Impulsive action and impulsive choice across substance and behavioral addictions: Cause or consequence?

Addictive Behaviors 39 (2014) 1632–1639

Contents lists available at ScienceDirect

Addictive Behaviors

Impulsive action and impulsive choice across substance and behavioral addictions: Cause or consequence? Jon E. Grant a,⁎, Samuel R. Chamberlain b,c,d a

University of Chicago, Pritzker School of Medicine, 5841 South Maryland Ave., Chicago, IL 60637, USA Department of Psychiatry, University of Cambridge, UK MRC/Wellcome Trust Behavioural and Clinical Neurosciences Institute, UK d Cambridge & Peterborough NHS Foundation Trust, Cambridge, UK b c

H I G H L I G H T S • Behavioral addictions associated with impulsive actions. • Findings are similar to those seen in chronic substance use disorders. • Whether cognitive deficits are cause or effect remains unclear.

a r t i c l e

i n f o

Available online 10 May 2014 Keywords: Impulsivity Neurobiology Cognition Addiction Behavior Neuroimaging

a b s t r a c t Substance use disorders are prevalent and debilitating. Certain behavioral syndromes (‘behavioral addictions’) characterized by repetitive habits, such as gambling disorder, stealing, shopping, and compulsive internet use, may share clinical, co-morbid, and neurobiological parallels with substance addictions. This review considers overlap between substance and behavioral addictions with a particular focus on impulsive action (inability to inhibit motor responses), and impulsive choice (preference for immediate smaller rewards to the detriment of long-term outcomes). We find that acute consumption of drugs with abuse potential is capable of modulating impulsive choice and action, although magnitude and direction of effect appear contingent on baseline function. Many lines of evidence, including findings from meta-analyses, show an association between chronic drug use and elevated impulsive choice and action. In some instances, elevated impulsive choice and action have been found to predate the development of substance use disorders, perhaps signifying their candidacy as objective vulnerability markers. Research in behavioral addictions is preliminary, and has mostly focused on impulsive action, finding this to be elevated versus controls, similar to that seen in chronic substance use disorders. Only a handful of imaging studies has explored the neural correlates of impulsive action and choice across these disorders. Key areas for future research are highlighted along with potential implications in terms of neurobiological models and treatment. In particular, future work should further explore whether the cognitive deficits identified are state or trait in nature: i.e. are evident before addiction perhaps signaling risk; or are a consequence of repetitive engagement in habitual behavior; and effects of novel agents known to modulate these cognitive abilities on various addictive disorders. © 2014 Elsevier Ltd. All rights reserved.

Contents 1. 2.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cognitive tasks fractionating aspects of behavioral inhibition: neural and neurochemical substrates . . . . . . . . . . . . . . . . . . . . . 2.1. Deficient response inhibition (impulsive action) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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⁎ Corresponding author at: Department of Psychiatry & Behavioral Neuroscience, University of Chicago, Pritzker School of Medicine, 5841 S. Maryland Avenue, MC 3077 Chicago, IL 60637, USA. Tel.: +1 773 834 1325; fax: +1 773 834 6761. E-mail address: [email protected] (J.E. Grant).

http://dx.doi.org/10.1016/j.addbeh.2014.04.022 0306-4603/© 2014 Elsevier Ltd. All rights reserved.

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2.2. Impaired deferment of gratification (impulsive choice) . . . . . . . . . . . . . . . . . . . . . . Behavioral inhibition and substance use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Acute effects of substances with abuse potential on impulsivity . . . . . . . . . . . . . . . . . . 3.2. Associations between chronic substance use (substance use disorders) and impulsivity . . . . . . . 3.3. Impulsive action and choice in chronic substance use (substance use disorders): cause or consequence? 4. Impulsivity in putative behavioral addictions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Gambling disorder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Kleptomania . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Compulsive buying . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4. Internet addiction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Treatment implications and future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Funding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflict of interests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.

