 2013; 238: 53–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Baker DA, McFarland K, Lake RW, Shen H, Tang X-C, Toda S, Kalivas PW. Neuroadaptations in cystine-glutamate exchange underlie cocaine relapse. Nature Neurosci 2003; 6: 743–749. [DOI] [PubMed] [Google Scholar]
  5. Baldo V, Cristofoletti M, Majori S, Cibin M, Peron C, Dal Zotto A, Zampieri N, Saia M, Trivello R. Ann Ig 2006; 18: 147–153. [PubMed] [Google Scholar]
  6. Beutler LR, Wanat MJ, Quintana A, Sanz E, Bamford NS, Zweifel LS, Palmiter RD. Balanced NMDA receptor activity in dopamine D1 receptor (D1R)- and D2R-expressing medium spiny neurons is required for amphetamine sensitization. PNAS 2011; 108: 4206–4211. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Boileau I, Payer D, Chugani B, Lobo DSS, Houle S, Wilson AA, Warsh J, Kish SJ, Zack M. In vivo evidence for greater amphetamine-induced dopamine release in pathological gambling: A positron emission tomography study with [11C]-(+)-PHNO. Mol Psychi 2014; 19: 1305–1313. [DOI] [PubMed] [Google Scholar]
  8. Cagniard B, Beeler JA, Britt JP, McGehee DS, Marinelli M, Zhuang X. Dopamine scales performance in the absence of new learning. Neuron 2006; 51: 541–547. [DOI] [PubMed] [Google Scholar]
  9. Cavallero A, Marte A, Fedele E. L-Aspartate as an amino acid neurotransmitter: Mechanisms of the depolarization-induced release from cerebrocortical synaptosomes. J Neurochem 2009; 110: 924–934. [DOI] [PubMed] [Google Scholar]
  10. Christie MJ, Summers RJ, Stephenson JA, Cook CJ, Beart PM. Excitatory amino acid projections to the nucleus accumbens septi in the rat: a retrograde transport study utilizing D[3H]aspartate and [3H]GABA. Neurosci 1987; 22: 425–439. [DOI] [PubMed] [Google Scholar]
  11. Clark l, Boileau I, Zack M. Neuroimaging of reward mechanisms in gambling disorder: An integrative review. Mol Psychi 2019; 24: 674–693. [DOI] [PubMed] [Google Scholar]
  12. Colby CR, Whisler K, Steffen C, Nestler EJ, Self DW. Striatal cell type-specific overexpression of ΔFosB enhances incentive for cocaine. J Neurosci 2003; 23: 2488–2493. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Conrad KL, Tseng KY, Uejima JL, Reimers JM, Heng L-J, Shaham Y, Marinelli M, Wolf ME. Formation of accumbens GluR2-lacking AMPA receptors mediates incubation of cocaine craving. Nature 2008; 454: 118–121. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Costikyan G. Uncertainty in games. Cambridge, MA: The MIT Press, 2013. [Google Scholar]
  15. D’Ardenne K, McClure SM, Nystrom LE, Cohen JD. BOLD responses reflecting dopaminergic signals in the human ventral tegmental area. Science 2008; 319: 1264–1267. [DOI] [PubMed] [Google Scholar]
  16. Degoulet M, Rostain J-C, Abraini JH, David HN. Short-term development of behavioral sensitization to amphetamine requires N-methyl-D-aspartate- and nicotine-dependent mechanism in the nucleus accumbens. Addiction Biology 2013; 18: 417–424. [DOI] [PubMed] [Google Scholar]
  17. Elliott R, Newman JL, Longe OA, Deakin JF. Differential response patterns in the striatum and orbitofrontal cortex to financial reward in humans: A parametric functional magnetic resonance imaging study. J Neurosci 2003; 23: 303–307. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Filip M, Frankowska M, Zaniewska M, Przegalinski E, Muller CE, Agnati L, Franco R, Roberts DCS, Fuxe K. Involvement of adenosine A2A and dopamine receptors in the locomotor and sensitizing effects of cocaine. Brain Res 2006; 1077: 67–80. [DOI] [PubMed] [Google Scholar]
  19. Fiorillo CD, Tobler PN, Schultz W. Discrete coding of reward probability and uncertainty by dopamine neurons. Science 2003; 299: 1898–1902. [DOI] [PubMed] [Google Scholar]
  20. Grant JE, Chamberlain SR. Gambling and substance use: Comorbidity and treatment implications. Prog Neuro-Psychopharm & Biol Psychi, 2019; current special issue on gambling and drugs. [DOI] [PubMed] [Google Scholar]
