|Home | About | Journals | Submit | Contact Us | Français|
This review summarizes neurobiological and genetic findings in behavioral addictions, draws parallels with findings pertaining to substance use disorders and offers suggestions for future research. Articles concerning brain function, neurotransmitter activity and family history/genetics findings for behavioral addictions involving gambling, internet use, video game playing, shopping, kleptomania and sexual activity were reviewed. Behavioral addictions involve dysfunction in several brain regions, particularly the frontal cortex and striatum. Findings from imaging studies incorporating cognitive tasks have arguably been more consistent than cue-induction studies. Early results suggest white and gray matter differences. Neurochemical findings suggest roles for dopaminergic and serotonergic systems, but results from clinical trials seem more equivocal. While limited, family history/genetic data support heritability for pathological gambling and that those with behavioral addictions are more likely to have a close family member with some form of psychopathology. Parallels exist between neurobiological and genetic/family history findings in substance and non-substance addictions, suggesting that compulsive engagement in these behaviors may constitute addictions. Findings to date are limited, particularly for shopping, kleptomania and sexual behavior. Genetic understandings are at an early stage. Future research directions are offered.
Classes of behaviors having hedonic qualities (at least initially) including gambling, shopping, sexual behaviors, internet use and video game play may lead to compulsive engagement among a minority of individuals. At excessive levels, these behaviors are considered “impulse control disorders not elsewhere classified” in the DSM-IV-TR1, However, they may also be considered non-substance or “behavioral” addictions2-7. As gambling, shopping, sex, gaming and internet use are normative behaviors, it may be challenging to differentiate between normal and excessive participation5. Further challenges may stem from greater heterogeneity in the syndromes of behavioral addictions, complicating their categorization8. Mechanisms underlying behavioral (versus substance) addictions are relatively poorly understood, in part because animal models that have facilitated insight into substance use disorders9,10 are less straightforward or advanced for behavioral addictions8,11,12.
Behavioral addictions share important elements with substance addictions. These include impaired control over engagement, continued engagement despite negative consequences and urges or cravings6,13. Behavioral and substance addictions frequently co-occur14,15 and there are similarities in the progression of the disorders (e.g., high rates of the conditions in adolescents and young adults, negative reinforcement motivations and a “telescoping” phenomenon observed in females6,16).
Similar neurobiological features underlie both substance and behavioral addictions8,17,18, with common features involving cross-sensitization, brain function and neurochemistry8. Cross-sensitization involves neuro-adaptations in which repeated exposure to one drug leads to a more robust response to another8. With respect to non-substance addictions, exposure to a substance of abuse can lead to sensitization to a natural reward and vice-versa8,19-21. The extent to which these findings extend to behaviors like gambling warrants additional investigation. All drugs of abuse affect the brain's “reward circuit,” with the mesolimbic dopamine pathway being of particular importance. This pathway includes dopaminergic neurons extending from the ventral tegmental area to the nucleus accumbens (NAc)22-25. Dopamine levels that are either too high or too low are suboptimal and may lead to impulsive and risk-taking acts including excessive substance use26. Natural rewards and abused substances appear to induce similar activity in reward circuitry and connected regions, including the amygdala, hippocampus and frontal cortex8.
Genetic and family history findings, albeit limited for behavioral addictions, provide further evidence of commonality between behavioral and substance addictions27. Co-morbidity among behavioral and substance addictions and other psychiatric conditions appears to involve shared genetic factors15,27-30.
The present review considers neurobiological and genetic/family history evidence pertaining to behavioral addictions. After describing our methods, we discuss brain function (Table 1), neurotransmitter systems (Table 2) and family history/genetic findings (Table 3) relating to six behavioral addictions: pathological gambling primarily; problematic Internet use and video-game playing secondarily; and thirdly, compulsive shopping, kleptomania and hypersexuality. We highlight similarities and differences with substance addiction findings, describe conclusions and offer suggestions for future research. Epidemiology and clinical findings are addressed briefly; however, several recent reviews2,31 and an edited volume14 have addressed these topics. We excluded studies involving only healthy or Parkinson's Disease (PD) participants. While PD studies provide a useful model for behavioral addictions, the extent to which these findings apply to the larger population of non-PD patients is uncertain (see 32,33).