1. Introduction Several behavioral problems (for example, gambling, stealing, shopping, and use of the internet) have been hypothesized to have similarities to substance addictions and there is interest in whether they could be usefully conceptualized as ‘behavioral addictions’ (i.e. people compulsively and dysfunctionally engage in an activity without exogenous drug administration) (Holden, 2001). Support for such a conceptualization would ideally arise from several complimentary perspectives, including evidence of overlapping phenomenology, comorbidity, neurobiology, and treatment response. While evidence of such overlap is in many cases lacking (e.g. Kor, Fogel, Reid, & Potenza, 2013), the latest version of the Diagnostic and Statistical Manual (DSM-5) recognized the utility of this conceptualization for the purposes of gambling disorder, which now sits within the category of Substancerelated and Addictive Disorders. From a phenomenological perspective, substance addictions are typically characterized by repetitive habitual engagement in drug use (escalation in quantity and/or frequency of use over time), unsuccessful attempts to cut back, craving (intense desires to obtain substances), persistence despite negative functional impact (e.g. in terms of relationships or health consequences), narrowing of repertoire (less functionally appropriate behavior), increased engagement to produce a given effect (tolerance), and withdrawal symptoms (unpleasant physical consequences when use is reduced or stopped). Many of these phenomenological aspects are shared with putative behavioral addictions (e.g. see Leeman & Potenza, 2012). For example, individuals who gamble occasionally may experience initial pleasure and be able to control gambling-related urges, but over time, this behavior may become ingrained, more ‘habitual’ than ‘pleasurable’, and difficult to resist, with a profound negative impact on everyday functioning (el-Guebaly, Mudry, Zohar, Tavares, & Potenza, 2012). Exposure to gambling-related environmental cues can trigger craving, in much the same way that drug-related cues can trigger craving in substance-addicted individuals. Pathological gamblers often make unsuccessful attempts to cut back and experience symptoms akin to withdrawal when resisting the behavior (Cunningham-Williams, Gattis, Dore, Shi, & Spitznagel, 2009). There is an ongoing search in psychiatry for neurobiological markers implicated in given behavioral domains that cross specific diagnostic categories. Neurobiological models of addiction emphasize the likely involvement of excess activity of the basal ganglia reward and habit forming system coupled with a lack of top-down control or inhibition (Bari & Robbins, 2013; Cardinal & Everitt, 2004; Robbins, Everitt, & Nutt, 2008). For substance addiction, there is a translational evidence of a postulated shift over time from a behavior that is initially rewarding (implicating the ventral striatum) to one that becomes habitual and compulsive (implicating the dorsal striatum) (Everitt & Robbins, 2013). However, diminished control over such actions (impulsive action) and

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preference for a small immediate gratification rather than a larger delayed gratification (impulsive choice) may serve to augment both aspects of striatally-mediated behaviors. While indubitably not capturing all facets of these illnesses, just as someone with alcoholism cannot seem to suppress the habitual act of consuming alcohol and seeks a short-term rewarding ‘hit’, so, too, do individuals with behavioral addictions report difficulties in stopping their habits and in averting their desire for short-term reward. While cognitive deficits have been reported across various domains in individuals with substance addiction and certain behavioral addictions versus healthy controls (e.g. Dom, De Wilde, Hulstijn, van den Brink, & Sabbe, 2006; Durazzo & Meyerhoff, 2007; Kalechstein, De La Garza, Mahoney, Fantegrossi, & Newton, 2007; Nnadi, Mimiko, McCurtis, & Cadet, 2005; Riggs & Greenberg, 2009; van Holst, van den Brink, Veltman, & Goudriaan, 2010), the domain of behavioral inhibition may represent a particularly fruitful arena for the search for candidate cognitive vulnerability markers. This primer focuses on findings using tests quantifying aspects of behavioral inhibition in this context. 2. Cognitive tasks fractionating aspects of behavioral inhibition: neural and neurochemical substrates With respect to modeling behavioral inhibition, several potentially dissociable cognitive domains have been proposed (Bari & Robbins, 2013). For the purposes of this selective review, we focus on deficient response inhibition (impulsive action), and deficient deferment of gratification (impulsive choice). 2.1. Deficient response inhibition (impulsive action) Response inhibition refers to the ability to suppress a given response when signaled to do so in response to environmental cues and is typically operationalized by go/no-go and stop-signal test (SST) paradigms (e.g. see Logan, Cowan, & Davis, 1984; Schachar et al., 2007; Eagle, Bari, & Robbins, 2008). Both types of test require participants to make simple motor responses (such as pressing a left or right button) in response to cues (such as left and right directional arrows appearing on a computer screen) — these are referred to as ‘go’ trials. On a minority of trials, participants attempt to withhold their usual response due to the presence of a stop-cue (referred to as ‘stop’ trials). The relative excess of go trials renders the go response ‘pre-potent’. For go/no-go tasks, the stop-cue is presented alongside (at the same time) as the go-cue: therefore, the response has not already been triggered; crucially, on stop-signal tasks, the stop-cue is presented a variable time after the go-cue. As such, stop-signal tasks assess the ability of the participant's brain to suppress already triggered responses. Stop-signal tasks may be more sensitive to inhibitory dyscontrol since they use tracking algorithms that flexibly adapt to the individual's performance. Via

