Why Porn Is The Mother Of All Internet Addictions
Sunday, September 1, 2024.
In my practice, many clients come to me grappling with the emotional impact of a partner's persistent use of pornography.
The feelings of frustration, sadness, and even betrayal can run deep, often leaving a significant strain on the relationship.
It’s essential to understand the underlying neural mechanisms driving such behaviors to help couples navigate these challenging dynamics and ultimately rebuild trust and intimacy.
One of the ways Limbic Capitalism controls us is by shaping research.
For example, when establishing criteria for new behavioral addictions, we’re reminded that diagnosing addictions to ordinary human behaviors is tricky.
We’re warned how important to be careful not to over-diagnose or label everyday challenges as disorders.
Prevailing opinion has suggested that behavioral addictions should be grounded on clinical relevance (Criterion 1), how well the behavior aligns with addiction patterns (Criterion 2), established theories (Criterion 3), and whether it makes sense within existing classifications (Criterion 4).
Based on these guidelines, we’ve been confidently told that there isn't enough evidence yet to classify pornography use or buying-shopping behaviors as addictions.
But Good Science doesn’t lie.
Recent research provides valuable insights into why pornography can be so difficult to manage.
A study published in Human Brain Mapping reveals that pornographic stimuli trigger stronger reward responses in the brain compared to other stimuli, such as monetary rewards or gaming (Brand et al., 2022).
This heightened activation of the brain’s reward system explains why some folks find it particularly challenging to reduce or eliminate their use of pornography.
By integrating these findings into therapy, we can help clients better understand and manage these behaviors, paving the way for healing within the relationship.
Understanding the Brain's Reward System and Internet Addiction
The brain's reward system plays a central role in internet addiction, including excessive pornography use.
When engaging in rewarding activities like viewing pornography, the brain releases dopamine, a neurotransmitter that reinforces the behavior by providing a pleasurable sensation.
Over time, repeated exposure to high-reward stimuli can make it increasingly difficult for individuals to experience pleasure from other activities, leading to compulsive use—a hallmark of addiction.
Signs of Internet Addiction: It’s important to recognize the signs that internet use has crossed into addiction:
Increased tolerance: Needing more time or more explicit material to achieve the same level of satisfaction.
Withdrawal symptoms: Feeling restless, anxious, or irritable when unable to access the internet or pornography.
Loss of control: Struggling to reduce or stop the behavior, despite wanting to.
Neglect of responsibilities: Allowing internet use to interfere with work, school, or relationships.
Preoccupation: Constant thoughts about the next opportunity to use the internet or view pornography.
The Role of Cognitive-Behavioral Therapy in Managing Pornography Use
Cognitive-behavioral therapy (CBT) is a powerful approach for managing pornography use because it addresses both the thoughts and behaviors that contribute to addiction.
Cognitive Restructuring: This technique helps clients identify and challenge distorted thinking patterns that drive their behavior. For example, if a client believes that pornography is the only way to relax, CBT can help them explore and adopt healthier coping mechanisms.
Behavioral Interventions: These interventions might include setting limits on internet use, avoiding triggers, and substituting pornography with other rewarding activities like physical exercise or social interactions, which can also activate the brain’s reward system.
How Mindfulness Practices Support Recovery from Pornography Addiction
Mindfulness practices are incredibly beneficial in recovery from pornography addiction because they help clients develop a greater awareness of their thoughts, emotions, and physical sensations without immediately reacting to them. This heightened awareness allows individuals to recognize triggers and cravings as they arise, giving them the space to choose a healthier response.
Mindfulness Techniques: Incorporating mindfulness into therapy might involve deep breathing exercises, body scans, and mindful meditation. These practices help clients become more attuned to their internal states, making it easier to manage cravings and reduce reliance on pornography.
Stress Management: Mindfulness also aids in stress reduction, which is crucial because stress often exacerbates addictive behaviors. By managing stress more effectively, clients are less likely to turn to pornography as a coping mechanism.
Addressing the Impact of Pornography Use in Couples Therapy
Pornography use doesn’t just affect the individual; it may also hold profound implications for relationships. Couples therapy is essential in addressing how one partner’s internet-use behaviors impact their relationship and in facilitating healing.
Effective Ways to Discuss Pornography Use with a Partner: Open, honest communication is the cornerstone of rebuilding trust. Here’s how to approach this delicate conversation:
Choose the Right Time: Ensure that the conversation happens when both partners are calm and not rushed, creating a space for constructive dialogue.
Use “I” Statements: Focus on expressing your feelings and concerns without assigning blame. For instance, saying “I feel hurt when you watch pornography because it makes me feel disconnected” can open up a more empathetic conversation.
Be Open to Listening: Encourage your partner to share their perspective, and listen with empathy, without interrupting or judging.
Set Mutual Goals: Work together to establish boundaries and goals regarding internet and pornography use. This might involve agreeing on when and how the internet is used or seeking support together to make positive changes.
Rebuilding Trust After Addressing Pornography Use
Rebuilding trust after a breach, such as the discovery of a partner’s pornography use, is a delicate but essential process. Trust is the foundation of any relationship, and without it, intimacy can falter. However, with patience, understanding, and consistent effort, trust can be restored.
Open Communication: The first step in rebuilding trust is fostering open and honest communication. The partner who has used pornography must be transparent about their behavior and willing to listen to the hurt partner’s feelings and concerns. It’s crucial that both partners feel heard and understood.
Setting Clear Boundaries: Establishing clear boundaries around internet use can help both partners feel secure and respected. These boundaries should be mutually agreed upon and revisited regularly to ensure they continue to meet the needs of both partners.
Accountability: Rebuilding trust requires consistent action. Incorporating accountability measures, such as regular check-ins or using internet monitoring tools, can help the partner who has used pornography demonstrate their commitment to change. These tools should be used to provide reassurance and support rather than control.
Empathy and Understanding: Both partners need to practice empathy. The partner who used pornography should acknowledge the hurt caused and strive to understand the emotional impact on their partner. The other partner, in turn, should try to understand the underlying issues that led to the behavior. This mutual understanding is key to healing.
Therapeutic Support: Couples therapy provides a safe space to explore the underlying issues and work through the emotions involved. It can guide the couple in developing strategies to rebuild trust and prevent future issues, helping to strengthen their bond.
Patience and Consistency: Rebuilding trust doesn’t happen overnight. It requires patience, consistent effort, and time. Both partners must be committed to the process, and over time, as trust is gradually restored, the relationship can become more resilient and connected.
How Can Couples Rebuild Intimacy After Addressing Pornography Use?
Rebuilding intimacy after addressing pornography use is a critical step in the healing process for couples. Intimacy goes beyond physical connection—it encompasses emotional closeness, trust, and mutual respect. When pornography use has damaged this bond, it’s important to focus on reconnecting both emotionally and physically.
Emotional Reconnection: Start by prioritizing emotional intimacy. This can be achieved through regular, meaningful conversations where both partners share their feelings, fears, and hopes for the future. Engaging in activities that foster closeness, such as spending quality time together or trying new experiences as a couple, can also help rebuild emotional bonds.
Physical Intimacy: Rebuilding physical intimacy might take time, especially if one partner feels hurt or betrayed. Begin with small gestures of affection, like holding hands or hugging, and gradually move towards more intimate physical connection as comfort levels increase. It’s important to move at a pace that feels right for both partners.
Being Present: Mindfulness can play a powerful role in rebuilding intimacy. Being fully present during moments of connection—whether emotional or physical—helps deepen the bond between partners. Mindful practices, such as looking into each other’s eyes, sharing deep breaths, or simply enjoying a quiet moment together, can enhance intimacy.
Rebuilding Trust: As trust is rebuilt through the steps mentioned earlier, it naturally supports the re-establishment of intimacy. When partners feel secure and valued, they are more likely to open up and reconnect on a deeper level.
Seeking Help Together: Sometimes, professional guidance is needed to navigate the complex emotions surrounding intimacy after a breach of trust. Couples therapy can provide tools and strategies to help partners reconnect and build a more intimate and fulfilling relationship.
Broader Therapeutic Approaches
Motivational Interviewing (MI): MI is a powerful tool for helping clients explore their reasons for wanting to change their internet-use behaviors. By discussing the pros and cons of their current habits and enhancing their motivation for change, therapists can help clients take meaningful steps toward recovery.
Relapse Prevention Planning: Understanding the brain’s strong reward response to pornography is crucial in developing effective relapse prevention plans. By identifying triggers and teaching coping skills, therapists can help clients manage cravings and prevent relapse, ensuring long-term success.
Final thoughts
Porn is a prime example of Limbic Capitalism at its most predatory encroachment on primal drives.
I hope that as a community of practice we will integrate these neuroscientific insights and therapeutic strategies into more effective therapeutic interventions.
If we focus on countering Limbic Capitalism, we can offer more informed, personalized, and effective interventions.
Understanding the neural mechanisms behind pornography use not only supports clients in managing these behaviors but also improves their mental health and relationship dynamics.
It’s time we pushed back on porn, using the hard science of how deeply it affects the brain, to help individuals and couples rebuild their lives, trust, and intimacy.
Be Well, Stay Kind, and Godspeed.
REFERENCES:
Addiction absorbs a huge amount of research dollars every year.