  21. Hall GW, Carriero NJ Takushi RY, Montoya ID, Preston KL, Gorelick DA. Pathological gambling among cocaine-dependent outpatients. Am J Psychi 2000; 157: 1127–1133. [DOI] [PubMed] [Google Scholar]
  22. Hart AS, Clark JJ, Phillips PEM. Dynamic shaping of dopamine signals during probabilistic Pavlovian conditioning. Neurobiol Learn Mem 2015; 117: 84–92. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Kalivas PW. The glutamate homeostasis hypothesis of addiction. Nature Rev Neurosci 2009; 10:561–572. [DOI] [PubMed] [Google Scholar]
  24. Kalivas PW, Stewart J. Dopamine transmission in the initiation and expression of drug- and stress-induced sensitization of motor activity. Brain Res Rev 1991; 16: 223–244. [DOI] [PubMed] [Google Scholar]
  25. Kawa AB, Bentzley BS, Robinson TE. Less is more: Prolonged intermittent access cocaine self-administration produces incentive-sensitization and addiction-like behavior. Psychopharmacology 2016: 233: 3587–3602. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Kawa AB, Valenta AC, Kennedy RT, Robinson TE. Incentive and dopamine sensitization produced by intermittent but not long access cocaine self-administration. Eur J Neurosci 2019; 50: 2663–2682. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Kelz MB, Chen J, Carlezon WA, Whisler K, Gilden L, Beckmann AM, Steffen C, Zhang Y-J, Marotti L, Self DW, Tkatch T, Baranauskas G, Surmeier DJ, Neve RL, Duman RS, Picciotto MR, Nestler EJ. Expression of the transcription factor ΔFosB in the brain controls sensitivity to cocaine. Nature 1999; 401: 272–276. [DOI] [PubMed] [Google Scholar]
  28. Kim J-H, Austin JD, Tanabe L, Creekmore E, Vezina P. Activationi of group II mGlu receptors blocks the enhanced drug taking induced by previous exposure to amphetamine. Eur J Neurosci 2005; 21: 295–300. [DOI] [PubMed] [Google Scholar]
  29. Kim WY, Cho BR, Kwak MJ, Kim J-H. Interaction between trait and housing conditions produces differential decision-making toward risk choice in a rat gambling task. Sci Rep 2017; 7: 5718. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Knackstedt LA, Melendez RI, Kalivas PW. Ceftriaxone restores glutamate homeostasis and prevents relapse to cocaine seeking. Biol Psychi 2010; 67: 81–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Laskowski CS, Dorchak DL, Ward KM, Christensen DR, Euston DR. Can slot-machine reward schedules induce gambling addiction in rats? J Gamb Stu 2019; 35: 887–914. [DOI] [PubMed] [Google Scholar]
  32. Leyton M, Vezina P. Striatal ups and downs: Their roles in vulnerability to addictions in humans. Neurosci Biobehav Rev 2013; 37: 1999–2014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Leyton M, Vezina P. Dopamine ups and downs in vulnerability to addictions: A neurodevelopmental model. Trends Pharmacol Sci 2014; 35: 268–276. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Lin D-T, Makino Y, Sharma K, Hayashi T, Neve R, Takamiya K, Huganir RL. Regulation of AMPA receptor extrasynaptic insertionby 4.1N, phosphorylation and palmitoylation. Nature Neurosci 2009: 12: 879–887. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Linnet J. The anticipatory dopamine response in addiction: A common neurobiological underpinning of gambling disorder and substance use disorder? Prog Neuro-Psychopharm & Biol Psychi, 2019; current special issue on gambling and drugs. [DOI] [PubMed] [Google Scholar]
  36. Linnet J, Moller A, Peterson E. Gjedde A, Doudet D. Dopamine release in ventral striatum during Iowa Gambling Task performance is associated with increased excitement levels in pathological gambling. Addiction 2011; 106: 383–390. [DOI] [PubMed] [Google Scholar]
  37. Linnet J, Mouridsen K, Peterson E, Moller A, Doudet DJ, Gjedde A. Striatal dopamine release codes uncertainty in pathological gambling. Psychi Res: Neuroimag 2012; 204: 55–60. [DOI] [PubMed] [Google Scholar]