Literature searches were conducted in May 2012 using Medline and Google Scholar. Each search was conducted using a general search term (neuro*, MRI, PET, imaging and genet*) and a search term for one of the following behavioral addictions (search terms in parentheses): gambling (gambl*), shopping (compulsive shopping, shopping addict*, compulsive buying), kleptomania (kleptomania, steal), sexual behavior (compulsive sex*, sex* addict*), internet (internet addict*, compulsive internet) and video game play (video gam*). Given space limitations and the multiple topics reviewed, data deemed most relevant are covered.
Neurobiological responses to cue induction and behavioral tasks assessing cognitive control, simulated gambling, impulse control, risk/reward decision-making and reward processing have been reported in PG. Findings demonstrating similarities and differences between PG and substance addictions have been reviewed recently18.
Most neuroimaging studies have implicated frontal cortical areas and the striatum, as well as other regions. Generally, findings regarding brain function underlying cognitive tasks have been more consistent than cue-induction findings.
Cue-induction studies suggest dysfunction in frontal areas, although the precise nature of the dysfunction is unclear. In cue-exposure tasks, PG (versus control) participants have shown reduced activation in ventrolateral and ventromedial prefrontal cortices (vlPFC and vmPFC7,34), although other cue-presentation studies in problem gamblers35 and PG36 have shown increased frontal activations. Apparent differences in findings across studies may relate to task design and analytic approaches. Studies with imaging conducted during cognitive tasks have more consistently shown decreased activity in frontal areas such as the vmPFC in PG37-40 although increased frontal activation in problem/PG has also been reported41,42.
Multiple studies implicate the striatum in PG. Decreased ventral striatal glucose metabolism and increased metabolism in the dorsal striatum at resting state have been found among PG patients with co-morbid bipolar disorder43. However, in PET (positron emission tomography) studies at resting state, no significant differences have been found between PG and healthy controls in D2-like receptor44,45 or serotonin 1B receptor availability in the ventral and dorsal striata, although in the latter case receptor availability correlated with problem-gambling severity in ventral striatum/pallidum46. In functional-magnetic-resonance-imaging (fMRI) studies during gambling-cue exposure, decreased activation has been observed in the ventral7 and dorsal striatum47 in PG (versus controls); however, there have also been negative results in the ventral striatum in PG/problem gambling samples35,36. Regarding activity associated with task performance, most findings indicate decreased ventral activity in PG (versus non-PG)38,40,48 with some evidence of elevated dorsal activity42,48. Some differences in findings among studies are likely attributable to the specific tasks used. Also, differences pertaining to ventral striatal activity may relate to subject groups as some studies involve problem gambling49 or mixed problem gambling/PG groups41 who may have different biological responses. Findings from Linnet et al.44,45 suggest individual differences in that the PG sample was divided about evenly between those who showed and did not show elevated dopamine release in the ventral striatum during the Iowa Gambling Task. Limited findings with tasks related to impulsivity have not shown significant differences in striatal activation between PG and controls50,51.
Regarding other brain regions, PG subjects (versus controls) differ in ACC activity following gambling-cue exposure7,34. Relatively diminished insular activation in PG during cue presentation7 and reward processing has been reported40. Relatively poor white matter integrity has been related to impulsivity52 and has been found among those with PG compared to controls in areas including the corpus collosum53,54. Negative results have been found for white and gray matter volume differences between PG and controls53.