Love, T., Laier, C., Brand, M., Hatch, L., & Hajela, R. (2015). Neuroscience of Internet Pornography Addiction: A Review and Update. Behavioral Sciences, 5(3), 388-433. https://doi.org/10.3390/bs5030388
White W.L. Slaying the Dragon: The History of Addiction Treatment and Recovery in America. 1st ed. Chestnut Health Systems; Bloomington, IL, USA: 1998. [Google Schola
Pitchers K.K., Vialou V., Nestler E.J., Laviolette S.R., Lehman M.N., Coolen L.M. Natural and drug rewards act on common neural plasticity mechanisms with ΔFosB as a key mediator. J. Neurosci. Off. J. Soc. Neurosci. 2013;33:3434–3442. doi: 10.1523/JNEUROSCI.4881-12.2013. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Nestler E.J. Is there a common molecular pathway for addiction? Nat. Neurosci. 2005;8:1445–1449. doi: 10.1038/nn1578. [PubMed] [CrossRef] [Google Scholar]
Robinson T.E., Berridge K.C. Review. The incentive sensitization theory of addiction: Some current issues. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 2008;363:3137–3146. [PMC free article] [PubMed] [Google Scholar]
Koob G.F., Le Moal M. Neurobiological mechanisms for opponent motivational processes in addiction. Philos. Trans. R. Soc. B Biol. Sci. 2008;363:3113–3123. doi: 10.1098/rstb.2008.0094. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Grant J.E., Brewer J.A., Potenza M.N. The neurobiology of substance and behavioral addictions. CNS Spectr. 2006;11:924–930. [PubMed] [Google Scholar]
Grant J.E., Potenza M.N., Weinstein A., Gorelick D.A. Introduction to behavioral addictions. Am. J. Drug Alcohol Abuse. 2010;36:233–241. doi: 10.3109/00952990.2010.491884. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Olsen C.M. Natural rewards, neuroplasticity, and non-drug addictions. Neuropharmacology. 2011;61:1109–1122. doi: 10.1016/j.neuropharm.2011.03.010. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Karim R., Chaudhri P. Behavioral addictions: An overview. J. Psychoactive Drugs. 2012;44:5–17. doi: 10.1080/02791072.2012.662859. [PubMed] [CrossRef] [Google Scholar]
Leeman R.F., Potenza M.N. A targeted review of the neurobiology and genetics of behavioural addictions: An emerging area of research. Can. J. Psychiatry Rev. Can. Psychiatr. 2013;58:260–273. [PMC free article] [PubMed] [Google Scholar]
American Society of Addiction Medicine (ASAM) Public Policy Statement: Definition of Addiction. [(accessed on 30 June 2015)]. Available online: http://www.asam.org/for-the-public/definition-of-addiction
American Psychiatric Association (APA) Diagnostic and Statistical Manual of Mental Disorders. 5th ed. American Psychiatric Publishing; Arlington, VA, USA: 2013. [Google Scholar]
American Psychiatric Association (APA) Internet Gaming Disorder. [(accessed on 30 June 2015)]. Available online: http://www.dsm5.org/Documents/Internet%20Gaming%20Disorder%20Fact%20Sheet.pdf
Davis R.A. A cognitive-behavioral model of pathological Internet use. Comput. Hum. Behav. 2001;17:187–195. doi: 10.1016/S0747-5632(00)00041-8. [CrossRef] [Google Scholar]
Brand M., Young K.S., Laier C. Prefrontal control and internet addiction: A theoretical model and review of neuropsychological and neuroimaging findings. Front. Hum. Neurosci. 2014;8:375. doi: 10.3389/fnhum.2014.00375. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Griffiths M.D., King D.L., Demetrovics Z. DSM-5 internet gaming disorder needs a unified approach to assessment. Neuropsychiatry. 2014;4:1–4. doi: 10.2217/npy.13.82. [CrossRef] [Google Scholar]
17. Block J.J. Issues for DSM-V: Internet addiction. Am. J. Psychiatry. 2008;165:306–307. doi: 10.1176/appi.ajp.2007.07101556. [PubMed] [CrossRef] [Google Scholar]
18. Yau Y.H.C., Crowley M.J., Mayes L.C., Potenza M.N. Are Internet use and video-game-playing addictive behaviors? Biological, clinical and public health implications for youths and adults. Minerva Psichiatr. 2012;53:153–170. [PMC free article] [PubMed] [Google Scholar]
19. King D.L., Delfabbro P.H. Issues for DSM-5: Video-gaming disorder? Aust. N. Z. J. Psychiatry. 2013;47:20–22. doi: 10.1177/0004867412464065. [PubMed] [CrossRef] [Google Scholar]
20. Potenza M.N. Non-substance addictive behaviors in the context of DSM-5. Addict. Behav. 2014;39:1–2. doi: 10.1016/j.addbeh.2013.09.004. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Wittmann B.C., Bunzeck N., Dolan R.J., Düzel E. Anticipation of novelty recruits reward system and hippocampus while promoting recollection. NeuroImage. 2007;38:194–202. doi: 10.1016/j.neuroimage.2007.06.038. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Costa V.D., Tran V.L., Turchi J., Averbeck B.B. Dopamine modulates novelty seeking behavior during decision making. Behav. Neurosci. 2014;128:556–566. [PMC free article] [PubMed] [Google Scholar
Spicer J., Galvan A., Hare T.A., Voss H., Glover G., Casey B. Sensitivity of the nucleus accumbens to violations in expectation of reward. NeuroImage. 2007;34:455–461. doi: 10.1016/j.neuroimage.2006.09.012. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Hilton D.L. Pornography addiction—A supranormal stimulus considered in the context of neuroplasticity. Socioaffective Neurosci. Psychol. 2013;3:20767. doi: 10.3402/snp.v3i0.20767. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Tinbergen N. The Study of Instinct. Clarendon Press; Oxford, UK: 1989. [Google Scholar]
Barrett D. Supernormal Stimuli: How Primal Urges Overran Their Evolutionary Purpose. 1st ed. W.W. Norton & Company; New York, NY, USA: 2010. [Google Scholar]
27. Toates F. How Sexual Desire Works: The Enigmatic Urge. Cambridge University Press; Cambridge, UK: 2014. [Google Scholar]
28. Downing M.J., Antebi N., Schrimshaw E.W. Compulsive use of Internet-based sexually explicit media: Adaptation and validation of the Compulsive Internet Use Scale (CIUS) Addict. Behav. 2014;39:1126–1130. doi: 10.1016/j.addbeh.2014.03.007. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Meerkerk G.-J., Van Den Eijnden R.J.J.M., Garretsen H.F.L. Predicting compulsive Internet use: it’s all about sex! Cyberpsychology Behav. Impact Internet Multimed. Virtual Real. Behav. Soc. 2006;9:95–103. doi: 10.1089/cpb.2006.9.95. [PubMed] [CrossRef] [Google Scholar]
Meerkerk G.-J., van den Eijnden R.J.J.M., Franken I.H.A., Garretsen H.F.L. Is compulsive internet use related to sensitivity to reward and punishment, and impulsivity? Comput. Hum. Behav. 2010;26:729–735. doi: 10.1016/j.chb.2010.01.009. [CrossRef] [Google Scholar]
Meerkerk G.-J., Van Den Eijnden R.J.J.M., Vermulst A.A., Garretsen H.F.L. The Compulsive Internet Use Scale (CIUS): Some psychometric properties. Cyberpsychology Behav. Impact Internet Multimed. Virtual Real. Behav. Soc. 2009;12:1–6. doi: 10.1089/cpb.2008.0181. [PubMed] [CrossRef] [Google Scholar]
Quiñones-García C., Korak-Kakabadse N. Compulsive internet use in adults: A study of prevalence and drivers within the current economic climate in the UK. Comput. Hum. Behav. 2014;30:171–180. doi: 10.1016/j.chb.2013.08.004. [CrossRef] [Google Scholar]
Derbyshire K.L., Grant J.E. Compulsive Sexual Behavior: A Review of the Literature. J. Behav. Addict. 2015;4:37–43. doi: 10.1556/2006.4.2015.003. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Tao R., Huang X., Wang J., Zhang H., Zhang Y., Li M. Proposed diagnostic criteria for internet addiction. Addict. Abingdon Engl. 2010;105:556–564. doi: 10.1111/j.1360-0443.2009.02828.x. [PubMed] [CrossRef] [Google Scholar]
King D.L., Haagsma M.C., Delfabbro P.H., Gradisar M., Griffiths M.D. Toward a consensus definition of pathological video-gaming: A systematic review of psychometric assessment tools. Clin. Psychol. Rev. 2013;33:331–342. doi: 10.1016/j.cpr.2013.01.002. [PubMed] [CrossRef] [Google Scholar]
Carli V., Durkee T., Wasserman D., Hadlaczky G., Despalins R., Kramarz E., Wasserman C., Sarchiapone M., Hoven C.W., Brunner R., Kaess M. The association between pathological internet use and comorbid psychopathology: a systematic review. Psychopathology. 2013;46:1–13. doi: 10.1159/000337971. [PubMed] [CrossRef] [Google Scholar]
Jelenchick L.A., Eickhoff J., Christakis D.A., Brown R.L., Zhang C., Benson M., Moreno M.A. The Problematic and Risky Internet Use Screening Scale (PRIUSS) for Adolescents and Young Adults: Scale Development and Refinement. Comput. Hum. Behav. 2014;35:171–178. doi: 10.1016/j.chb.2014.01.035. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Jung Y.-E., Leventhal B., Kim Y.S., Park T.W., Lee S.-H., Lee M., Park S.H., Yang J.-C., Chung Y.-C., Chung S.-K., Park J.-I. Cyberbullying, problematic internet use, and psychopathologic symptoms among Korean youth. Yonsei Med. J. 2014;55:826–830. doi: 10.3349/ymj.2014.55.3.826. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Lopez-Fernandez O., Honrubia-Serrano M.L., Gibson W., Griffiths M.D. Problematic Internet use in British adolescents: An exploration of the addictive symptomatology. Comput. Hum. Behav. 2014;35:224–233. doi: 10.1016/j.chb.2014.02.042. [CrossRef] [Google Scholar]
Spada M.M. An overview of problematic internet use. Addict. Behav. 2014;39:3–6. doi: 10.1016/j.addbeh.2013.09.007. [PubMed] [CrossRef] [Google Scholar]
Yau Y.H.C., Pilver C.E., Steinberg M.A., Rugle L.J., Hoff R.A., Krishnan-Sarin S., Potenza M.N. Relationships between problematic Internet use and problem-gambling severity: Findings from a high-school survey. Addict. Behav. 2014;39:13–21. doi: 10.1016/j.addbeh.2013.09.003. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Yau Y.H.C., Potenza M.N., Mayes L.C., Crowley M.J. Blunted feedback processing during risk-taking in adolescents with features of problematic Internet use. Addict. Behav. 2015;45:156–163. doi: 10.1016/j.addbeh.2015.01.008. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Volkow N.D., Wang G.-J., Fowler J.S., Tomasi D., Telang F. Addiction: Beyond dopamine reward circuitry. Proc. Natl. Acad. Sci. 2011;108:15037–15042. doi: 10.1073/pnas.1010654108. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Volkow N.D., Baler R.D. Addiction science: Uncovering neurobiological complexity. Neuropharmacology. 2014;76:235–249. doi: 10.1016/j.neuropharm.2013.05.007. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Koob G.F., Volkow N.D. Neurocircuitry of Addiction. Neuropsychopharmacology. 2010;35:217–238. doi: 10.1038/npp.2009.110. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Ley D., Prause N., Finn P. The Emperor Has No Clothes: A Review of the “Pornography Addiction” Model. Curr. Sex. Health Rep. 2014;6:94–105. doi: 10.1007/s11930-014-0016-8. [CrossRef] [Google Scholar]
47. Van Rooij A.J., Prause N. A critical review of “Internet addiction” criteria with suggestions for the future. J. Behav. Addict. 2014;3:203–213. doi: 10.1556/JBA.3.2014.4.1. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
48. Goldstein R.Z., Volkow N.D. Dysfunction of the prefrontal cortex in addiction: Neuroimaging findings and clinical implications. Nat. Rev. Neurosci. 2011;12:652–669. doi: 10.1038/nrn3119. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Ko C.H., Yen J.Y., Yen C.F., Chen C.S., Chen C.C. The association between Internet addiction and psychiatric disorder: A review of the literature. Eur. Psychiatry J. Assoc. Eur. Psychiatr. 2012;27:1–8. doi: 10.1016/j.eurpsy.2010.04.011. [PubMed] [CrossRef] [Google Scholar]