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a tracking algorithm, stop-signal tasks permit calculation of the stopsignal reaction time (SSRT), which is a measure of how long it takes the volunteer to suppress a response that would ordinarily be made (Logan et al., 1984). Longer SSRT equates to worse inhibitory control, and greater impulsive action. The specific neural basis underlying response inhibition remains under dispute, in terms of whether neural regions are specifically acting as a top-down ‘brake’ or might be better conceptualized in terms of adaptive learning processes (Hampshire, Chamberlain, Monti, Duncan, & Owen, 2010). However, performance on the SST is largely dependent on distributed neural circuitry including the inferior frontal gyrus, anterior cingulate cortex, and subcortical structures such as the subthalamic nucleus (Aron et al., 2007). Evidence from diffusion-weighted imaging tractography suggests that the inferior frontal cortex and subthalamic nucleus are connected with the pre-supplementary motor area, consistent with a model in which the right frontal lobe can act as a ‘brake’ to halt prepotent behavior (Aron et al., 2007). Considerable research has been conducted in developing translational versions of this task used in other species and applying them in studies of focal lesions and neurochemical manipulations. While the details of this research are outside the scope of the current primer (for a detailed overview see Bari & Robbins, 2013), translational work indicates that the key measure of impulse control — the SSRT — appears to be largely under noradrenergic control (Bari et al., 2011; Chamberlain & Robbins, 2013; Eagle & Baunez, 2010). However, some lines of research implicate the involvement other neurotransmitter systems such as dopamine (e.g. Ghahremani et al., 2012; Nandam et al., 2011), and this represents another key line of inquiry.

2.2. Impaired deferment of gratification (impulsive choice) Impulsive choice refers to a tendency to preferentially select small immediate rewards rather than larger delayed rewards, to the detriment of long-term outcomes (Cardinal, Pennicott, Sugathapala, Robbins, & Everitt, 2001; Evenden, 1999; Thiebot, Le Bihan, Soubrie, & Simon, 1985). This tendency is typically quantified by plotting discounting curves, in which a steeper discounting curve (greater delay-discounting) is indicative of a greater impulsive choice. In humans, rewards can be provided in the form of real money, or abstract points; while in animals, rewards can be given — for example — in the form of food. The differential contributions of neural regions and neurochemical systems to impulsive choice is unclear, likely due in substantial part to the complexity of measuring this cognitive domain. Several lines of research implicate the nucleus accumbens in impulsive choice (Acheson et al., 2006; Cardinal et al., 2001; Pothuizen, Jongen-Rêlo, Feldon, & Yee, 2005), along with the cingulate cortices (perhaps more posterior than anterior) (Bickel, Pitcock, Yi, & Angtuaco, 2009; Rudebeck, Walton, Smyth, Bannerman, & Rushworth, 2006), posterior insula (Luhmann, 2009), and orbitofrontal lobes (Winstanley, Theobald, Cardinal, & Robbins, 2004) (for a detailed discussion see Dalley, Mar, Economidou, & Robbins, 2008). It may be that the accumbens is relatively sensitive to the magnitude of future rewards, while lateral cortical regions are relatively sensitive to the delay of future rewards (Ballard & Knutson, 2009). Certainly various dopaminergic, serotonergic, and noradrenergic manipulations have been found to affect impulsive choice (Dalley et al., 2008) and a cohesive model of the relative contributions of these systems has yet to be established. Indeed, there is evidence that interactions between the serotonin and dopamine systems are involved in delay discounting, based on the finding that the ability of the pro-dopamine stimulant medication amphetamine to reduce impulsive choice in rats is reduced by global brain serotonin depletion (Winstanley, Dalley, Theobald, & Robbins, 2003). In vivo microdialysis studies suggest that extracellular levels of dopamine and serotonin in the medial prefrontal cortices increase during delay-discounting in animals (Dalley et al., 2008).