  38. Loweth JA, Baker LK, Guptaa R, Guillory AM, Vezina P. Inhibition of CaMKII in the nucleus accumbens shell decreases enhanced amphetamine intake in sensitized rats. Neurosci Lett 2008; 444: 157–160. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Loweth JA, Li D, Cortright JJ, Wilke G, Jeyifous O, Neve RL, Bayer KU, Vezina P. Persistent reversal of enhanced amphetamine intake by transient CaMKII inhibition. J Neurosci 2013; 33: 1411–1416. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Loweth JA, Singer BF, Baker LK, Wilke G, Inamine H, Bubula N, Alexander JK, Carlezon WA Jr, Neve RL, Vezina P. Transient overexpression of α-Ca2+/calmodulin-dependent protein kinase II in the nucleus accumbens shell enhances behavioral responding to amphetamine. J Neurosci 2010; 30: 939–949. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Loweth JA, Scheyer AF, Milovanovic M, LaCrosse AL, Flores-Barrera E, Werner CT, Li X, Ford KA, Le T, Foster Olive M, Szumlinski KK, Tseng KY, Wolf ME. Synaptic depression via mGluR1 positive allosteric modulation suppresses cue-induced cocaine craving. Nature Neurosci 2014; 17: 73–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Marcellino D, Roberts DCS, Navarro G, Filip M, Agnati L, Lluis C, Franco R, Fuxe K. Increase in A2A receptors in the nucleus accumbens after extended cocaine self-administration and its disappearance after cocaine withdrawal. Brain Res 2007; 1143: 208–220. [DOI] [PubMed] [Google Scholar]
  43. Marshall L, Mathys C, Ruge D, de Berker AO, Dayan P, Stephan KE, Bestman S. Pharmacological fingerprints of contextual uncertainty. PLOS Bio 2016; 1002575: 1–31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Mascia P, Neugebauer NM, Brown J, Bububla N, Nesbitt KM, Kennedy RT, Vezina P. Exposure to conditions of uncertainty promotes the pursuit of amphetamine. Neuropsychopharmacology 2019; 44: 274–280. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Medvedev IO, Ramsey AJ, Masoud ST, Bermejo MK, Urs N, Sotnikova TD, Beaulieu J-M, Gainetdinov RR, Salahpour A. D1 dopamine receptor coupling to PLCβ regulates forward locomotion in mice. J Neurosci 2013; 33: 18125–18133. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Meredith GE, Pennartz CM, Groenewegen HJ. The cellular framework for chemical signaling in the nucleus accumbens. 1993; Prog Brain Res 99: 3–24. [DOI] [PubMed] [Google Scholar]
  47. Mitrano DA, Schroeder JP, Smith Y, Cortright JJ, Bubula N, Vezina P, Weinshenker D. Alpha-1 adrenergic receptors are localized on presynaptic elements in the nucleus accumbens and regulate mesolimbic dopamine transmission. Neuropsychopharmacology 2012; 37: 2161–2172. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Pettorruso M, De Risio L, Martinotti G, Di Nicola M, Ruggeri F, Conte G, Di Giannantonio M, Janiri L. Targeting the glutamatergic system to treat pathological gambling: Current evidence and future perspectives. BoMed Res Int 2014; 2014: 109786. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Pierce RC, Bell K, Duffy P, Kalivas PW. Repeated cocaine augments excitatory amino acid transmission in the nucleus accumbens only in rats having developed behavioral sensitization. J Neurosci, 1996; 16: 1550–1560. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Pierce RC, Quick EA, Reeder DC, Morgan ZR, Kalivas PW. Calcium-mediated second messengers modulate the expression of behavioral sensitization to cocaine. J Pharmacol Exp Ther 1998; 286:1171–1176. [PubMed] [Google Scholar]
  51. Preuschoff K, Bossaerts P, Quartz SR. Neural differentiation of expected reward and risk in human subcortical structures. Neuron 2006; 51: 381–390. [DOI] [PubMed] [Google Scholar]
  52. Rashid AJ, So CH, Kong MMC, Furtak T, El-Ghundi M, Cheng R, O’Dowd BF, George SR. D1-D2 dopamine receptor heteroligomers with unique pharmacology are coupled to rapid activation of Gq/11 in the striatum. Proc Natl Acad Sci USA 2007; 104:654–659. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Robinson MJF, Anselme P, Fishcer AM, Berridge KC. Initial uncertainty in Pavlovian reward prediction persistently elevates incentive salience and extends sign-tracking to normally unattractive cues. Beh Brain Res 2014; 266: 119–130. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Robinson MJF, Anselme P, Suchomel K, Berridge KC. Amphetamine-induced sensitization and reward uncertainty similarly enhance incentive salience for conditioned cues. Beh Neurosci 2015; 129: 502–511. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Robinson SE, Kunko PM, Smith JA, Wallace MJ, Mo Q, Maher JR. Extracellular aspartate concentration increases in nucleus accumbens after cocaine sensitization. Eur J Pharmacol 1997; 319: 31–36. [DOI] [PubMed] [Google Scholar]