Limbrick-Oldfield E.H., van Holst R.J., Clark L. Fronto-striatal dysregulation in drug addiction and pathological gambling: Consistent inconsistencies? NeuroImage Clin. 2013;2:385–393. doi: 10.1016/j.nicl.2013.02.005. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Koob G.F. Negative reinforcement in drug addiction: The darkness within. Curr. Opin. Neurobiol. 2013;23:559–563. doi: 10.1016/j.conb.2013.03.011. [PubMed] [CrossRef] [Google Scholar]
Solomon R.L., Corbit J.D. An opponent-process theory of motivation. I. Temporal dynamics of affect. Psychol. Rev. 1974;81:119–145. [PubMed] [Google Scholar]
Franklin J.C., Hessel E.T., Aaron R.V., Arthur M.S., Heilbron N., Prinstein M.J. The functions of nonsuicidal self-injury: Support for cognitive-affective regulation and opponent processes from a novel psychophysiological paradigm. J. Abnorm. Psychol. 2010;119:850–862. doi: 10.1037/a0020896. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Hyman S.E., Malenka R.C., Nestler E.J. Neural mechanisms of addiction: The role of reward-related learning and memory. Annu. Rev. Neurosci. 2006;29:565–598. doi: 10.1146/annurev.neuro.29.051605.113009. [PubMed] [CrossRef] [Google Scholar]
Everitt B.J., Robbins T.W. Neural systems of reinforcement for drug addiction: From actions to habits to compulsion. Nat. Neurosci. 2005;8:1481–1489. doi: 10.1038/nn1579. [PubMed] [CrossRef] [Google Scholar]
Everitt B.J., Robbins T.W. From the ventral to the dorsal striatum: Devolving views of their roles in drug addiction. Neurosci. Biobehav. Rev. 2013;37:1946–1954. doi: 10.1016/j.neubiorev.2013.02.010. [PubMed] [CrossRef] [Google Scholar]
Robinson T.E., Berridge K.C. The neural basis of drug craving: An incentive-sensitization theory of addiction. Brain Res. Brain Res. Rev. 1993;18:247–291. doi: 10.1016/0165-0173(93)90013-P. [PubMed] [CrossRef] [Google Scholar]
Smith K.S., Berridge K.C., Aldridge J.W. Disentangling pleasure from incentive salience and learning signals in brain reward circuitry. Proc. Natl. Acad. Sci. 2011;108:E255–E264. doi: 10.1073/pnas.1101920108. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Stacy A.W., Wiers R.W. Implicit cognition and addiction: A tool for explaining paradoxical behavior. Annu. Rev. Clin. Psychol. 2010;6:551–575. doi: 10.1146/annurev.clinpsy.121208.131444. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Berridge K.C., Robinson T.E., Aldridge J.W. Dissecting components of reward: “Liking”, “wanting”, and learning. Curr. Opin. Pharmacol. 2009;9:65–73. doi: 10.1016/j.coph.2008.12.014. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Robinson M.J.F., Berridge K.C. Instant transformation of learned repulsion into motivational “wanting” Curr. Biol. 2013;23:282–289. doi: 10.1016/j.cub.2013.01.016. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Swendsen J., Le Moal M. Individual vulnerability to addiction. Ann. N. Y. Acad. Sci. 2011;1216:73–85. doi: 10.1111/j.1749-6632.2010.05894.x. [PubMed] [CrossRef] [Google Scholar]
Volkow N.D., Muenke M. The genetics of addiction. Hum. Genet. 2012;131:773–777. doi: 10.1007/s00439-012-1173-3. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Agrawal A., Verweij K.J.H., Gillespie N.A., Heath A.C., Lessov-Schlaggar C.N., Martin N.G., Nelson E.C., Slutske W.S., Whitfield J.B., Lynskey M.T. The genetics of addiction—A translational perspective. Transl. Psychiatry. 2012;2:e140. doi: 10.1038/tp.2012.54. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Blum K., Noble E.P., Sheridan P.J., Montgomery A., Ritchie T., Jagadeeswaran P., Nogami H., Briggs A.H., Cohn J.B. Allelic association of human dopamine D2 receptor gene in alcoholism. JAMA. 1990;263:2055–2060. doi: 10.1001/jama.1990.03440150063027. [PubMed] [CrossRef] [Google Scholar]
Blum K., Cull J.G., Braverman E.R., Comings D.E. Reward Deficiency Syndrome. Am. Sci. 1996;84:132–145. [Google Scholar]
Blum K., Chen A.L.C., Giordano J., Borsten J., Chen T.J.H., Hauser M., Simpatico T., Femino J., Braverman E.R., Barh D. The addictive brain: All roads lead to dopamine. J. Psychoactive Drugs. 2012;44:134–143. doi: 10.1080/02791072.2012.685407. [PubMed] [CrossRef] [Google Scholar]
Madsen H.B., Brown R.M., Lawrence A.J. Neuroplasticity in addiction: Cellular and transcriptional perspectives. Front. Mol. Neurosci. 2012;5:99. doi: 10.3389/fnmol.2012.00099. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Nestler E.J. Review. Transcriptional mechanisms of addiction: Role of DeltaFosB. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 2008;363:3245–3255. [PMC free article] [PubMed] [Google Scholar]
Nestler E.J. Transcriptional Mechanisms of Drug Addiction. Clin. Psychopharmacol. Neurosci. 2012;10:136–143. doi: 10.9758/cpn.2012.10.3.136. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Nestler E.J., Barrot M., Self D.W. DeltaFosB: A sustained molecular switch for addiction. Proc. Natl. Acad. Sci. U. S. A. 2001;98:11042–11046. doi: 10.1073/pnas.191352698. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Robison A.J., Nestler E.J. Transcriptional and epigenetic mechanisms of addiction. Nat. Rev. Neurosci. 2011;12:623–637. doi: 10.1038/nrn3111. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Robison A.J., Vialou V., Mazei-Robison M., Feng J., Kourrich S., Collins M., Wee S., Koob G., Turecki G., Neve R., Thomas M., Nestler E.J. Behavioral and structural responses to chronic cocaine require a feedforward loop involving ΔFosB and calcium/calmodulin-dependent protein kinase II in the nucleus accumbens shell. J. Neurosci. Off. J. Soc. Neurosci. 2013;33:4295–4307. doi: 10.1523/JNEUROSCI.5192-12.2013. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Kalivas P.W., O’Brien C. Drug Addiction as a Pathology of Staged Neuroplasticity. Neuropsychopharmacology. 2007;33:166–180. doi: 10.1038/sj.npp.1301564. [PubMed] [CrossRef] [Google Scholar]
75. Lobo D.S.S., Kennedy J.L. The genetics of gambling and behavioral addictions. CNS Spectr. 2006;11:931–939. [PubMed] [Google Scholar]
76. Blum K., Braverman E.R., Holder J.M., Lubar J.F., Monastra V.J., Miller D., Lubar J.O., Chen T.J., Comings D.E. The reward deficiency syndrome: A biogenetic model for the diagnosis and treatment of impulsive, addictive, and compulsive behaviors. J. Psychoactive Drugs. 2000;32:1–112. doi: 10.1080/02791072.2000.10736099. [PubMed] [CrossRef] [Google Scholar]
77. Smith D.E. The process addictions and the new ASAM definition of addiction. J. Psychoactive Drugs. 2012;44:1–4. doi: 10.1080/02791072.2012.662105. [PubMed] [CrossRef] [Google Scholar]
78. Fineberg N.A., Chamberlain S.R., Goudriaan A.E., Stein D.J., Vanderschuren L.J.M.J., Gillan C.M., Shekar S., Gorwood P.A.P.M., Voon V., Morein-Zamir S., et al. New developments in human neurocognition: Clinical, genetic, and brain imaging correlates of impulsivity and compulsivity. CNS Spectr. 2014;19:69–89. [PMC free article] [PubMed] [Google Scholar]
79. Ahmed S.H., Guillem K., Vandaele Y. Sugar addiction: Pushing the drug-sugar analogy to the limit. Curr. Opin. Clin. Nutr. Metab. Care. 2013;16:434–439. doi: 10.1097/MCO.0b013e328361c8b8. [PubMed] [CrossRef] [Google Scholar]
80. Balodis I.M., Grilo C.M., Kober H., Worhunsky P.D., White M.A., Stevens M.C., Pearlson G.D., Potenza M.N. A pilot study linking reduced fronto–Striatal recruitment during reward processing to persistent bingeing following treatment for binge-eating disorder. Int. J. Eat. Disord. 2014;47:376–384. doi: 10.1002/eat.22204. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
81. Balodis I.M., Kober H., Worhunsky P.D., White M.A., Stevens M.C., Pearlson G.D., Sinha R., Grilo C.M., Potenza M.N. Monetary reward processing in obese individuals with and without binge eating disorder. Biol. Psychiatry. 2013;73:877–886. doi: 10.1016/j.biopsych.2013.01.014. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
82. Blum K., Oscar-Berman M., Barh D., Giordano J., Gold M. Dopamine Genetics and Function in Food and Substance Abuse. J. Genet. Syndr. Gene Ther. doi: 10.4172/2157-7412.1000121. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
83. Clark S.M., Saules K.K. Validation of the Yale Food Addiction Scale among a weight-loss surgery population. Eat. Behav. 2013;14:216–219. doi: 10.1016/j.eatbeh.2013.01.002. [PubMed] [CrossRef] [Google Scholar]
84. Gearhardt A.N., Boswell R.G., Potenza M.N. Neuroimaging of Eating Disorders, Substance Use Disorders, and Addictions: Overlapping and Unique Systems. In: Brewerton T.D., Dennis A.B., editors. Eating Disorders, Addictions and Substance Use Disorders. Springer; Berlin, Germany: 2014. pp. 71–89. [Google Scholar]
85. Rodgers R.F., Melioli T., Laconi S., Bui E., Chabrol H. Internet addiction symptoms, disordered eating, and body image avoidance. Cyberpsychol. Behav. Soc. Netw. 2013;16:56–60. doi: 10.1089/cyber.2012.1570. [PubMed] [CrossRef] [Google Scholar]
86. Savage S.W., Zald D.H., Cowan R.L., Volkow N.D., Marks-Shulman P.A., Kessler R.M., Abumrad N.N., Dunn J.P. Regulation of novelty seeking by midbrain dopamine D2/D3 signaling and ghrelin is altered in obesity. Obesity (Silver Spring, Md.) 2014;22:1452–1457. doi: 10.1002/oby.20690. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
87. Tomasi D., Wang G.-J., Wang R., Caparelli E.C., Logan J., Volkow N.D. Overlapping patterns of brain activation to food and cocaine cues in cocaine abusers: Association to striatal D2/D3 receptors. Hum. Brain Mapp. 2015;36:120–136. doi: 10.1002/hbm.22617. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
88. Volkow N.D., Wang G.-J., Tomasi D., Baler R.D. The addictive dimensionality of obesity. Biol. Psychiatry. 2013;73:811–818. doi: 10.1016/j.biopsych.2012.12.020. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
89. Volkow N.D., Wang G.-J., Tomasi D., Baler R.D. Obesity and addiction: Neurobiological overlaps. Obes. Rev. Off. J. Int. Assoc. Study Obes. 2013;14:2–18. doi: 10.1111/j.1467-789X.2012.01031.x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
90. Volkow N.D., Baler R.D. NOW vs LATER brain circuits: Implications for obesity and addiction. Trends Neurosci. 2015;38:345–352. doi: 10.1016/j.tins.2015.04.002. [PubMed] [CrossRef] [Google Scholar]
91. Potenza M.N. Neurobiology of gambling behaviors. Curr. Opin. Neurobiol. 2013;23:660–667. doi: 10.1016/j.conb.2013.03.004. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
92. Potenza M.N. The neurobiology of pathological gambling and drug addiction: An overview and new findings. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2008;363:3181–3189. doi: 10.1098/rstb.2008.0100. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
93. el-Guebaly N., Mudry T., Zohar J., Tavares H., Potenza M.N. Compulsive features in behavioural addictions: The case of pathological gambling. Addict. Abingdon Engl. 2012;107:1726–1734. doi: 10.1111/j.1360-0443.2011.03546.x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
94. Brevers D., Noël X. Pathological gambling and the loss of willpower: A neurocognitive perspective. Socioaffective Neurosci. Psychol. 2013;3:21592. doi: 10.3402/snp.v3i0.21592. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