3. Behavioral inhibition and substance use To understand the relationship between substance use disorders and behavioral inhibition, several questions would need to be addressed: firstly, what are the effects of acute substance intake on inhibition? Secondly, what are the effects of chronic substance intake on inhibition (or more pragmatically, is chronic substance intake associated with inhibition problems)? And thirdly, could problems with inhibition in fact predate substance use disorders and predispose some people toward developing these disorders? 3.1. Acute effects of substances with abuse potential on impulsivity The issue of effects of acute substance intake on inhibition has been reviewed in detail elsewhere (see Perry & Carroll, 2008 for excellent overview). In essence, several substances with addictive potential have been found to modulate motor impulsivity in humans (indexed using stop-signal and/or go/no-go paradigms). Acute nicotine has been found to improve impulsive action in healthy volunteers (e.g. Potter, Bucci, & Newhouse, 2012). In some but not all studies, alcohol, certain benzodiazepines, and the main psychoactive active ingredient in cannabis (tetrahydrocannabinol, THC) have been shown to impair response inhibition (e.g. Fillmore, Rush, Kelly, & Hays, 2001; McDonald, Schleifer, Richards, & de Wit, 2003; Mulvihill, Skilling, & Vogel-Sprott, 1997). Amphetamine and cocaine appear capable of improving or impairing response inhibition, contingent on baseline performance (e.g. de Wit, Enggasser, & Richards, 2002; Fillmore, Rush, & Hays, 2006). In terms of effects of acute substance intake on impulsive choice (measured primarily using delay-discounting paradigms), somewhat fewer studies have been conducted in humans (Perry & Carroll, 2008). Amphetamine has been found to reduce impulsive choice, at least in some studies (e.g. de Wit et al., 2002), while THC appeared to have no effect on impulsive choice, even though impulsive action was increased (McDonald et al., 2003). Alcohol had no notable effect on impulsive choice in some studies (Richards, Zhang, Mitchell, & de Wit, 1999), reduced it in another (Ortner, MacDonald, & Olmstead, 2003), and increased it in another (Reynolds, Richards, & de Wit, 2006). Taken together, the available data indicate that a variety of substances with addictive potential can modulate impulsivity when given acutely, but with a larger body of evidence available for effects on impulsive action. The findings are conflicting, however, and there are several likely reasons for this. For example, the direction of effect is likely to depend on baseline function (whether a given subject has a pre-existing cognitive impairment, or is at optimal performance) and arousal, the magnitude of dose given, and previous exposure to the substance in question. It is likely that cognitive functions operate according to an inverted ‘U’ model, in which too much or too little of a given neurotransmitter can impair a given ability (see Chamberlain & Robbins, 2013 for discussion). Drugs with misuse potential exert complex effects on different neurochemical systems, and therefore it is perhaps not surprising that findings are so heterogeneous. 3.2. Associations between chronic substance use (substance use disorders) and impulsivity Chronic use of substances with abuse potential has been associated with elevated impulsive choice, and impulsive action, across multiple studies (versus controls). In a meta-analysis that considered data from a variety of psychopathologies, substance dependence was significantly associated with impaired response inhibition, with small–medium effect size (Hedge's g = 0.39) (Lipszyc & Schachar, 2010). The studies within this meta-analysis focused on alcohol-dependent patients (3 studies: Goudriaan, Oosterlaan, de Beurs, & van den Brink, 2006; Rubio et al., 2007; Li, Luo, Yan, Bergquist, & Sinha, 2009), and cocainedependent patients (3 studies: Fillmore & Rush, 2002; Li, Milivojevic, Kemp, Hong, & Sinha, 2006; Li et al., 2008). In a study in young adults

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conducted by our group, nicotine use was not associated with stopsignal abnormalities, but it was associated with impairments in other cognitive domains (Chamberlain, Odlaug, Schreiber, & Grant, 2012). Elevated impulsive action has also been found in studies of recreational and heavy cannabis users (e.g. Behan et al., 2013; Moreno et al., 2012). A large meta-analysis comprising data from 46 studies found that clinically noteworthy addictive behaviors were associated with significantly elevated impulsive choice versus controls with medium effect size overall (MacKillop et al., 2011). The extent of impairment was greater in more severely addicted individuals (i.e. impulsive choice was more strongly associated with substance misuse, rather than use). Significantly elevated impulsive choice was identified in the context of alcohol (Cohen's d = 0.50), nicotine (d = 0.57), opiate (d = 0.76), and stimulant (d = 0.87) misuse; but — interestingly — not significantly so for marijuana misuse (d = 0.20). Thus, the available evidence demonstrates an association between chronic intake of several types of addictive substances and heightened impulsivity. However, it is important to bear in mind that many of these studies may have been influenced by confounding factors. For example, substance use disorders are frequently comorbid with a variety of other psychiatric conditions such as mood/anxiety disorders, attention deficit hyperactivity disorder (ADHD), and others, which could theoretically have contributed to some of the deficits reported.