  56. Robinson TE, Berridge KC. The neural basis of drug craving: An incentive-sensitization theory of addiction. Brain Res Rev 1993; 18: 247–291. [DOI] [PubMed] [Google Scholar]
  57. Robinson TE, Berridge KC. The incentive sensitization theory of addiction: Some current issues. Phil Trans R Soc B 2008; 363: 3137–3146. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Robison AJ, Vialou V, Mazei-Robison M, Feng J, Kourrich S, Collins M, Wee S, Koob G, Turecki G, Neve R, Thomas M, Nestler EJ. Behavioral and structural responses to chronic cocaine require a feedforward loop involving ΔFosB and calcium-dependent protein kinase II in the nucleus accumbens shell. J Neurosci 2013; 33: 4295–4307. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Schultz W, Preuschoff K, Camerer C, Hsu M, Fiorillo CD, Tobler PN, Bossaerts P. Explicit neural signals reflecting reward uncertainty. Phil Trans R Soc B 2008; 363: 3801–3811. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Singer BF, Scott-Railton J, Vezina P. Unpredictable saccharin reinforcement enhances locomotor responding to amphetamine. Beh Brain Res 2012; 226: 340–344. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Singer BF, Bubula N, Li D, Przybycien-Szymanska MM, Bindokas VP, Vezina P. Drug-paired contextual stimuli increase dendritic spine dynamics in select neurons of the nucleus accumbens. Neuropsychopharmacology 2016; 41: 2178–2187. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Smith JA, Mo Q, Guo H, Kunko PM, Robinson SE. Cocaine increases extraneuronal levels of aspartate and glutamate n the nucleus accumbens. Brain Res 1995; 683: 264–269. [DOI] [PubMed] [Google Scholar]
  63. Steidl S, Wasserman DI, Blaha CD, Yeomans JS. Opioid-induced rewards, locomotion, and dopamine activation: A proposed model for control by mesopontine and rostromedial tegmental neurons. Neurosci Biobehav Rev 2017; 83: 72–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. St. Onge JR, Ahn S, Phillips AG, Floresco SB. Dynamic fluctuations in dopamine efflux in the prefrontal cortex and nucleus accumbens during risk-based decision making. J Neurosci 2012; 32: 16880–16891. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Suto N, Tanabe LM, Austin JD, Creekmore E, Pham CT, Vezina P. Previous exposure to psychostimulants enhances the reinstatement of cocaine seeking by nucleus accumbens AMPA. Neuropsychopharmacology 2004; 29: 2149–2159. [DOI] [PubMed] [Google Scholar]
  66. Thomsen KR, Fjorback LO, Moller A, Lou HC. Applying incentive sensitization models to behavioral addiction. Neurosci Biobehav Rev 2014; 45: 343–349. [DOI] [PubMed] [Google Scholar]
  67. Todtenkopf MS, Parsegian A, Naydenov A, Neve RL, Konradi C, Carlezon WA Jr. Brain reward regulated by AMPA receptor subunits in nucleus accumbens shell. J Neurosci 2006; 26:11665–11669. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Van Bockstaele EJ, Chan J, Pickel VM. Pre- and postsynaptic sites for serotonin modulationof GABA-containing neurons in the shell region of the rat nucleus accumbens. J Comp Neurol 1996; 370: 116–128. [DOI] [PubMed] [Google Scholar]
  69. Van Bockstaele EJ, Pickel VM. Ultrastructure of serotonin-immunoreactive terminals in the core and shell of the rat nucleus accumbens: Cellular substrates for interactions with catecholamine afferents. J Comp Neurol 1993; 334: 603–617. [DOI] [PubMed] [Google Scholar]