95. Gyollai A., Griffiths M.D., Barta C., Vereczkei A., Urbán R., Kun B., Kökönyei G., Székely A., Sasvári-Székely M., Blum K., Demetrovics Z. The genetics of problem and pathological gambling: a systematic review. Curr. Pharm. Des. 2014;20:3993–3999. doi: 10.2174/13816128113199990626. [PubMed] [CrossRef] [Google Scholar]
96. Singer B.F., Anselme P., Robinson M.J.F., Vezina P. Neuronal and psychological underpinnings of pathological gambling. Front. Behav. Neurosci. 2014;8:230. doi: 10.3389/fnbeh.2014.00230. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
97. Romanczuk-Seiferth N., Koehler S., Dreesen C., Wüstenberg T., Heinz A. Pathological gambling and alcohol dependence: Neural disturbances in reward and loss avoidance processing. Addict. Biol. 2015;20:557–569. doi: 10.1111/adb.12144. [PubMed] [CrossRef] [Google Scholar]
98. Billieux J. Problematic Use of the Internet and Self-Regulation: A Review of the Initial Studies. Open Addict. J. 2012;5:24–29. doi: 10.2174/1874941001205010024. [CrossRef] [Google Scholar]
99. Gainsbury S., Blaszczynski A. Online self-guided interventions for the treatment of problem gambling. Int. Gambl. Stud. 2011;11:289–308. doi: 10.1080/14459795.2011.617764. [CrossRef] [Google Scholar]
100. Griffiths M.D. Internet sex addiction: A review of empirical research. Addict. Res. Theory. 2011;20:111–124. doi: 10.3109/16066359.2011.588351. [CrossRef] [Google Scholar]
101. King D.L., Delfabbro P.H. Internet gaming disorder treatment: A review of definitions of diagnosis and treatment outcome. J. Clin. Psychol. 2014;70:942–955. doi: 10.1002/jclp.22097. [PubMed] [CrossRef] [Google Scholar]
102. King D.L., Delfabbro P.H., Griffiths M.D., Gradisar M. Assessing clinical trials of Internet addiction treatment: A systematic review and CONSORT evaluation. Clin. Psychol. Rev. 2011;31:1110–1116. doi: 10.1016/j.cpr.2011.06.009. [PubMed] [CrossRef] [Google Scholar]
103. Ko C.-H., Liu G.-C., Yen J.-Y., Yen C.-F., Chen C.-S., Lin W.-C. The brain activations for both cue-induced gaming urge and smoking craving among subjects comorbid with Internet gaming addiction and nicotine dependence. J. Psychiatr. Res. 2013;47:486–493. doi: 10.1016/j.jpsychires.2012.11.008. [PubMed] [CrossRef] [Google Scholar]
104. Kuss D.J., Griffiths M.D. Internet Gaming Addiction: A Systematic Review of Empirical Research. Int. J. Ment. Health Addict. 2011;10:278–296. doi: 10.1007/s11469-011-9318-5. [CrossRef] [Google Scholar]
105. Kuss D.J., Griffiths M.D. Internet and Gaming Addiction: A Systematic Literature Review of Neuroimaging Studies. Brain Sci. 2012;2:347–374. doi: 10.3390/brainsci2030347. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
106. Kuss D.J., Griffiths M.D., Karila L., Billieux J. Internet addiction: A systematic review of epidemiological research for the last decade. Curr. Pharm. Des. 2014;20:4026–4052. doi: 10.2174/13816128113199990617. [PubMed] [CrossRef] [Google Scholar]
107. Lam L.T. Internet gaming addiction, problematic use of the internet, and sleep problems: A systematic review. Curr. Psychiatry Rep. 2014;16:444. doi: 10.1007/s11920-014-0444-1. [PubMed] [CrossRef] [Google Scholar]
108. Li W., Garland E.L., Howard M.O. Family factors in Internet addiction among Chinese youth: A review of English- and Chinese-language studies. Comput. Hum. Behav. 2014;31:393–411. doi: 10.1016/j.chb.2013.11.004. [CrossRef] [Google Scholar]
109. Moreno M.A., Jelenchick L., Cox E., Young H., Christakis D.A. Problematic internet use among US youth: A systematic review. Arch. Pediatr. Adolesc. Med. 2011;165:797–805. doi: 10.1001/archpediatrics.2011.58. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
110. Owens E.W., Behun R.J., Manning J.C., Reid R.C. The Impact of Internet Pornography on Adolescents: A Review of the Research. Sex. Addict. Compulsivity. 2012;19:99–122. doi: 10.1080/10720162.2012.660431. [CrossRef] [Google Scholar]
111. Pezoa-Jares R.E. Internet Addiction: A Review. J. Addict. Res. Ther. S. 2012;6:2. doi: 10.4172/2155-6105.S6-004. [CrossRef] [Google Scholar]
112. Short M.B., Black L., Smith A.H., Wetterneck C.T., Wells D.E. A review of Internet pornography use research: Methodology and content from the past 10 years. Cyberpsychol. Behav. Soc. Netw. 2012;15:13–23. doi: 10.1089/cyber.2010.0477. [PubMed] [CrossRef] [Google Scholar]
113. Sim T., Gentile D.A., Bricolo F., Serpelloni G., Gulamoydeen F. A Conceptual Review of Research on the Pathological Use of Computers, Video Games, and the Internet. Int. J. Ment. Health Addict. 2012;10:748–769. doi: 10.1007/s11469-011-9369-7. [CrossRef] [Google Scholar]
114. Meng Y., Deng W., Wang H., Guo W., Li T. The prefrontal dysfunction in individuals with Internet gaming disorder: A meta-analysis of functional magnetic resonance imaging studies. Addict. Biol. 2015;20:799–808. doi: 10.1111/adb.12154. [PubMed] [CrossRef] [Google Scholar]
115. Weinstein A., Lejoyeux M. New developments on the neurobiological and pharmaco-genetic mechanisms underlying internet and videogame addiction. Am. J. Addict. Am. Acad. Psychiatr. Alcohol. Addict. 2013;24:117–125. doi: 10.1111/j.1521-0391.2013.12110.x. [PubMed] [CrossRef] [Google Scholar]
116. Weinstein A., Lejoyeux M. Internet addiction or excessive internet use. Am. J. Drug Alcohol Abuse. 2010;36:277–283. doi: 10.3109/00952990.2010.491880. [PubMed] [CrossRef] [Google Scholar]
117. Weinstein A.M. Computer and video game addiction-a comparison between game users and non-game users. Am. J. Drug Alcohol Abuse. 2010;36:268–276. doi: 10.3109/00952990.2010.491879. [PubMed] [CrossRef] [Google Scholar]
118. Winkler A., Dörsing B., Rief W., Shen Y., Glombiewski J.A. Treatment of internet addiction: A meta-analysis. Clin. Psychol. Rev. 2013;33:317–329. doi: 10.1016/j.cpr.2012.12.005. [PubMed] [CrossRef] [Google Scholar]
119. Zhu Y., Zhang H., Tian M. Molecular and Functional Imaging of Internet Addiction. Bio. Med. Res. Int. 2015;2015:e378675. doi: 10.1155/2015/378675. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
120. Du W., Liu J., Gao X., Li L., Li W., Li X., Zhang Y., Zhou S. Functional magnetic resonance imaging of brain of college students with internet addiction. Zhongnan Daxue Xuebao Yixue Ban. 2011;36:744–749. [PubMed] [Google Scholar]
121. Han D.H., Hwang J.W., Renshaw P.F. Bupropion sustained release treatment decreases craving for video games and cue-induced brain activity in patients with Internet video game addiction. Exp. Clin. Psychopharmacol. 2010;18:297–304. doi: 10.1037/a0020023. [PubMed] [CrossRef] [Google Scholar]
122. Van Rooij A.J., Schoenmakers T.M., Vermulst A.A., Van den Eijnden R.J.J.M., Van de Mheen D. Online video game addiction: Identification of addicted adolescent gamers. Addict. Abingdon Engl. 2011;106:205–212. doi: 10.1111/j.1360-0443.2010.03104.x. [PubMed] [CrossRef] [Google Scholar]
123. Shek D.T.L., Tang V.M.Y., Lo C.Y. Evaluation of an Internet addiction treatment program for Chinese adolescents in Hong Kong. Adolescence. 2009;44:359–373. [PubMed] [Google Scholar]
124. Zhou Y., Lin F.-C., Du Y.-S., Qin L., Zhao Z.-M., Xu J.-R., Lei H. Gray matter abnormalities in Internet addiction: a voxel-based morphometry study. Eur. J. Radiol. 2011;79:92–95. doi: 10.1016/j.ejrad.2009.10.025. [PubMed] [CrossRef] [Google Scholar]
125. Widyanto L., Griffiths M.D., Brunsden V. A psychometric comparison of the Internet Addiction Test, the Internet-Related Problem Scale, and self-diagnosis. Cyberpsychology Behav. Soc. Netw. 2011;14:141–149. doi: 10.1089/cyber.2010.0151. [PubMed] [CrossRef] [Google Scholar]
126. Fu K., Chan W.S.C., Wong P.W.C., Yip P.S.F. Internet addiction: prevalence, discriminant validity and correlates among adolescents in Hong Kong. Br. J. Psychiatry J. Ment. Sci. 2010;196:486–492. doi: 10.1192/bjp.bp.109.075002. [PubMed] [CrossRef] [Google Scholar]
127. Tsitsika A., Critselis E., Louizou A., Janikian M., Freskou A., Marangou E., Kormas G., Kafetzis D. Determinants of Internet addiction among adolescents: A case-control study. ScientificWorldJournal. 2011;11:866–874. doi: 10.1100/tsw.2011.85. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
128. Yuan K., Qin W., Wang G., Zeng F., Zhao L., Yang X., Liu P., Liu J., Sun J., von Deneen K.M., Gong Q., Liu Y., Tian J. Microstructure Abnormalities in Adolescents with Internet Addiction Disorder. PLoS ONE. 2011;6:e20708. doi: 10.1371/journal.pone.0020708. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
129. Kim S.H., Baik S.-H., Park C.S., Kim S.J., Choi S.W., Kim S.E. Reduced striatal dopamine D2 receptors in people with Internet addiction. Neuroreport. 2011;22:407–411. doi: 10.1097/WNR.0b013e328346e16e. [PubMed] [CrossRef] [Google Scholar]
130. Ko C.-H., Yen J.-Y., Chen C.-C., Chen S.-H., Yen C.-F. Proposed diagnostic criteria of Internet addiction for adolescents. J. Nerv. Ment. Dis. 2005;193:728–733. doi: 10.1097/01.nmd.0000185891.13719.54. [PubMed] [CrossRef] [Google Scholar]
131. Dong G., DeVito E., Huang J., Du X. Diffusion tensor imaging reveals thalamus and posterior cingulate cortex abnormalities in internet gaming addicts. J. Psychiatr. Res. 2012;46:1212–1216. doi: 10.1016/j.jpsychires.2012.05.015. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
132. Dong G., Huang J., Du X. Enhanced reward sensitivity and decreased loss sensitivity in Internet addicts: An fMRI study during a guessing task. J. Psychiatr. Res. 2011;45:1525–1529. doi: 10.1016/j.jpsychires.2011.06.017. [PubMed] [CrossRef] [Google Scholar]
133. Dong G., Huang J., Du X. Alterations in regional homogeneity of resting-state brain activity in internet gaming addicts. Behav. Brain Funct. 2012;8:41. doi: 10.1186/1744-9081-8-41. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
134. Dong G., Hu Y., Lin X. Reward/punishment sensitivities among internet addicts: Implications for their addictive behaviors. Prog. Neuropsychopharmacol. Biol. Psychiatry. 2013;46:139–145. doi: 10.1016/j.pnpbp.2013.07.007. [PubMed] [CrossRef] [Google Scholar]
135. Dong G., Lin X., Zhou H., Lu Q. Cognitive flexibility in internet addicts: fMRI evidence from difficult-to-easy and easy-to-difficult switching situations. Addict. Behav. 2014;39:677–683. doi: 10.1016/j.addbeh.2013.11.028. [PubMed] [CrossRef] [Google Scholar]
136. Montag C., Kirsch P., Sauer C., Markett S., Reuter M. The role of the CHRNA4 gene in Internet addiction: A case-control study. J. Addict. Med. 2012;6:191–195. doi: 10.1097/ADM.0b013e31825ba7e7. [PubMed] [CrossRef] [Google Scholar]
137. Lee Y.S., Han D.H., Yang K.C., Daniels M.A., Na C., Kee B.S., Renshaw P.F. Depression like characteristics of 5HTTLPR polymorphism and temperament in excessive internet users. J. Affect. Disord. 2008;109:165–169. doi: 10.1016/j.jad.2007.10.020. [PubMed] [CrossRef] [Google Scholar]
138. Han D.H., Lee Y.S., Yang K.C., Kim E.Y., Lyoo I.K., Renshaw P.F. Dopamine genes and reward dependence in adolescents with excessive internet video game play. J. Addict. Med. 2007;1:133–138. doi: 10.1097/ADM.0b013e31811f465f. [PubMed] [CrossRef] [Google Scholar]
139. Yu H., Zhao X., Li N., Wang M., Zhou P. Effect of excessive Internet use on the time—Frequency characteristic of EEG. Prog. Nat. Sci. 2009;19:1383–1387. doi: 10.1016/j.pnsc.2008.11.015. [CrossRef] [Google Scholar]