3.3. Impulsive action and choice in chronic substance use (substance use disorders): cause or consequence? The above-reviewed studies indicate that acute intake of substances with abuse potential can modulate choice and action impulsivity under some circumstances, and that chronic intake of various substances with abuse potential is associated with elevated impulsivity. Nonetheless, these latter studies — by their cross-sectional nature — do not clarify whether it is the substance use itself that is responsible for impulsivity thus operationalized: it may be that subjects with elevated baseline impulsivity are more vulnerable to developing substance use disorders; or that of other influences (e.g. co-morbidities) contributed. Importantly impaired response inhibition (elevated impulsive action) has been identified in first-degree relatives of people with stimulant dependence, who themselves had no history of stimulantdependence (Ersche et al., 2012; Ersche et al., 2012). Longitudinal research has found that elevated impulsive choice during development was associated with subsequent initiation of smoking (AudrainMcGovern et al., 2009); and even drug use into adulthood some 20 years later (Ayduk et al., 2000). Furthermore, elevated impulsive choice appears to persist into recovery from substance use disorders, at least in the context of former alcohol and nicotine users (Bickel, Odum, & Madden, 1999; Petry, 2005). While more research is needed, we hypothesize that elevated action and choice impulsivity represent candidate heritable markers that may predispose certain people toward the development of substance use problems.

4. Impulsivity in putative behavioral addictions While the relationship between substance addiction and behavioral dysinhibition has been somewhat complicated by the prospect that chronic substance use may exert neurotoxic effects on the brain, presumably behavioral addictions would not be impacted by this potential confound. As such, cognitive deficits identified in people with behavioral addictions may more readily be attributable to disease predisposition rather than toxic brain effects of the habit, and therefore may inform our speculation as to elevated action and choice impulsivity representing candidate vulnerability markers not only for substance use disorders, but also behavioral addictions.

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4.1. Gambling disorder Gambling disorder shares many features with substance addictions. Although prospective studies are largely lacking, gambling disorder appears to follow a similar trajectory as substance addiction, with high rates in adolescent and young adult groups, lower rates in older adults, and periods of abstinence and relapse (Grant & Potenza, 2004). Gambling disorder is also highly comorbid with substance addiction (Chou & Afifi, 2011). It has been hypothesized that poor inhibition of prepotent responses in adult gamblers may contribute to the reduced capacity to remain abstinent. Studies comparing non-gamblers to individuals with gambling disorder on SST have found that gambling disorder is associated with impaired pre-potent inhibition performance, i.e. elevated impulsive action (Brevers et al., 2012; Odlaug, Chamberlain, Kim, Schreiber, & Grant, 2011; Goudriaan et al., 2006; but see Lipszyc & Schachar, 2010). Elevated impulsive choice has also been identified in a study conducted in gambling disorder versus controls (Petry, 2005). 4.2. Kleptomania The core features of kleptomania include: 1) a recurrent failure to resist an impulse to steal unneeded objects; 2) an increasing sense of tension before committing the theft; 3) an experience of pleasure, gratification or release at the time of committing the theft; and 4) the stealing is not performed out of anger, vengeance, or due to psychosis (APA, 2013). Like individuals with substance addictions, most with kleptomania have urges to steal, find the behavior intensely exciting, and try unsuccessfully to stop (Grant, Odlaug, & Kim, 2010; Grant, Odlaug, & Kim, 2010). There are also indications of tolerance and withdrawal in individuals with kleptomania (Grant, Odlaug, & Kim, 2010; Grant, Odlaug, & Kim, 2010). Together, these findings demonstrate a continued engagement in the problematic behavior despite adverse consequences, a core feature of addiction. On cognitive testing, a small sample (n = 13) of individuals with kleptomania demonstrated significantly longer reaction times on the SST (i.e. elevated impulsive action) compared to age- and gendermatched health controls even though tasks of cognitive flexibility did not differ (Grant, Odlaug, Schreiber, Chamberlain, & Won, 2013). The findings were similar to those found in individuals with a gambling disorder. To the authors' knowledge, impulsive choice has not been studied in this disorder. 4.3. Compulsive buying Compulsive buying is characterized by a preoccupation with buying, buying more than one can afford or unneeded items, and shopping for longer durations of time than originally intended resulting in marked distress or interference with social and occupational functioning (McElroy, Keck, Pope, Smith, & Strakowski, 1994). Individuals with compulsive buying often report that once they start buying, they cannot control their behavior even if they are aware of the possible consequences (Black, 2007). As with other behavioral and substance addictions, the onset of compulsive buying appears to occur during late adolescence or early adulthood, although the full disorder may take several years to develop (Christenson et al., 1994). Due to the pleasurable and rewarding aspects of the behavior, compulsive buying is characterized by repetitive urges to shop. These urges, which may worsen during times of stress, emotional difficulties, or boredom, are generally intrusive, and most patients attempt to resist them, although usually unsuccessfully (Christenson et al., 1994). Neurocognitive data on compulsive buying are limited (Black, Shaw, McCormick, Bayless, & Allen, 2012). In the only study examining impulsive action (SST performance) in compulsive buying, such individuals