In summary, most imaging findings in PG have implicated frontal cortical areas and the striatum. Tasks relating to risk/reward, gambling and cognitive control typically show reduced activity in PG in frontal areas and ventral striatum more consistently. Early results suggest reduced insula activity and poor white matter integrity in PG.
Most findings relate to dopamine and serotonin, although other neurotransmitters have been implicated. While dopamine dysfunction has been hypothesized for PG55, findings have been less conclusive. Data44,45 suggest individual differences in PG and control groups in dopamine release during the Iowa Gambling Task but no baseline between-group differences regarding D2-like receptor availability. Although PG and control groups showed similar dopamine release during slot-machine-task performance, dopamine release correlated with problem-gambling severity in PG.56 Amphetamine administration increased motivations to gamble among problem gamblers57. The D2-like antagonist haloperidol has also been associated with increased gambling motivations in PG58, although individual differences appear important59. Individual differences may explain negative clinical-trial findings with D2-like antagonist drugs60,61.
Findings from neurochemical studies with varied methods suggest differences in serotonergic function between PG subjects and controls18,62-67. Clinical-trial findings involving serotonin-reuptake inhibitors (SRIs) and a 5HT2-receptor antagonist have been negative or mixed though60,61,68-72. While neurochemical studies indicate serotonergic dysfunction in PG, mixed clinical findings suggest important individual differences.
Regarding other neurotransmitters, multiple positive clinical-trial findings with opiate antagonists73-76 (see 77 for negative results) suggest opioidergic involvement in PG. Preliminary evidence of efficacy for medications that alter glutamate neurotransmission78,79 suggest that glutamate may contribute to impulsive and compulsive behaviors and treatment outcome in PG79. Elevated levels of adrenergic agents and their metabolites have been observed in PG80,81. Norepinephrine levels increase in problem gamblers during gambling82. Blunted growth hormone responses to clonidine has been observed in PG83, which may reflect elevated noradrenergic secretion.
Twin studies suggest that genetic factors may contribute more than environment factors to gambling problems15,84,85. PG heritability estimates range from 50-60%15, with increasing genetic contributions seen with greater problem-gambling severity86. Molecular studies find small, additive effects across multiple genes87. Associations between PG and genetic variants related to dopamine transmission (e.g., DRD2) have been found88-92 (but see93 for negative results). A variant in the serotonin-transporter-gene promoter region (5-HTTLPR) has been associated with PG in males94 and monoamine oxidase A (MAO-A) among males with severe PG95,96. These studies have multiple limitations relating to sample size, sample characterization and analytic approaches, and these factors may relate to inconsistencies in replication.
In a resting-state fMRI study, increased regional homogeneity was found among compulsive internet users in frontal areas (e.g., superior frontal gyrus) and other regions (e.g., parahippocampus). Increased regional homogeneity may reflect greater synchronization among these regions. Given that many of the implicated regions are components of the “reward circuit,” these findings intimate enhanced sensitivity to reward among compulsive internet users97.
In a small, resting-state fMRI and PET study, reduced D2-like receptor availability was found in the dorsal striatum, with negative correlations between binding potential in this region and self-reported internet addiction measures. No evidence of dysfunction in the ventral striatum was found98.
Regarding other brain regions, the ACC was implicated in the aforementioned study of increased resting-state regional homogeneity among compulsive internet users97. Poor white-matter integrity and gray-matter density/volume differences have been seen in compulsive internet users (versus controls). Using diffusion-tensor imaging (DTI), lower FA in orbitofrontal cortex, corpus collosum and cingulum was seen in compulsive internet users (versus controls)99. Using MRI, lower gray-matter density was found in regions tied to emotion regulation including the ACC, posterior cingulate, insula and lingual gyrus100. In a separate study, reduced FA values were found in the parahippocampal gyrus101 and decreased volume observed in the cerebellum, orbitofrontal cortex, dorsolateral prefrontal cortex (dlPFC) and ACC. Regional gray matter volumes correlated inversely with duration of internet addiction101. These findings intimate that compulsive internet use may induce gray-matter reductions or that individuals with low gray-matter volumes may be predisposed to internet addiction.