140. Campanella S., Pogarell O., Boutros N. Event-related potentials in substance use disorders: A narrative review based on articles from 1984 to 2012. Clin. EEG Neurosci. 2014;45:67–76. doi: 10.1177/1550059413495533. [PubMed] [CrossRef] [Google Scholar]
141. Duven E.C.P., Müller K.W., Beutel M.E., Wölfling K. Altered reward processing in pathological computer gamers—ERP-results from a semi-natural gaming-design. Brain Behav. 2015;5:13–23. doi: 10.1002/brb3.293. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
142. Ge L., Ge X., Xu Y., Zhang K., Zhao J., Kong X. P300 change and cognitive behavioral therapy in subjects with Internet addiction disorder: A 3-month follow-up study. Neur. Reg. Res. 2011;6:2037–2041. [Google Scholar]
143. Zhu T.-M., Li H., Jin R.-J., Zheng Z., Luo Y., Ye H., Zhu H.-M. Effects of electroacupuncture combined psycho-intervention on cognitive function and event-related potentials P300 and mismatch negativity in patients with internet addiction. Chin. J. Integr. Med. 2012;18:146–151. doi: 10.1007/s11655-012-0990-5. [PubMed] [CrossRef] [Google Scholar]
144. Zhou Z.-H., Yuan G.-Z., Yao J.-J., Li C., Cheng Z.-H. An event-related potential investigation of deficient inhibitory control in individuals with pathological Internet use. Acta. Neuropsychiatr. 2010;22:228–236. doi: 10.1111/j.1601-5215.2010.00444.x. [PubMed] [CrossRef] [Google Scholar]
145. Parsons O.A., Sinha R., Williams H.L. Relationships between Neuropsychological Test Performance and Event-Related Potentials in Alcoholic and Nonalcoholic Samples. Alcohol. Clin. Exp. Res. 1990;14:746–755. doi: 10.1111/j.1530-0277.1990.tb01239.x. [PubMed] [CrossRef] [Google Scholar]
146. Dong G., Zhou H., Zhao X. Impulse inhibition in people with Internet addiction disorder: Electrophysiological evidence from a Go/NoGo study. Neurosci. Lett. 2010;485:138–142. doi: 10.1016/j.neulet.2010.09.002. [PubMed] [CrossRef] [Google Scholar]
147. Yang Z., Xie J., Shao Y.-C., Xie C.-M., Fu L.-P., Li D.-J., Fan M., Ma L., Li S.-J. Dynamic neural responses to cue-reactivity paradigms in heroin-dependent users: An fMRI study. Hum. Brain Mapp. 2009;30:766–775. doi: 10.1002/hbm.20542. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
148. Littel M., van den Berg I., Luijten M., van Rooij A.J., Keemink L., Franken I.H.A. Error processing and response inhibition in excessive computer game players: An event-related potential study. Addict. Biol. 2012;17:934–947. doi: 10.1111/j.1369-1600.2012.00467.x. [PubMed] [CrossRef] [Google Scholar]
149. Yu H., Zhao X., Wang Y., Li N., Wang M. The effect of excessive internet use on N400 event-related potentials. J. Biomed. Eng. 2008;25:1014–1020. [PubMed] [Google Scholar]
150. Zhou Z., Li C., Zhu H. An error-related negativity potential investigation of response monitoring function in individuals with internet addiction disorder. Front. Behav. Neurosci. 2013;7:131. doi: 10.3389/fnbeh.2013.00131. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
151. Yau Y.H.C., Potenza M.N. Gambling disorder and other behavioral addictions: Recognition and treatment. Harv. Rev. Psychiatry. 2015;23:134–146. doi: 10.1097/HRP.0000000000000051. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
152. Dong G., Zhou H., Zhao X. Male Internet addicts show impaired executive control ability: Evidence from a color-word Stroop task. Neurosci. Lett. 2011;499:114–118. doi: 10.1016/j.neulet.2011.05.047. [PubMed] [CrossRef] [Google Scholar]
153. Thalemann R., Wölfling K., Grüsser S.M. Specific cue reactivity on computer game-related cues in excessive gamers. Behav. Neurosci. 2007;121:614–618. doi: 10.1037/0735-7044.121.3.614. [PubMed] [CrossRef] [Google Scholar]
154. Choi J.-S., Park S.M., Lee J., Hwang J.Y., Jung H.Y., Choi S.-W., Kim D.J., Oh S., Lee J.-Y. Resting-state beta and gamma activity in Internet addiction. Int. J. Psychophysiol. Off. J. Int. Organ. Psychophysiol. 2013;89:328–333. doi: 10.1016/j.ijpsycho.2013.06.007. [PubMed] [CrossRef] [Google Scholar]
155. Lee J., Hwang J.Y., Park S.M., Jung H.Y., Choi S.-W., Kim D.J., Lee J.-Y., Choi J.-S. Differential resting-state EEG patterns associated with comorbid depression in Internet addiction. Prog. Neuropsychopharmacol. Biol. Psychiatry. 2014;50:21–26. doi: 10.1016/j.pnpbp.2013.11.016. [PubMed] [CrossRef] [Google Scholar]
156. Laws of the People’s Republic of China. [(accessed on 30 June 2015)]. Available online: http://www.asianlii.org/cn/legis/cen/laws/clotproc361/
157. Petry N.M., Blanco C., Stinchfield R., Volberg R. An empirical evaluation of proposed changes for gambling diagnosis in the DSM-5. Addict. Abingdon Engl. 2013;108:575–581. doi: 10.1111/j.1360-0443.2012.04087.x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
158. Petry N.M., Blanco C., Auriacombe M., Borges G., Bucholz K., Crowley T.J., Grant B.F., Hasin D.S., O’Brien C. An overview of and rationale for changes proposed for pathological gambling in DSM-5. J. Gambl. Stud. Co-Spons. Natl. Counc. Probl. Gambl. Inst. Study Gambl. Commer. Gaming. 2014;30:493–502. doi: 10.1007/s10899-013-9370-0. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
159. Petry N.M., O’Brien C.P. Internet gaming disorder and the DSM-5. Addict. Abingdon Engl. 2013;108:1186–1187. doi: 10.1111/add.12162. [PubMed] [CrossRef] [Google Scholar]
160. Liu J., Gao X.-P., Osunde I., Li X., Zhou S.-K., Zheng H.-R., Li L.-J. Increased regional homogeneity in internet addiction disorder: a resting state functional magnetic resonance imaging study. Chin. Med. J. (Engl.) 2010;123:1904–1908. [PubMed] [Google Scholar]
161. Kim Y.-R., Son J.-W., Lee S.-I., Shin C.-J., Kim S.-K., Ju G., Choi W.-H., Oh J.-H., Lee S., Jo S., Ha T.H. Abnormal brain activation of adolescent internet addict in a ball-throwing animation task: possible neural correlates of disembodiment revealed by fMRI. Prog. Neuropsychopharmacol. Biol. Psychiatry. 2012;39:88–95. doi: 10.1016/j.pnpbp.2012.05.013. [PubMed] [CrossRef] [Google Scholar]
162. Dong G., Devito E.E., Du X., Cui Z. Impaired inhibitory control in “internet addiction disorder”: A functional magnetic resonance imaging study. Psychiatry Res. 2012;203:153–158. doi: 10.1016/j.pscychresns.2012.02.001. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
163. Dong G., Shen Y., Huang J., Du X. Impaired error-monitoring function in people with Internet addiction disorder: An event-related fMRI study. Eur. Addict. Res. 2013;19:269–275. doi: 10.1159/000346783. [PubMed] [CrossRef] [Google Scholar]
164. Liu J., Esmail F., Li L., Kou Z., Li W., Gao X., Wang Z., Tan C., Zhang Y., Zhou S. Decreased frontal lobe function in people with Internet addiction disorder. Neural Regen. Res. 2013;8:3225–3232. [PMC free article] [PubMed] [Google Scholar]
165. Kühn S., Gallinat J. Brains online: structural and functional correlates of habitual Internet use. Addict. Biol. 2015;20:415–422. doi: 10.1111/adb.12128. [PubMed] [CrossRef] [Google Scholar]
166. Li B., Friston K.J., Liu J., Liu Y., Zhang G., Cao F., Su L., Yao S., Lu H., Hu D. Impaired frontal-basal ganglia connectivity in adolescents with internet addiction. Sci. Rep. 2014;4:5027. doi: 10.1038/srep05027. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
167. Kim J.-E., Son J.-W., Choi W.-H., Kim Y.-R., Oh J.-H., Lee S., Kim J.-K. Neural responses to various rewards and feedback in the brains of adolescent Internet addicts detected by functional magnetic resonance imaging. Psychiatry Clin. Neurosci. 2014;68:463–470. doi: 10.1111/pcn.12154. [PubMed] [CrossRef] [Google Scholar]
168. Wee C.-Y., Zhao Z., Yap P.-T., Wu G., Shi F., Price T., Du Y., Xu J., Zhou Y., Shen D. Disrupted Brain Functional Network in Internet Addiction Disorder: A Resting-State Functional Magnetic Resonance Imaging Study. PLoS ONE. 2014;9:e107306. doi: 10.1371/journal.pone.0107306. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
169. Loh K.K., Kanai R. Higher Media Multi-Tasking Activity Is Associated with Smaller Gray-Matter Density in the Anterior Cingulate Cortex. PLoS ONE. 2014;9:e106698. doi: 10.1371/journal.pone.0106698. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
170. Li W., Li Y., Yang W., Zhang Q., Wei D., Li W., Hitchman G., Qiu J. Brain structures and functional connectivity associated with individual differences in Internet tendency in healthy young adults. Neuropsychologia. 2015;70:134–144. doi: 10.1016/j.neuropsychologia.2015.02.019. [PubMed] [CrossRef] [Google Scholar]
171. Turel O., He Q., Xue G., Xiao L., Bechara A. Examination of neural systems sub-serving facebook “addiction” Psychol. Rep. 2014;115:675–695. doi: 10.2466/18.PR0.115c31z8. [PubMed] [CrossRef] [Google Scholar]
172. Ko C.-H., Liu G.-C., Hsiao S., Yen J.-Y., Yang M.-J., Lin W.-C., Yen C.-F., Chen C.-S. Brain activities associated with gaming urge of online gaming addiction. J. Psychiatr. Res. 2009;43:739–747. doi: 10.1016/j.jpsychires.2008.09.012. [PubMed] [CrossRef] [Google Scholar]
173. Han D.H., Kim Y.S., Lee Y.S., Min K.J., Renshaw P.F. Changes in cue-induced, prefrontal cortex activity with video-game play. Cyberpsychology Behav. Soc. Netw. 2010;13:655–661. doi: 10.1089/cyber.2009.0327. [PubMed] [CrossRef] [Google Scholar]
174. Ko C.-H., Liu G.-C., Yen J.-Y., Chen C.-Y., Yen C.-F., Chen C.-S. Brain correlates of craving for online gaming under cue exposure in subjects with Internet gaming addiction and in remitted subjects. Addict. Biol. 2013;18:559–569. doi: 10.1111/j.1369-1600.2011.00405.x. [PubMed] [CrossRef] [Google Scholar]
175. Han D.H., Bolo N., Daniels M.A., Arenella L., Lyoo I.K., Renshaw P.F. Brain activity and desire for internet video game play. Compr. Psychiatry. 2011;52:88–95. doi: 10.1016/j.comppsych.2010.04.004. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
176. Han D.H., Kim S.M., Lee Y.S., Renshaw P.F. The effect of family therapy on the changes in the severity of on-line game play and brain activity in adolescents with on-line game addiction. Psychiatry Res. 2012;202:126–131. doi: 10.1016/j.pscychresns.2012.02.011. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
177. Sun Y., Ying H., Seetohul R.M., Xuemei W., Ya Z., Qian L., Guoqing X., Ye S. Brain fMRI study of crave induced by cue pictures in online game addicts (male adolescents) Behav. Brain Res. 2012;233:563–576. doi: 10.1016/j.bbr.2012.05.005. [PubMed] [CrossRef] [Google Scholar]
178. Lorenz R.C., Krüger J.-K., Neumann B., Schott B.H., Kaufmann C., Heinz A., Wüstenberg T. Cue reactivity and its inhibition in pathological computer game players. Addict. Biol. 2013;18:134–146. doi: 10.1111/j.1369-1600.2012.00491.x. [PubMed] [CrossRef] [Google Scholar]
179. Yuan K., Jin C., Cheng P., Yang X., Dong T., Bi Y., Xing L., von Deneen K.M., Yu D., Liu J., Liang J., Cheng T., Qin W., Tian J. Amplitude of Low Frequency Fluctuation Abnormalities in Adolescents with Online Gaming Addiction. PLoS ONE. 2013;8:e78708. doi: 10.1371/journal.pone.0078708. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
180. Kätsyri J., Hari R., Ravaja N., Nummenmaa L. Just watching the game ain’t enough: Striatal fMRI reward responses to successes and failures in a video game during active and vicarious playing. Front. Hum. Neurosci. 2013;7:278. doi: 10.3389/fnhum.2013.00278. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