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displayed significantly worse response inhibition than healthy controls, along with deficits in decision-making and spatial working memory (Derbyshire et al., 2014). Impulsive choice has yet to be explored in this disorder, according to our survey of the extant literature. 4.4. Internet addiction Internet addiction is not currently recognized by the DSM-5 as a formal psychiatric disorder but is listed in Section 3, in a modified form (Internet Gaming Disorder) as a disorder requiring further research. Tao et al. (2010), however, have recommended the following criteria for internet addiction, which mirror those used for other behavioral and substance addictions: internet preoccupation; withdrawal; increased tolerance for internet use; inability to control internet use; continuation of internet use despite negative consequences; loss of interest in other activities; and using the internet to relieve dysphoric mood states. Individuals with internet addiction typically spend 40 to 80 h per week online (Young, 1998), spend more time on the internet for non-essential use (i.e., pleasure or personal use) (Shapira, Goldsmith, Keck, Khosla, & McElroy, 2000; Young, 1998), and report a variety of problems associated with their internet use (Shapira et al., 2000). Individuals with internet addiction have demonstrated greater impulsive action than controls on the go/stop impulsivity paradigm (Cao, Su, Liu, & Gao, 2007). In terms of the SST, one study has found that individuals with internet addiction demonstrated significantly greater dysfunction in inhibitory control compared to healthy controls (Choi et al.,2013). A recent study of pathological gaming subjects found that they made more impulsive choices, preferring smaller immediate over larger delayed rewards (Irvine et al., 2013). 5. Treatment implications and future directions Inhibitory deficits are considered to be a central problem in drug addiction, both in terms of human findings (Volkow, Fowler, Wang, & Swanson, 2004), but also in terms of animal models of drug addiction (Dalley et al., 2007). This paper has focused on findings in humans relating to two operationalizations of impulsivity: impulsive action (inability to suppress motor responses that would ordinarily be undertaken), and impulsive choice (preference for smaller immediate rewards rather than proportionately larger delayed rewards). Our survey of the available literature indicates that acute intake of substances with addictive potential can modulate action and choice impulsivity, with direction and magnitude of effect likely to be contingent on baseline performance; and that chronic intake of various substances with addictive potential has been associated with elevated impulsive action and impulsive choice. Furthermore, these paradigms have started to be applied to the study of putative behavioral addictions and a growing body of preliminary literature has identified elevated impulsive action in several such disorders, while impulsive choice remains less well studied. These findings may have important clinical implications in that impulsivity may facilitate relapse to drug-seeking (e.g. Jentsch & Taylor, 1999; Winstanley, Olausson, Taylor, & Jentsch, 2010) and possibly behavioral addictions; and be associated with lower levels of treatment compliance (e.g. Moeller, Barratt, Dougherty, Schmitz, & Swann, 2001). Research from longitudinal cohorts and individuals with substance addictions and their unaffected siblings suggests that deficits in the aspects of inhibition may represent potentially heritable characteristics and therefore promising candidate endophenotypes for genetic investigation (Ersche, Jones, et al., 2012; Ersche, Turton, et al., 2012). Consequently, a deeper understanding of the mechanisms behind inhibitory control deficits allow for a greater understanding of pathophysiology across disorders and more effective treatment options for a range of addictive behaviors. It remains to be seen whether these behavioral impairments are mediated by common dysfunction of fronto-striatal circuitry across