  70. Vanderschuren LJMJ, Kalivas PW. Alterations in dopaminergic and glutamatergic transmission in the induction and expression of behavioral sensitization: A critical review of preclinical studies. Psychopharmacology 2000; 151; 99–120. [DOI] [PubMed] [Google Scholar]
  71. van Holstein M, Macleod PE, Floresco SB. Basolateral amygdala – nucleus accumbens circuitry regulates optimal cue-guided risk/reward decision making. Prog Neuro-Psychopharm & Biol Psychi, 2019; current special issue on gambling and drugs. [DOI] [PubMed] [Google Scholar]
  72. Vezina P. Sensitization of midbrain dopamine neuron reactivity and the self-administration of psychomotor stimulant drugs. Neurosci Biobehav Rev 2004; 27: 827–839. [DOI] [PubMed] [Google Scholar]
  73. Vezina P, Brown J, Neugebauer N, Rodvelt K, Li D, Bubula N, Mascia P. Phosphorylation by PKC but not PKA of AMPA receptor GluA1 subunit residues in the nucleus accumbens is required for expression of sensitized amphetamine-induced locomotion and self-administration. Soc Neurosci Abst 2017; 43: 703.18. [Google Scholar]
  74. Vezina P, Lorrain DS, Arnold GM, Austin JD, Suto N. Sensitization of midbrain dopamine neuron reactivity promotes the pursuit of amphetamine. J Neurosci 2002; 22: 4654–4662. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Vezina P, Queen AL. Induction of locomotor sensitization by amphetamine requires the activation of NMDA receptors in the rat ventral tegmental area. Psychopharmacology 2000; 151: 184–191. [DOI] [PubMed] [Google Scholar]
  76. Wang Q, Li D, Bubula N, Campioni MR, McGehee DS, Vezina P. Sensitizing exposure to amphetamine increases AMPA receptor phosphorylation without increasing cell surface expression in the rat nucleus accumbens. Neuropharmacology 2017; 117: 328–337. [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Wolf ME. The role of excitatory amino acids in behavioral sensitization to psychomotor stimulant drugs. Prog Neurobiol 1998; 54:679–720. [DOI] [PubMed] [Google Scholar]
  78. Wong J-MT, Malec PA, Mabrouk OS, Ro J, Dus M, Kennedy RT. Benzoyl chloride derivatization with liquid chromatography-mass spectrometry for targeted metabolomics of neurochemicals in biological samples. J Chromatography A 2016; 1446: 78–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Yau YHC, Potenza MN. Gambling disorder and other behavioral addictions: Recognition and treatment. Harv Rev Psychi 2015; 23: 134–146. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Zack M, Featherstone RE, Mathewson S, Fletcher PJ. Chronic exposure to a gambling-like schedule of reward predictive stimuli can promote sensitization to amphetamine in rats. Front Behav Neurosci 2014; 8: 7–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Zack M, Poulos CX. Amphetamine primes motivation to gamble and gambling-related semantic networks in problem gamblers. Neuropsychopharmacology 2004; 29: 195–207. [DOI] [PubMed] [Google Scholar]
  82. Zack M, Poulos CX. Parallel roles for dopamine in pathological gambling and psychostimulant addiction. Curr Drug Abuse Rev 2009; 2: 11–25. [DOI] [PubMed] [Google Scholar]
  83. Zack M, St George R, Clark L. Dopaminergic signalling of uncertainty and the aetiology of gambling addiction. Prog Neuro-Psychopharm & Biol Psychi, 2019; current special issue on gambling and drugs. [DOI] [PubMed] [Google Scholar]
  84. Zald DH, Boileau I, El-Dearedy W, Gunn R, McGlone F, Dichter GS, Dagher A. Dopamine transmission in the human striatum during monetary reward tasks. J Neurosci 2004; 24: 4105–4112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Zeeb FD, Li Z, Fisher DC, Zack MH, Fletcher PJ. Uncertainty exposure causes behavioural sensitization and increases risky decision-making in male rats: Toward modeling gambling disorder. J Psychi Neurosci 2017; 42: 404–413. [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Zeeb FD, Robbins TW, Winstanley CA. Serotonergic and dopaminergic modulation of gambling behavior as assessed using a novel rat gambling task. Neuropsychopharmacology 2009; 34: 2329–2343. [DOI] [PubMed] [Google Scholar]

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