181. Dong G., Hu Y., Lin X., Lu Q. What makes Internet addicts continue playing online even when faced by severe negative consequences? Possible explanations from an fMRI study. Biol. Psychol. 2013;94:282–289. [PubMed] [Google Scholar]
182. Ko C.-H., Hsieh T.-J., Chen C.-Y., Yen C.-F., Chen C.-S., Yen J.-Y., Wang P.-W., Liu G.-C. Altered brain activation during response inhibition and error processing in subjects with Internet gaming disorder: a functional magnetic imaging study. Eur. Arch. Psychiatry Clin. Neurosci. 2014;264:661–672. doi: 10.1007/s00406-013-0483-3. [PubMed] [CrossRef] [Google Scholar]
183. Ding W., Sun J., Sun Y.-W., Chen X., Zhou Y., Zhuang Z., Li L., Zhang Y., Xu J., Du Y. Trait impulsivity and impaired prefrontal impulse inhibition function in adolescents with internet gaming addiction revealed by a Go/No-Go fMRI study. Behav. Brain Funct. 2014;10:20. doi: 10.1186/1744-9081-10-20. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
184. Chen C.-Y., Huang M.-F., Yen J.-Y., Chen C.-S., Liu G.-C., Yen C.-F., Ko C.-H. Brain correlates of response inhibition in Internet gaming disorder. Psychiatry Clin. Neurosci. 2015;69:201–209. doi: 10.1111/pcn.12224. [PubMed] [CrossRef] [Google Scholar]
185. Choi J.S. Sy08-2neurophysiological and Neuroimaging Aspects between Internet Gaming Disorder and Alcohol Use Disorder. Alcohol Alcohol. 2014;49:i10. doi: 10.1093/alcalc/agu052.38. [CrossRef] [Google Scholar]
186. Kim S.M., Han D.H. Sy20-4virtual Reality Therapy for Internet Gaming Disorder. Alcohol Alcohol. 2014;49:i19. doi: 10.1093/alcalc/agu052.88. [CrossRef] [Google Scholar]
187. Jung Y.C., Lee S., Chun J.W., Kim D.J. P-72altered Cingulate-Hippocampal Synchrony Correlate with Aggression in Adolescents with Internet Gaming Disorder. Alcohol Alcohol. 2014;49:i67–i68. doi: 10.1093/alcalc/agu054.72. [CrossRef] [Google Scholar]
188. Lin X., Zhou H., Dong G., Du X. Impaired risk evaluation in people with Internet gaming disorder: fMRI evidence from a probability discounting task. Prog. Neuropsychopharmacol. Biol. Psychiatry. 2015;56:142–148. doi: 10.1016/j.pnpbp.2014.08.016. [PubMed] [CrossRef] [Google Scholar]
189. Dong G., Lin X., Potenza M.N. Decreased functional connectivity in an executive control network is related to impaired executive function in Internet gaming disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry. 2015;57:76–85. doi: 10.1016/j.pnpbp.2014.10.012. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
190. Chen X., Wang Y., Zhou Y., Sun Y., Ding W., Zhuang Z., Xu J., Du Y. Different Resting-State Functional Connectivity Alterations in Smokers and Nonsmokers with Internet Gaming Addiction. Bio. Med. Res. Int. 2014;2014:1–9. doi: 10.1155/2014/825787. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
191. Hong S.-B., Harrison B.J., Dandash O., Choi E.-J., Kim S.-C., Kim H.-H., Shim D.-H., Kim C.-D., Kim J.-W., Yi S.-H. A selective involvement of putamen functional connectivity in youth with internet gaming disorder. Brain Res. 2015;1602:85–95. doi: 10.1016/j.brainres.2014.12.042. [PubMed] [CrossRef] [Google Scholar]
192. Han J.W., Han D.H., Bolo N., Kim B., Kim B.N., Renshaw P.F. Differences in functional connectivity between alcohol dependence and internet gaming disorder. Addict. Behav. 2015;41:12–19. [PMC free article] [PubMed] [Google Scholar]
193. Yuan K., Qin W., Yu D., Bi Y., Xing L., Jin C., Tian J. Core brain networks interactions and cognitive control in internet gaming disorder individuals in late adolescence/early adulthood. Brain Struct. Funct. doi: 10.1007/s00429-014-0982-7. [PubMed] [CrossRef] [Google Scholar]
194. Lorenz R.C., Gleich T., Gallinat J., Kühn S. Video game training and the reward system. Front. Hum. Neurosci. 2015;9:40. doi: 10.3389/fnhum.2015.00040. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
195. Wang Y., Yin Y., Sun Y., Zhou Y., Chen X., Ding W., Wang W., Li W., Xu J., Du Y. Decreased prefrontal lobe interhemispheric functional connectivity in adolescents with internet gaming disorder: A primary study using resting-state FMRI. PloS One. 2015;10:e0118733. doi: 10.1371/journal.pone.0118733. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
196. Liu J., Li W., Zhou S., Zhang L., Wang Z., Zhang Y., Jiang Y., Li L. Functional characteristics of the brain in college students with internet gaming disorder. Brain Imaging Behav. 2015;10:1–8. [PubMed] [Google Scholar]
197. Luijten M., Meerkerk G.-J., Franken I.H.A., van de Wetering B.J.M., Schoenmakers T.M. An fMRI study of cognitive control in problem gamers. Psychiatry Res. 2015;231:262–268. doi: 10.1016/j.pscychresns.2015.01.004. [PubMed] [CrossRef] [Google Scholar]
198. Zhang J.-T., Yao Y.-W., Li C.-S.R., Zang Y.-F., Shen Z.-J., Liu L., Wang L.-J., Liu B., Fang X.-Y. Altered resting-state functional connectivity of the insula in young adults with Internet gaming disorder. Addict. Biol. doi: 10.1111/adb.12247. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
199. Dong G., Lin X., Hu Y., Xie C., Du X. Imbalanced functional link between executive control network and reward network explain the online-game seeking behaviors in Internet gaming disorder. Sci. Rep. 2015;5:9197. doi: 10.1038/srep09197. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
200. Lin F., Zhou Y., Du Y., Qin L., Zhao Z., Xu J., Lei H. Abnormal White Matter Integrity in Adolescents with Internet Addiction Disorder: A Tract-Based Spatial Statistics Study. PLoS ONE. 2012;7:e30253. doi: 10.1371/journal.pone.0030253. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
201. Kühn S., Romanowski A., Schilling C., Lorenz R., Mörsen C., Seiferth N., Banaschewski T., Barbot A., Barker G.J., Büchel C., et al. The neural basis of video gaming. Transl. Psychiatry. 2011;1:e53. [PMC free article] [PubMed] [Google Scholar]
202. Han D.H., Lyoo I.K., Renshaw P.F. Differential regional gray matter volumes in patients with on-line game addiction and professional gamers. J. Psychiatr. Res. 2012;46:507–515. doi: 10.1016/j.jpsychires.2012.01.004. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
203. Weng C., Qian R., Fu X., Lin B., Ji X., Niu C., Wang Y. A voxel-based morphometric analysis of brain gray matter in online game addicts. Zhonghua Yixue Zazhi. 2012;92:3221–3223. [PubMed] [Google Scholar]
204. Yuan K., Cheng P., Dong T., Bi Y., Xing L., Yu D., Zhao L., Dong M., von Deneen K.M., Liu Y., Qin W., Tian J. Cortical Thickness Abnormalities in Late Adolescence with Online Gaming Addiction. PLoS ONE. 2013;8:e53055. doi: 10.1371/journal.pone.0053055. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
205. Hong S.-B., Zalesky A., Cocchi L., Fornito A., Choi E.-J., Kim H.-H., Suh J.-E., Kim C.-D., Kim J.-W., Yi S.-H. Decreased Functional Brain Connectivity in Adolescents with Internet Addiction. PLoS ONE. 2013;8:e57831. doi: 10.1371/journal.pone.0057831. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
206. Weng C.-B., Qian R.-B., Fu X.-M., Lin B., Han X.-P., Niu C.-S., Wang Y.-H. Gray matter and white matter abnormalities in online game addiction. Eur. J. Radiol. 2013;82:1308–1312. doi: 10.1016/j.ejrad.2013.01.031. [PubMed] [CrossRef] [Google Scholar]
207. Ding W., Sun J., Sun Y., Zhou Y., Li L., Xu J., Du Y. Altered Default Network Resting-State Functional Connectivity in Adolescents with Internet Gaming Addiction. PLoS ONE. 2013;8:e59902. doi: 10.1371/journal.pone.0059902. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
208. Hong S.-B., Kim J.-W., Choi E.-J., Kim H.-H., Suh J.-E., Kim C.-D., Klauser P., Whittle S., Yűcel M., Pantelis C., Yi S.-H. Reduced orbitofrontal cortical thickness in male adolescents with internet addiction. Behav. Brain Funct. 2013;9:11. doi: 10.1186/1744-9081-9-11. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
209. Feng Q., Chen X., Sun J., Zhou Y., Sun Y., Ding W., Zhang Y., Zhuang Z., Xu J., Du Y. Voxel-level comparison of arterial spin-labeled perfusion magnetic resonance imaging in adolescents with internet gaming addiction. Behav. Brain Funct. 2013;9:33. doi: 10.1186/1744-9081-9-33. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
210. Liu G.-C., Yen J.-Y., Chen C.-Y., Yen C.-F., Chen C.-S., Lin W.-C., Ko C.-H. Brain activation for response inhibition under gaming cue distraction in internet gaming disorder. Kaohsiung J. Med. Sci. 2014;30:43–51. doi: 10.1016/j.kjms.2013.08.005. [PubMed] [CrossRef] [Google Scholar]
211. Han D.H., Lee Y.S., Shi X., Renshaw P.F. Proton magnetic resonance spectroscopy (MRS) in on-line game addiction. J. Psychiatr. Res. 2014;58:63–68. doi: 10.1016/j.jpsychires.2014.07.007. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
212. Lin X., Dong G., Wang Q., Du X. Abnormal gray matter and white matter volume in “Internet gaming addicts” Addict. Behav. 2015;40:137–143. doi: 10.1016/j.addbeh.2014.09.010. [PubMed] [CrossRef] [Google Scholar]
213. Xing L., Yuan K., Bi Y., Yin J., Cai C., Feng D., Li Y., Song M., Wang H., Yu D., et al. Reduced fiber integrity and cognitive control in adolescents with internet gaming disorder. Brain Res. 2014;1586:109–117. [PubMed] [Google Scholar]
214. Sun Y., Sun J., Zhou Y., Ding W., Chen X., Zhuang Z., Xu J., Du Y. Assessment of in vivo microstructure alterations in gray matter using DKI in internet gaming addiction. Behav. Brain Funct. 2014;10:37. doi: 10.1186/1744-9081-10-37. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
215. Ko C.-H., Hsieh T.-J., Wang P.-W., Lin W.-C., Yen C.-F., Chen C.-S., Yen J.-Y. Altered gray matter density and disrupted functional connectivity of the amygdala in adults with Internet gaming disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry. 2015;57:185–192. doi: 10.1016/j.pnpbp.2014.11.003. [PubMed] [CrossRef] [Google Scholar]
216. Kim H., Kim Y.K., Gwak A.R., Lim J.-A., Lee J.-Y., Jung H.Y., Sohn B.K., Choi S.-W., Kim D.J., Choi J.-S. Resting-state regional homogeneity as a biological marker for patients with Internet gaming disorder: A comparison with patients with alcohol use disorder and healthy controls. Prog. Neuropsychopharmacol. Biol. Psychiatry. 2015;60:104–111. doi: 10.1016/j.pnpbp.2015.02.004. [PubMed] [CrossRef] [Google Scholar]
217. Cai C., Yuan K., Yin J., Feng D., Bi Y., Li Y., Yu D., Jin C., Qin W., Tian J. Striatum morphometry is associated with cognitive control deficits and symptom severity in internet gaming disorder. Brain Imaging Behav. doi: 10.1007/s11682-015-9358-8. [PubMed] [CrossRef] [Google Scholar]
218. Wang H., Jin C., Yuan K., Shakir T.M., Mao C., Niu X., Niu C., Guo L., Zhang M. The alteration of gray matter volume and cognitive control in adolescents with internet gaming disorder. Front. Behav. Neurosci. 2015;9:64. doi: 10.3389/fnbeh.2015.00064. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
219. Hou H., Jia S., Hu S., Fan R., Sun W., Sun T., Zhang H. Reduced Striatal Dopamine Transporters in People with Internet Addiction Disorder. Bio. Med. Res. Int. 2012;2012:e854524. doi: 10.1155/2012/854524. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
220. Park H.S., Kim S.H., Bang S.A., Yoon E.J., Cho S.S., Kim S.E. Altered regional cerebral glucose metabolism in internet game overusers: A 18F-fluorodeoxyglucose positron emission tomography study. CNS Spectr. 2010;15:159–166. [PubMed] [Google Scholar]