these clinical contexts. Converging tiers of evidence from neuroimaging studies in healthy controls and people with focal brain lesions indicate impulsive action to be contingent on function of the pre-supplementary motor area (pre-SMA), dorsomedial prefrontal cortex, and right frontal regions (including anterior insula and inferior frontal gyrus) (Swick, Ashley, & Turken, 2011). By contrast, impulsive choice appears to be contingent on function of the nucleus accumbens, cingulate and orbitofrontal cortices, based on tiers of data including neuroimaging findings in healthy volunteers (Dalley et al., 2008). A handful of studies has identified abnormalities of brain activation during SST paradigms in people with drug dependence. For example, stimulation-dependent individuals manifested hypoactivation of the ventrolateral prefrontal and anterior cingulate cortices versus controls (Morein-Zamir, Simon Jones, Bullmore, Robbins, & Ersche, 2013). Under-activation of the dorsomedial prefrontal cortex was found in problem gamblers and heavy smokers versus controls (de Ruiter, Oosterlaan, Veltman, van den Brink, & Goudriaan, 2012), intriguingly hinting at common neural dysfunction across behavioral and substance addictions. Further work is needed to explore neural underpinnings of impaired SST performance across the range of disorders. Some studies have similarly explored brain activation during temporal discounting paradigms in people with drug dependence. In individuals with methamphetamine-dependence, while healthy controls showed less recruitment of dorsolateral and intraparietal regions for easy versus hard task choices, drug-dependent individuals did not, suggesting that cortical inefficiently may relate to enhanced delayed discounting seen in this group (Monterosso et al., 2007). In a separate study, also in methamphetamine-dependent individuals, drug users showed underactivation of regions including the cingulate, and dorsolateral cortices, during a temporal discounting paradigm, versus controls (Hoffman et al., 2008). Adolescents who smoke showed elevated impulsive choice linked with lower ventral striatum responses during a discounting test as compared to controls (Peters et al., 2011). Kobiella et al. (2013) attempted to disentangle influences of acute nicotine from chronic nicotine use in terms of brain activation during a discounting task. They found hypoactivation in parietal and occipital regions during discounting decision-making in nicotine-satiated smokers versus controls; and that a single dose of nicotine in non-smokers yielded a similar effect. Smokers showed hyporesponsiveness of the ventral striatum during reward processing versus controls while acute nicotine intake in controls was associated with increased reward-related activation in the hippocampus, amygdala, and insula. Thus, the authors concluded that differences between smokers and non-smokers are only partially due to acute pharmacological influences of nicotine (Kobiella et al., 2013). In pathological gamblers, functional imaging demonstrated that correlations between ventral striatum and orbitofrontal cortex activation and subjective reward values were attenuated in gamblers for risky rewards; while for delayed rewards, correlations were significantly enhanced in gamblers (Miedl, Peters, & Büchel, 2012). Thus, there do appear to be some parallels in terms of dysfunction of neural nodes implicated in discounting between substance dependence and gambling disorder. However, further research is needed to extend the impulsive choice findings in gambling, and beyond into other putative behavioral addictions. In terms of neurochemical underpinnings of inhibitory control on the SST, based on pharmacological challenge studies in rodents and humans, noradrenaline has been most consistently implicated (Chamberlain & Robbins, 2013). A recent study in human volunteers demonstrated that the relatively selective noradrenaline reuptake blocker atomoxetine improves SSRT without affecting measures of attention and learning, whereas the selective serotonin reuptake inhibitor, citalopram, affected learning but not attention or SSRT (Chamberlain et al., 2006). Other data suggest that dopaminergic and serotoninergic influences on SSRT performance are only minor (Robbins, 2007), while other evidence supports a role for dopamine in this function (Ghahremani et al., 2012; Nandam et al., 2011).