In summary, early findings suggest regional homogeneity in frontal areas, reduced D2-like receptor availability in the dorsal striatum, poor white-matter integrity and gray-matter density/volume differences affecting regions implicated in reward and emotion processing.
In a small SPECT study, the dopamine transporter appeared to be expressed at lower levels in the striatum among young adult males with compulsive internet use, compared to controls102. In terms of clinical-trials results, there have been no controlled pharmacotherapy studies5.
Harm-avoidant problem internet users more frequently carried the short allele of a variant in the promoter region of the gene coding for the serotonin transporter (SS-5-HTTLPR), an allele also common among depressed patients103.
We have separated findings concerning video-gaming from those pertaining to internet use. However, neurobiological research on compulsive video-gaming typically involves web-based games; thus, video-game findings cannot be separated clearly from internet findings.
Using resting-state PET, increased metabolism was found in the middle orbitofrontal gyrus, which might reflect compensatory cognitive processing104. Reduced metabolism was found in the precentral gyrus, which might reflect insensitivity to negative consequences104. In cue-exposure studies, greater pre- and post-cue changes indicative of increased activity were observed in compulsive internet users (versus controls) in the orbitofrontal cortex (OFC), medial frontal cortex and dlPFC105. In a subsequent study, greater pre-/post-cue changes were observed in the dlPFC among current compulsive players compared with controls106. Pre- and post-treatment fMRI during cue-induction was incorporated into an open-label bupropion trial107. Similar to other studies, stronger activity was found in the dlPFC (versus controls), with dlPFC activity declining after the 6-week treatment period. In an fMRI study tied to a computer-based guessing task involving monetary wins and losses, greater activation in the OFC was found on win trials among compulsive internet users, attributed to higher reward sensitivity108.
Regarding striatal activity, increased metabolism was found in the left caudate104. Greater activity post-cue induction was found in the right NAc and right caudate in compulsive game-players compared to controls during fMRI105.
The ACC and insula have also been implicated in compulsive video-gaming. In a cue-induction fMRI study106, greater activity post-cue was found in the ACC among compulsive gamers. During a reward processing guessing task, decreased ACC activation was found during loss trials in compulsive video-gamers (versus controls), suggesting hypo-sensitivity to loss108. Increased insular activity was found at rest104. Compulsive game-players demonstrated increased volume in the thalamus but decreased volume in the inferior temporal, right middle and left inferior occipital gyri109.
In summary, findings in samples of predominantly young male compulsive game-players suggest increased activity at rest, to cues and during reward processing in frontal areas, the striatum and other regions, and reduced sensitivity to loss outcomes. Findings of increased activity seem to run counter to multiple PG study findings. Areas implicated in compulsive video-gaming appear to contribute to reward processing, impulse control and memory.
Limited molecular genetic research has been performed. Allelic variants of the DRD2 Taq1A1 allele that have been associated with altered dopamine signaling have been suggested to contribute to compulsive video-gaming. Amongst male gamers, the Taq1A1 allele was related to higher self-reported reward dependence110. Variants of the gene encoding catechol-o-methyl transferase (COMT) that have been implicated in dopamine transmission and addictions111 have also been reported to be more prevalent among compulsive gamers110.
In a recent study112, compulsive shoppers and healthy controls were compared on a multi-phase purchasing task113 during fMRI. During an initial product presentation phase, compulsive shoppers showed stronger activity in the NAc than did controls. During a subsequent price presentation phase, compulsive shoppers showed less activation of the insula and ACC than did controls, the latter of which was activated more strongly by compulsive buyers during the concluding decision phase.