221. Tian M., Chen Q., Zhang Y., Du F., Hou H., Chao F., Zhang H. PET imaging reveals brain functional changes in internet gaming disorder. Eur. J. Nucl. Med. Mol. Imaging. 2014;41:1388–1397. doi: 10.1007/s00259-014-2708-8. [PubMed] [CrossRef] [Google Scholar]
222. Koepp M.J., Gunn R.N., Lawrence A.D., Cunningham V.J., Dagher A., Jones T., Brooks D.J., Bench C.J., Grasby P.M. Evidence for striatal dopamine release during a video game. Nature. 1998;393:266–268. [PubMed] [Google Scholar]
223. Zhao X., Yu H., Zhan Q., Wang M. Influence of excessive internet use on auditory event-related potential. J. Biomed. Eng. 2008;25:1289–1293. [PubMed] [Google Scholar]
224. Son K.L., Choi J.S., Lee J., Park S.M., Lim J.A., Lee J.Y., Kim S.N., Oh S., Kim D.J., Kwon J.S. Neurophysiological features of Internet gaming disorder and alcohol use disorder: a resting-state EEG study. Translational psychiatry. 2015;9:e628. doi: 10.1038/tp.2015.124. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
225. Lu D.W., Wang J.W., Huang A.C.W. Differentiation of Internet addiction risk level based on autonomic nervous responses: The Internet-addiction hypothesis of autonomic activity. Cyberpsychology Behav. Soc. Netw. 2010;13:371–378. doi: 10.1089/cyber.2009.0254. [PubMed] [CrossRef] [Google Scholar]
226. Zhang H.-X., Jiang W.-Q., Lin Z.-G., Du Y.-S., Vance A. Comparison of Psychological Symptoms and Serum Levels of Neurotransmitters in Shanghai Adolescents with and without Internet Addiction Disorder: A Case-Control Study. PLoS ONE. 2013;8:e63089. doi: 10.1371/journal.pone.0063089. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
227. Lin P.-C., Kuo S.-Y., Lee P.-H., Sheen T.-C., Chen S.-R. Effects of internet addiction on heart rate variability in school-aged children. J. Cardiovasc. Nurs. 2014;29:493–498. doi: 10.1097/JCN.0b013e3182a477d5. [PubMed] [CrossRef] [Google Scholar]
228. Han D.H., Lee Y.S., Na C., Ahn J.Y., Chung U.S., Daniels M.A., Haws C.A., Renshaw P.F. The effect of methylphenidate on Internet video game play in children with attention-deficit/hyperactivity disorder. Compr. Psychiatry. 2009;50:251–256. doi: 10.1016/j.comppsych.2008.08.011. [PubMed] [CrossRef] [Google Scholar]
229. Metcalf O., Pammer K. Physiological arousal deficits in addicted gamers differ based on preferred game genre. Eur. Addict. Res. 2014;20:23–32. doi: 10.1159/000349907. [PubMed] [CrossRef] [Google Scholar]
230. Andreassen C.S., Pallesen S. Social network site addiction—An overview. Curr. Pharm. Des. 2014;20:4053–4061. doi: 10.2174/13816128113199990616. [PubMed] [CrossRef] [Google Scholar]
231. Andreassen C.S., Torsheim T., Brunborg G.S., Pallesen S. Development of a Facebook Addiction Scale. Psychol. Rep. 2012;110:501–517. doi: 10.2466/02.09.18.PR0.110.2.501-517. [PubMed] [CrossRef] [Google Scholar]
232. Balakrishnan V., Shamim A. Malaysian Facebookers: Motives and Addictive Behaviours Unraveled. Comput. Hum. Behav. 2013;29:1342–1349. doi: 10.1016/j.chb.2013.01.010. [CrossRef] [Google Scholar]
233. Carmody C.L. Internet Addiction: Just Facebook Me! The Role of Social Networking Sites in Internet Addiction. Comput. Technol. Appl. 2012;3:262–267. [Google Scholar]
234. Cam E., Isbulan O. A New Addiction for Teacher Candidates: Social Networks. Turk. Online J. Educ. Technol.—TOJET. 2012;11:14–19. [Google Scholar]
235. Karaiskos D., Tzavellas E., Balta G., Paparrigopoulos T. P02-232—Social network addiction : a new clinical disorder? Eur. Psychiatry. 2010;25:855. doi: 10.1016/S0924-9338(10)70846-4. [CrossRef] [Google Scholar]
236. Kittinger R., Correia C.J., Irons J.G. Relationship between Facebook use and problematic Internet use among college students. Cyberpsychology Behav. Soc. Netw. 2012;15:324–327. doi: 10.1089/cyber.2010.0410. [PubMed] [CrossRef] [Google Scholar]
237. Koc M., Gulyagci S. Facebook addiction among Turkish college students: The role of psychological health, demographic, and usage characteristics. Cyberpsychology Behav. Soc. Netw. 2013;16:279–284. doi: 10.1089/cyber.2012.0249. [PubMed] [CrossRef] [Google Scholar]
238. Milošević-Đorđević J.S., Žeželj I.L. Psychological predictors of addictive social networking sites use: The case of Serbia. Comput. Hum. Behav. 2014;32:229–234. doi: 10.1016/j.chb.2013.12.018. [CrossRef] [Google Scholar]
239. Rosen L.D., Whaling K., Rab S., Carrier L.M., Cheever N.A. Is Facebook Creating “iDisorders”? The Link Between Clinical Symptoms of Psychiatric Disorders and Technology Use, Attitudes and Anxiety. Comput. Hum. Behav. 2013;29:1243–1254. [Google Scholar]
240. Salehan M., Negahban A. Social Networking on Smartphones: When Mobile Phones Become Addictive. Comput Hum Behav. 2013;29:2632–2639. doi: 10.1016/j.chb.2013.07.003. [CrossRef] [Google Scholar]
241. Weiss R., Samenow C.P. Smart Phones, Social Networking, Sexting and Problematic Sexual Behaviors—A Call for Research. Sex. Addict. Compulsivity. 2010;17:241–246. doi: 10.1080/10720162.2010.532079. [CrossRef] [Google Scholar]
242. Childress A.R., Ehrman R.N., Wang Z., Li Y., Sciortino N., Hakun J., Jens W., Suh J., Listerud J., Marquez K., Franklin T., Langleben D., Detre J., O’Brien C.P. Prelude to Passion: Limbic Activation by “Unseen” Drug and Sexual Cues. PLoS ONE. 2008;3:e1506. doi: 10.1371/journal.pone.0001506. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
243. Georgiadis J.R., Kringelbach M.L. The human sexual response cycle: Brain imaging evidence linking sex to other pleasures. Prog. Neurobiol. 2012;98:49–81. doi: 10.1016/j.pneurobio.2012.05.004. [PubMed] [CrossRef] [Google Scholar]
244. Frascella J., Potenza M.N., Brown L.L., Childress A.R. Shared brain vulnerabilities open the way for nonsubstance addictions: Carving addiction at a new joint? Ann. N. Y. Acad. Sci. 2010;1187:294–315. doi: 10.1111/j.1749-6632.2009.05420.x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
245. Blum K., Werner T., Carnes S., Carnes P., Bowirrat A., Giordano J., Oscar-Berman M., Gold M. Sex, drugs, and rock “n” roll: Hypothesizing common mesolimbic activation as a function of reward gene polymorphisms. J. Psychoactive Drugs. 2012;44:38–55. doi: 10.1080/02791072.2012.662112. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
246. Blum K., Giordano J., Morse S., Liu Y., Tan J., Bowirrat A., Smolen A., Waite R., Downs W., Madigan M., et al. Genetic Addiction Risk Score (GARS) analysis: Exploratory development of polymorphic risk alleles in poly-drug addicted males. IIOAB J. 2010;1:169–175. [Google Scholar]
247. Blum K., Gardner E., Oscar-Berman M., Gold M. “Liking” and “wanting” linked to Reward Deficiency Syndrome (RDS): Hypothesizing differential responsivity in brain reward circuitry. Curr. Pharm. Des. 2012;18:113–118. doi: 10.2174/138161212798919110. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
248. Comings D.E., Blum K. Reward deficiency syndrome: Genetic aspects of behavioral disorders. Prog. Brain Res. 2000;126:325–341. [PubMed] [Google Scholar]
249. Downs B., Oscar-Berman M., Waite R., Madigan M., Giordano J., Beley T., Jones S., Simpatico T., Hauser M., Borsten J., et al. Have We Hatched the Addiction Egg: Reward Deficiency Syndrome Solution SystemTM. J. Genet. Syndr. Gene. Ther. 2013;4:14318. [PMC free article] [PubMed] [Google Scholar]
250. Grueter B.A., Robison A.J., Neve R.L., Nestler E.J., Malenka R.C. ∆FosB differentially modulates nucleus accumbens direct and indirect pathway function. Proc. Natl. Acad. Sci. USA. 2013;110:1923–1928. doi: 10.1073/pnas.1221742110. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
251. Nestler E.J. Cellular basis of memory for addiction. Dialogues Clin. Neurosci. 2013;15:431–443. [PMC free article] [PubMed] [Google Scholar]
252. Zhang Y., Crofton E.J., Li D., Lobo M.K., Fan X., Nestler E.J., Green T.A. Overexpression of DeltaFosB in nucleus accumbens mimics the protective addiction phenotype, but not the protective depression phenotype of environmental enrichment. Front. Behav. Neurosci. 2014;8:297. doi: 10.3389/fnbeh.2014.00297. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
253. Muschamp J.W., Nemeth C.L., Robison A.J., Nestler E.J., Carlezon W.A. ΔFosB enhances the rewarding effects of cocaine while reducing the pro-depressive effects of the kappa-opioid receptor agonist U50488. Biol. Psychiatr. 2012;71:44–50. doi: 10.1016/j.biopsych.2011.08.011. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
254. Been L.E., Hedges V.L., Vialou V., Nestler E.J., Meisel R.L. ΔJunD overexpression in the nucleus accumbens prevents sexual reward in female Syrian hamsters. Genes Brain Behav. 2013;12:666–672. doi: 10.1111/gbb.12060. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
255. Hedges V.L., Chakravarty S., Nestler E.J., Meisel R.L. Delta FosB overexpression in the nucleus accumbens enhances sexual reward in female Syrian hamsters. Genes Brain Behav. 2009;8:442–449. doi: 10.1111/j.1601-183X.2009.00491.x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
256. Wallace D.L., Vialou V., Rios L., Carle-Florence T.L., Chakravarty S., Kumar A., Graham D.L., Green T.A., Kirk A., Iñiguez S.D., et al. The influence of DeltaFosB in the nucleus accumbens on natural reward-related behavior. J. Neurosci. 2008;28:10272–10277. [PMC free article] [PubMed] [Google Scholar]
257. Pitchers K.K., Frohmader K.S., Vialou V., Mouzon E., Nestler E.J., Lehman M.N., Coolen L.M. DeltaFosB in the nucleus accumbens is critical for reinforcing effects of sexual reward. Genes Brain Behav. 2010;9:831–840. doi: 10.1111/j.1601-183X.2010.00621.x. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
258. Pitchers K.K., Balfour M.E., Lehman M.N., Richtand N.M., Yu L., Coolen L.M. Neuroplasticity in the mesolimbic system induced by natural reward and subsequent reward abstinence. Biol. Psychiatry. 2010;67:872–879. doi: 10.1016/j.biopsych.2009.09.036. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
259. Doidge N. The Brain That Changes Itself: Stories of Personal Triumph from the Frontiers of Brain Science. Penguin Books; New York, NY, USA: 2007. [Google Scholar]
260. Hilton D.L., Watts C. Pornography addiction: A neuroscience perspective. Surg. Neurol. Int. 2011;2:19. [PMC free article] [PubMed] [Google Scholar]
261. Reid R.C., Carpenter B.N., Fong T.W. Neuroscience research fails to support claims that excessive pornography consumption causes brain damage. Surg. Neurol. Int. 2011;2:64. doi: 10.4103/2152-7806.81427. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
262. Voon V., Mole T.B., Banca P., Porter L., Morris L., Mitchell S., Lapa T.R., Karr J., Harrison N.A., Potenza M.N., Irvine M. Neural Correlates of Sexual Cue Reactivity in Individuals with and without Compulsive Sexual Behaviours. PLoS ONE. 2014;9:e102419. doi: 10.1371/journal.pone.0102419. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
263. Kühn S., Gallinat J. Brain structure and functional connectivity associated with pornography consumption: The brain on porn. JAMA Psychiatry. 2014;71:827–834. [PubMed] [Google Scholar]
264. Prause N., Pfaus J. Viewing Sexual Stimuli Associated with Greater Sexual Responsiveness, Not Erectile Dysfunction. Sex. Med. 2015;3:90–98. doi: 10.1002/sm2.58. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