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Interestingly, the data using atomoxetine and other noradrenergic agents such as desipramine in the treatment of substance addiction has been far less convincing than the animal data (Tirado, Goldman, Lynch, Kampman, & Obrien, 2008; Walsh et al., 2013). There have been no placebo-controlled trials of a noradrenergic agent in the treatment of behavioral addictions, although this might be a promising area for future inquiry. Although the animal data has not explored the role of glutamate in performance on the SST, glutamatergic agents, such as memantine, may be able to treat both behavioral and substance addictions by targeting this core motor impulsivity domain (Grant, Potenza, Weinstein, & Gorelick, 2010; Grant, Odlaug, & Kim, 2010, 12, 13) and may explain why it was not particularly beneficial for nicotine dependence which does not exhibit this motor impulsivity dysfunction (Jackson et al., 2009). Glutamate is the primary neurotransmitter within cortico-striatal-thalamic circuit, and glutamatergic agents may present a potentially useful option for addictive behaviors characterized by motor impulsivity. Given the role of dopamine in reward processing, as well as the potential role of stimulants in addictive disorders, the potential effectiveness of dopaminergic agents may also reflect a neural commonality in disorders of motor impulsivity (Li et al., 2010). A non-treatment trial examined the effects of an atypical dopaminergic stimulant, modafinil, on individuals with gambling disorder classified according to impulsivity. Individuals with high impulsivity showed improvement in impulsive action (using the SST) (Zack & Poulos, 2009). It should be noted however that modafinil's mode of action is partially contingent on noradrenergic function, based on animal findings. Whether dopamine agonists working in the prefrontal cortex would benefit a range of addictive disorders remains unknown but potentially worthy of study. As stated previously, the neurochemical systems underlying impulsive choice are less clear, and treatment options targeting this cognitive domain are less researched. Recent animal research suggests that blockade of 5-HT2C receptors improved impulsive choice (Paterson, Wetzler, Hackett, & Hanania, 2012), and a primate study found that guanfacine, an agonist of the alpha-2A subtype of the norepinephrine receptor, shifted impulsive choice toward preference for a larger later reward (Kim, Bobeica, Gamo, Arnsten, & Lee, 2012).

6. Conclusions The clinical phenotypes of behavioral addictions (e.g., gambling disorder, compulsive buying, kleptomania, internet addiction) mirror those seen in substance use disorders and this has led to further research examining possible neurobiological similarities between substance use disorders and a variety of behaviors. Research into neurobiological markers of behavioral domains that cross specific diagnostic categories of substance and behavioral addictions, however, is only in the early stages. Preliminary research has found that diminished control over prepotent behavior, and to a much more limited extent, the preference for immediate rewards, may be promising targets to understand both behavioral and substance addictions. The brain circuitry implicated in behavioral inhibition, however, is still lacking clear definition, and therefore many unanswered questions about the nature of behavioral inhibition remain and warrant further investigation. What is the temporal relationship of these cognitive domains to the behaviors in question? Future work should further explore whether the cognitive deficits identified are state or trait in nature: i.e. are evident before addiction perhaps signaling risk; or are a consequence of repetitive engagement in habitual behavior. When are deficits in behavioral inhibition the consequence of emotional dysregulation or of aberrant cognitive operations? Can behavioral inhibition be successfully treated by behavioral or pharmacological therapies? Much has to be done for us to be able to answer these questions and improvements in animal models and imaging techniques will be very helpful.

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Research on the behavioral and neural basis of inhibition may profoundly change the way we understand and treat many of these disorders. Funding This work was supported by a Center of Excellence in Gambling Research grant from the National Center for Responsible Gaming to Dr. Grant. Conflict of interests Dr. Grant has received research grants from NIDA (1RC1DA028279-01), National Center for Responsible Gaming, Forest Pharmaceuticals, Transcept Pharmaceuticals, Psyadon Pharmaceuticals, Roche Pharmaceuticals, and the University of South Florida. Dr. Grant receives yearly compensation from Springer Publishing for acting as Editor-in-Chief of the Journal of Gambling Studies. Dr. Grant has received royalties from the Oxford University Press, the American Psychiatric Publishing, Inc., the Norton Press, and McGraw Hill. Dr. Chamberlain has consulted for Cambridge Cognition, P1Vital, and Shire Pharmaceuticals; and has received speaker honoraria from Lilly. Dr Chamberlain's research is funded by a grant for clinical lecturers from the Academy of Medical Sciences (AMS), United Kingdom. Contributors Authors Grant and Chamberlain conducted literature searches,wrote the article,and both authors contributed to and have approved the final manuscript.

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