Favorable results were seen with citalopram in a small open-label trial114. A subsequent small trial beginning with an open-label period followed by double-blind, placebo-controlled administration among responders yielded additional positive results for citalopram115. These findings provided tentative support for possible serotonergic dysfunction in compulsive shopping. However, negative results with other SRIs (e.g., fluvoxamine,116,117 escitalopram118) raise questions about the clinical utility of SRIs for compulsive shopping.
Limited data suggest that compulsive shoppers are more likely to have close family members with psychopathology119,120. No differences were seen in the frequencies of two serotonin transporter gene (5-HTT) polymorphisms in individuals with and without compulsive shopping121.
Relatively poor white-matter integrity in ventromedial prefrontal cortical regions was seen in kleptomania122.
Findings regarding serotonergic dysfunction have been inconsistent. Lower numbers of platelet-derived serotonin transporters have been reported in kleptomania123,124, suggesting serotonergic dysfunction; however, negative findings from a small double-blind, placebo-controlled clinical trial involving open-label responders were reported for escitalopram125. Positive results in a small double-blind trial of naltrexone126 suggest possible opioidergic involvement.
Studies of sexual compulsivity have been limited. In a DTI study129, individuals with sexual compulsivity had relatively low superior frontal region mean diffusivity compared to controls. These findings did not follow patterns of results from studies of other behavioral addictions53,54,99,101,122.
Positive results for citalopram in a double-blind placebo controlled study of compulsive sexual behavior in homosexual and bisexual men suggest possible serotonergic dysfunction130.
Limited findings suggest a high proportion of those with compulsive sexual behavior had a parent with a similar condition131. Findings indicate tendencies for sexually compulsive individuals to have first-degree relatives with substance-use disorders (SUDs)131.
Neurobiological findings in the behavioral addictions remain scant and data are particularly sparse for compulsive shopping, kleptomania and compulsive sexual behaviors. However, available data provide evidence of underlying neurobiological impairment overall, which parallels SUD findings. Tables 1, ,22 and and33 contain information comparing behavioral addiction with SUDs.
Findings of poorer white-matter integrity have perhaps been the most complementary between substance132,133 and behavioral addictions53,54,99,101,122 (but see129 for seemingly conflicting results). Cognitive-task results in SUDs50,51,134,135 and PG40,50,51,136 have suggested reduced activity in frontal areas. Findings involving aspects of risk/reward decision-making (including reward processing), but arguably less so from response-impulsivity tasks, have tended to show reduced ventral-striatal activity in PG38,40,48 and SUDs137-140, although there have been seemingly opposing results41,141,142. Findings have tended to show increased activity in the dorsal striatum in behavioral addictions43,48 and SUDs143,144.
Evidence regarding neurotransmitter activity in behavioral addictions and SUDs has tended to be complementary. Neurochemical evidence has suggested reduced dopamine transporter and D2-like receptor availability at rest98,102,145,146 and dopamine release during activity related to addictive behavior147,148, although there have been seemingly conflicting results at resting state in PG44,45 and SUDs149, and individual differences seem relevant to dopamine release44,45,150. Neurochemical findings suggest differential serotonergic function compared to controls among those with behavioral addictions62-66,124 and SUDs151-153. Clinical results with dopamine antagonists60,61,154-156 and medications targeting serotonin systems (primarily SRIs68-72,157-159) have demonstrated negative or mixed findings in behavioral addictions and SUDs. Clinical results involving opioid antagonists have tended to be positive for both types of conditions40,45,73-76,126,160-162. Limited results with pharmacologic probes suggest a role for glutamatergic activity in PG78,79 and SUDs163,164. Neurochemical and clinical findings suggest a possible role for norandrenergic activity in PG80-83 and SUDs165-167.
Genetic (especially molecular) and family-history evidence is limited for behavioral addictions. However, available evidence suggests substantial heritability for PG15,84. For other behavioral addictions, there is evidence suggesting familial risk across psychiatric conditions71,110,119,120,127,128,131. SUDs appear highly heritable as well27,168.