265. Arnow B.A., Desmond J.E., Banner L.L., Glover G.H., Solomon A., Polan M.L., Lue T.F., Atlas S.W. Brain activation and sexual arousal in healthy, heterosexual males. Brain. 2002;125:1014–1023. doi: 10.1093/brain/awf108. [PubMed] [CrossRef] [Google Scholar]
266. Ferris C.F., Snowdon C.T., King J.A., Sullivan J.M., Ziegler T.E., Olson D.P., Schultz-Darken N.J., Tannenbaum P.L., Ludwig R., Wu Z., et al. Activation of Neural Pathways Associated with Sexual Arousal in Non-Human Primates. J. Magn. Reson. Imaging. 2004;19:168–175. [PMC free article] [PubMed] [Google Scholar]
267. Wang Y., Zhu J., Li Q., Li W., Wu N., Zheng Y., Chang H., Chen J., Wang W. Altered fronto-striatal and fronto-cerebellar circuits in heroin-dependent individuals: A resting-state FMRI study. PLoS One. 2013;8:e58098. doi: 10.1371/journal.pone.0058098. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
268. Gola M., Wordecha M., Sescousse G., Kossowski B., Marchewka A. Increased sensitivity to erotic reward cues in subjects with compulsive sexual behaviors. J. Behav. Addict. 2015;4:16. [Google Scholar]
269. Sescousse G., Barbalat G., Domenech P., Dreher J.-C. Imbalance in the sensitivity to different types of rewards in pathological gambling. Brain J. Neurol. 2013;136:2527–2538. doi: 10.1093/brain/awt126. [PubMed] [CrossRef] [Google Scholar]
270. Brand M., Grabenhorst T., Snagowski J., Laier C., Maderwald S. Cybersex addiction is correlated with ventral striatum activity when watching preferred pornographic pictures. J. Behav. Addict. 2015;4:9. [Google Scholar]
271. Wehrum-Osinsky S., Klucken T., Rudolf S. Neural and subjective responses in patients with excessive pornography consumption. J. Behav. Addict. 2015;4:42. [Google Scholar]
272. Fineberg N.A., Potenza M.N., Chamberlain S.R., Berlin H.A., Menzies L., Bechara A., Sahakian B.J., Robbins T.W., Bullmore E.T., Hollander E. Probing Compulsive and Impulsive Behaviors, from Animal Models to Endophenotypes: A Narrative Review. Neuropsychopharmacology. 2010;35:591–604. doi: 10.1038/npp.2009.185. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
273. Chan R.C.K., Shum D., Toulopoulou T., Chen E.Y.H. Assessment of executive functions: Review of instruments and identification of critical issues. Arch. Clin. Neuropsychol. 2008;23:201–216. doi: 10.1016/j.acn.2007.08.010. [PubMed] [CrossRef] [Google Scholar]
274. Miyake A., Friedman N.P., Emerson M.J., Witzki A.H., Howerter A., Wager T.D. The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognit. Psychol. 2000;41:49–100. doi: 10.1006/cogp.1999.0734. [PubMed] [CrossRef] [Google Scholar]
275. Smith E.E., Jonides J. Storage and executive processes in the frontal lobes. Science. 1999;283:1657–1661. doi: 10.1126/science.283.5408.1657. [PubMed] [CrossRef] [Google Scholar]
276. Stuss D.T., Alexander M.P. Executive functions and the frontal lobes: A conceptual view. Psychol. Res. 2000;63:289–298. doi: 10.1007/s004269900007. [PubMed] [CrossRef] [Google Scholar]
277. Jurado M.B., Rosselli M. The elusive nature of executive functions: A review of our current understanding. Neuropsychol. Rev. 2007;17:213–233. doi: 10.1007/s11065-007-9040-z. [PubMed] [CrossRef] [Google Scholar]
278. Royall D.R., Lauterbach E.C., Cummings J.L., Reeve A., Rummans T.A., Kaufer D.I., LaFrance W.C., Coffey C.E. Executive control function: A review of its promise and challenges for clinical research. J. Neuropsychiatry Clin. Neurosci. 2002;14:377–405. doi: 10.1176/jnp.14.4.377. [PubMed] [CrossRef] [Google Scholar]
279. Verdejo-García A., López-Torrecillas F., Giménez C.O., Pérez-García M. Clinical implications and methodological challenges in the study of the neuropsychological correlates of cannabis, stimulant, and opioid abuse. Neuropsychol. Rev. 2004;14:1–41. doi: 10.1023/B:NERV.0000026647.71528.83. [PubMed] [CrossRef] [Google Scholar]
280. Bechara A. Decision making, impulse control and loss of willpower to resist drugs: A neurocognitive perspective. Nat. Neurosci. 2005;8:1458–1463. doi: 10.1038/nn1584. [PubMed] [CrossRef] [Google Scholar]
281. Young K.S. Internet sex addiction: Risk factors, stages of development, and treatment. Am. Behav. Sci. 2008;52:21–37. doi: 10.1177/0002764208321339. [CrossRef] [Google Scholar]
282. Holstege G., Georgiadis J.R., Paans A.M.J., Meiners L.C., van der Graaf F.H.C.E., Reinders A.A.T.S. Brain activation during human male ejaculation. J. Neurosci. 2003;23:9185–9193. [PMC free article] [PubMed] [Google Scholar]
283. Brand M., Laier C., Pawlikowski M., Schächtle U., Schöler T., Altstötter-Gleich C. Watching pornographic pictures on the Internet: Role of sexual arousal ratings and psychological-psychiatric symptoms for using Internet sex sites excessively. CyberPsychology Behav. Soc. Netw. 2011;14:371–377. doi: 10.1089/cyber.2010.0222. [PubMed] [CrossRef] [Google Scholar]
Laier C., Pekal J., Brand M. Cybersex addiction in heterosexual female users of Internet pornography can be explained by gratification hypothesis. CyberPsychology Behav. Soc. Netw. 2014;17:505–511. [PubMed] [Google Scholar]
Laier C., Pekal J., Brand M. Sexual excitability and dysfunctional coping determine cybersex addiction in homosexual males. Cyberpsych. Behav. Soc. Netw. 2015 doi: 10.1089/cyber.2015.0152. in press. [PubMed] [CrossRef] [Google Scholar]
Laier C., Pawlikowski M., Pekal J., Schulte F.P., Brand M. Cybersex addiction: Experienced sexual arousal when watching pornography and not real-life sexual contacts makes the difference. J. Behav. Addict. 2013;2:100–107. doi: 10.1556/JBA.2.2013.002. [PubMed] [CrossRef] [Google Scholar]
Snagowski J., Wegmann E., Pekal J., Laier C., Brand M. Implicit associations in cybersex addiction: Adaption of an Implicit Association Test with pornographic pictures. Addict. Behav. 2015;49:7–12. doi: 10.1016/j.addbeh.2015.05.009. [PubMed] [CrossRef] [Google Scholar]
Snagowski J., Brand M. Symptoms of cybersex addiction can be linked to both approaching and avoiding pornographic stimuli: results from an analog sample of regular cybersex users. Front. Psychol. 2015;6:653. doi: 10.3389/fpsyg.2015.00653. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Laier C., Brand M. Empirical Evidence and Theoretical Considerations on Factors Contributing to Cybersex Addiction From a Cognitive-Behavioral View. Sex. Addict. Compuls. 2014;21:305–321. doi: 10.1080/10720162.2014.970722. [CrossRef] [Google Scholar]
Reid R.C., Karim R., McCrory E., Carpenter B.N. Self-reported differences on measures of executive function and hypersexual behavior in a patient and community sample of men. Int. J. Neurosci. 2010;120:120–127. doi: 10.3109/00207450903165577. [PubMed] [CrossRef] [Google Scholar]
Reid R.C., Garos S., Carpenter B.N., Coleman E. A surprising finding related to executive control in a patient sample of hypersexual men. J. Sex. Med. 2011;8:2227–2236. doi: 10.1111/j.1743-6109.2011.02314.x. [PubMed] [CrossRef] [Google Scholar]
Wright L.W., Adams H.E. The effects of stimuli that vary in erotic content on cognitive processes. J. Sex Res. 1999;36:145–151. doi: 10.1080/00224499909551979. [CrossRef] [Google Scholar]
Most S., Smith S., Cooter A., Levy B., Zald D. The naked truth: Positive, arousing distractors impair rapid target perception. Cogn. Emot. 2007;21:37–41. doi: 10.1080/02699930600959340. [CrossRef] [Google Scholar]
Kagerer S., Wehrum S., Klucken T., Walter B., Vaitl D., Stark R. Sex attracts: Investigating individual differences in attentional bias to sexual stimuli. PLoS ONE. 2014;9:e107795. doi: 10.1371/journal.pone.0107795. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Doornwaard S.M., van den Eijnden R.J.J.M., Johnson A., ter Bogt T.F.M. Exposure to sexualized media content and selective attention for sexual cues: An experimental study. Comput. Hum. Behav. 2014;41:357–364. doi: 10.1016/j.chb.2014.10.037. [CrossRef] [Google Scholar]
Prause N., Janssen E., Hetrick W.P. Attention and emotional responses to sexual stimuli and their relationship to sexual desire. Arch. Sex. Behav. 2008;37:934–949. doi: 10.1007/s10508-007-9236-6. [PubMed] [CrossRef] [Google Scholar]
Macapagal K.R., Janssen E., Fridberg B.S., Finn R., Heiman J.R. The effects of impulsivity, sexual arousability, and abstract intellectual ability on men’s and women’s go/no-go task performance. Arch. Sex. Behav. 2011;40:995–1006. doi: 10.1007/s10508-010-9676-2. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Laier C., Pawlikowski M., Brand M. Sexual picture processing interferes with decision making under ambiguity. Arch. Sex. Behav. 2014;43:473–482. doi: 10.1007/s10508-013-0119-8. [PubMed] [CrossRef] [Google Scholar]
Laier C., Schulte F.P., Brand M. Pornographic picture processing interferes with working memory performance. J. Sex Res. 2013;50:642–652. doi: 10.1080/00224499.2012.716873. [PubMed] [CrossRef] [Google Scholar]
Schiebener J., Laier C., Brand M. Getting stuck with pornography ? Overuse or neglect of cybersex cues in a multitasking situation is related to symptoms of cybersex addiction. J. Behav. Addict. 2015;4:14–21. [PMC free article] [PubMed] [Google Scholar]
Mechelmans D.J., Irvine M., Banca P., Porter L., Mitchell S., Mole T.B., Lapa T.R., Harrison N.A., Potenza M.N., Voon V. Enhanced Attentional Bias towards Sexually Explicit Cues in Individuals with and without Compulsive Sexual Behaviours. PLoS ONE. 2014;9:e105476. doi: 10.1371/journal.pone.0105476. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Ruiz-Díaz M., Hernández-González M., Guevara M.A., Amezcua C., Ågmo A. Prefrontal EEG correlation during tower of hanoi and WCST performance: Effect of emotional visual stimuli. J. Sex. Med. 2012;9:2631–2640. doi: 10.1111/j.1743-6109.2012.02782.x. [PubMed] [CrossRef] [Google Scholar]
Steele V.R., Staley C., Fong T., Prause N. Sexual desire, not hypersexuality, is related to neurophysiological responses elicited by sexual images. Socioaffective Neurosci. Psychol. 2013;3:20770. doi: 10.3402/snp.v3i0.20770. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Minnix J.A., Versace F., Robinson J.D., Lam C.Y., Engelmann J.M., Cui Y., Brown V.L., Cinciripini P.M. The late positive potential (LPP) in response to varying types of emotional and cigarette stimuli in smokers: A content comparison. Int. J. Psychophysiol. Off. J. Int. Organ. Psychophysiol. 2013;89:18–25. doi: 10.1016/j.ijpsycho.2013.04.019. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Rupp H.A., Wallen K. Sex Differences in Response to Visual Sexual Stimuli: A Review. Arch. Sex. Behav. 2008;37:206–218. doi: 10.1007/s10508-007-9217-9. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Lykins A.D., Meana M., Strauss G.P. Sex differences in visual attention to erotic and non-erotic stimuli. Arch. Sex. Behav. 2008;37:219–228. doi: 10.1007/s10508-007-9208-x. [PubMed] [CrossRef] [Google Scholar]
Hilton D.L. “High desire”, or “merely” an addiction? A response to Steele et al. Socioaffective Neurosci. Psychol. 2014;4:23833. [PMC free article] [PubMed] [Google Scholar]
Prause N., Steele V.R., Staley C., Sabatinelli D., Hajcak G. Modulation of late positive potentials by sexual images in problem users and controls inconsistent with “porn addiction” Biol. Psychol. 2015 doi: 10.1016/j.biopsycho.2015.06.005. in press. [PubMed] [CrossRef] [Google Scholar]