Evidence from cue-induction and resting-state imaging studies have been less clear and seemingly more conflicting. Resting-state and cue-induction findings in compulsive video-gaming have suggested increased activity across multiple brain regions104-106,169. There have been seemingly conflicting results in problem/PG and SUD cue-induction studies for both ventral striatal (gambling7,35; SUD7,143,144,170) and frontal activity171,172. Differences across studies in participant characteristics and other methodological details may contribute to these differing results171,172. In addition, declines in dopamine release in response to drug consumption as dependence worsens173 may also lead to heterogeneity in ventral-striatal activity across participants in SUD studies.
In summary, data suggest neurobiological dysfunction in behavioral addictions and SUDs. Some of the more complementary results have involved white-matter integrity, brain function during cognitive-task performance, neurotransmitter activity and overall heritability.
Research on the neurobiology and genetics of behavioral addictions has accelerated in recent years, particularly in PG, compulsive internet use and compulsive video-gaming. Gaps in knowledge remain and research on other behavioral addictions has been limited. Existing research suggests parallels between behavioral addictions and SUDs. Additional genetic research, particularly molecular, would be valuable in delineating similarities and differences among individual behavioral addictions and between behavioral addictions and SUDs. Neuroimaging has begun to provide insight regarding similarities and differences. Additional research is needed, incorporating a broader variety of cognitive tasks174. While conventional approaches have been valuable, alternative analytic methods such as computational modeling174 may further illustrate parallels with SUDs.
Research testing medications and therapies indicated for SUDs has only begun. Studies involving individuals with co-occurring behavioral and substance addictions could enhance our understanding of addiction and advance treatment development. Females are often excluded from or under-represented in behavioral addiction studies, particularly in existing genetic studies and research on compulsive video-gaming. Future studies should include females and examine the extent to which various phenomena pertaining to behavioral addictions apply to both genders.
Given that behavioral addictions, particularly those relating to gambling, internet use and video-gaming, appear relevant to adolescents and young adults2,101,110, longitudinal studies would be valuable. Epidemiologic data are limited for behavioral addictions with the possible exception of PG. National and international studies assessing prevalence of multiple behavioral addictions would enhance our knowledge regarding the extent to which these conditions affect people across the lifespan. Uniformly agreed-upon diagnostic criteria and assessment instruments would facilitate comparisons across studies.
This work was supported in part by the NIH (K01 AA 019694, K05 AA014715, R01 DA019039, P20 DA027844, RC1 DA028279, RL1 AA017539), the VA VISN1 MIRECC, the Connecticut Department of Mental Health and Addiction Services and a Center of Research Excellence Award from the National Center for Responsible Gaming and its affiliated Institute for Research on Gambling Disorders. The contents of the manuscript are solely the responsibility of the authors and do not necessarily represent the official views of any of the funding agencies.
Disclosures: The authors report that they have no financial conflicts of interest with respect to the content of this manuscript. Dr. Potenza has received financial support or compensation for the following: Dr. Potenza has consulted for and advised Boehringer Ingelheim; has consulted for and has financial interests in Somaxon; has received research support from the National Institutes of Health, Veteran's Administration, Mohegan Sun Casino, the National Center for Responsible Gaming and its affiliated Institute for Research on Gambling Disorders, and Psyadon, Forest Laboratories, Ortho-McNeil, Oy-Control/Biotie and Glaxo-SmithKline pharmaceuticals; has participated in surveys, mailings or telephone consultations related to drug addiction, impulse control disorders or other health topics; has consulted for law offices and the federal public defender's office in issues related to impulse control disorders; provides clinical care in the Connecticut Department of Mental Health and Addiction Services Problem Gambling Services Program; has performed grant reviews for the National Institutes of Health and other agencies; has guest-edited journal sections; has given academic lectures in grand rounds, CME events and other clinical or scientific venues; and has generated books or book chapters for publishers of mental health texts.