Jump to ContentJump to Main Navigation
Show Summary Details
More options …


Organ der Neurowissenschaftlichen Gesellschaft

Editor-in-Chief: Wahle, Petra

CiteScore 2018: 0.11

SCImago Journal Rank (SJR) 2018: 0.134
Source Normalized Impact per Paper (SNIP) 2018: 0.047

Print + Online
See all formats and pricing
More options …
Volume 25, Issue 2


Psychological and neuroscientific advances to understand Internet Use Disorder

Prof. Dr. Benjamin Becker
  • neuSCAN Laboratory, The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China Chengdu China
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Prof. Dr. Christian Montag
  • Corresponding author
  • Department of Molecular Psychology Institute of Psychology and Education, Ulm University Helmholtzstr. 8/1, D-89081 Ulm phone: +49-731-50 26550 fax: +49-731-50 32759 Twitter: @ChrisMontag77 Ulm Germany
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2019-06-04 | DOI: https://doi.org/10.1515/nf-2018-0026


Internet-Nutzungsstörung (INS; in der jüngeren Vergangenheit zumeist als „Internet-Sucht“ benannt) stellt ein viel diskutiertes Thema weltweit dar. Besonders mit der Aufnahme der Diagnose Gaming Disorder im ICD-11 der Weltgesundheitsbehörde ist das nächste Level einer oftmals emotional geführten Debatte über die Natur der Verhaltenssüchte erreicht worden. Um den Leser aktuelle Einsichten in den aktuellen Stand der Dinge bezüglich dieses Themenbereiches zu vermitteln, wird in der vorliegenden Übersichtarbeit zunächst zusammengefasst, was über die INS bekannt ist und auch wie sich das Störungsbild entwickelt. Zusätzlich wird versucht, das relativ neue Phänomen der Smartphone-Nutzungsstörung (für viele eher bekannt als „Smartphone-Sucht“) in dem großen Themenkomplex der INS zu verorten.

Über diese theoretischen und diagnostischen Aspekte hinausgehend, gibt der vorliegende Artikel eine Übersicht über neurowissenschaftliche Erkenntnisse, die dabei helfen, die INS besser zu charakterisieren. Viele unterschiedliche Methoden der Neurowissenschaften wurden bereits eingesetzt, um die biologischen Grundlagen der INS zu entschlüsseln. Die Magnetresonanztomographie (MRT) stand dabei in der Vergangenheit besonders im Fokus, so dass Befunde aus der MRT-Forschung auch im Fokus dieses Übersichtsartikel stehen werden. Der Artikel endet mit Limitationen der aktuellen empirischen Forschung. Zusätzlich wird ein Ausblick auf die nächsten Schritte in dem lebhaften Forschungsfeld der INS gegeben.


Internet Use Disorder (IUD; previously referred to as “Internet addiction”) has been considered an emerging public health issue. However, the topic is debated and remains highly controversial. Furthermore, the inclusion of a Gaming Disorder diagnosis in ICD-11 by the World Health Organization have rekindled debates on the nature of behavioral addictions. Against this background, the present review aims to provide readers with a summary on the current state of diagnostic approaches, risk factors and neurobiological models of IUD. Moreover, and in this context, the present work will include an outlook on smartphone use disorder (often referred to as “smartphone addiction”).

With respect to neurobiological underpinnings of IUD, different approaches including molecular genetics and neuroimaging have been employed. Here we will focus on magnetic resonance imaging (MRI) studies in particular. In doing so, we will outline limitations of the available literature and provide an outlook for future research questions, which aim to integrate IUD with other behavioral and substance-based addictions.

This article offers supplementary material which is provided at the end of the article.

Schlüsselwörter: Internet-Sucht; Internetnutzungsstörung; Smartphone-Sucht; Computerspiel-Sucht; Gaming Disorder; Magnetresonanztomographie

Keywords: Internet addiction; Internet Use Disorder; Smartphone addiction; gaming disorder; magnetic resonance imaging


  • Becker, B., Wagner, D., Koester, P., Tittgemeyer, M., Mercer-Chalmers-Bender, K., Hurlemann, R., Zhang, J., Gouzoulis-Mayfrank, E., Kendrick, K., Daumann, J. (2015) Smaller amygdala and medial prefrontal cortex predict escalating stimulant use. Brain 138, 2074–2086.Google Scholar

  • Bibbey, A., Phillips, A. C., Ginty, A. T., and Carroll, D. (2015). Problematic Internet use, excessive alcohol consumption, their comorbidity and cardiovascular and cortisol reactions to acute psychological stress in a student population. Journal of behavioral addictions 4(2), 44–52.Google Scholar

  • Billieux, J., Schimmenti, A., Khazaal, Y., Maurage, P., and Heeren, A. (2015). Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research. Journal of behavioral addictions 4(3), 119–123.Google Scholar

  • Brand, M., Young, K. S., and Laier, C. (2014). Prefrontal control and Internet addiction: a theoretical model and review of neuropsychological and neuroimaging findings. Frontiers in human neuroscience 8, 375.Google Scholar

  • Brand, M., Young, K. S., Laier, C., Wölfling, K., and Potenza, M. N. (2016). Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neuroscience and Biobehavioral Reviews 71, 252–266.Google Scholar

  • Chen, J., Liang, Y., Mai, C., Zhong, X., and Qu, C. (2016). General deficit in inhibitory control of excessive smartphone users: Evidence from an event-related potential study. Frontiers in psychology 7, 511.Google Scholar

  • Daumann, J., Koester, P., Becker, B., Wagner, D., Imperati, D., Gouzoulis-Mayfrank, E., Tittgemeyer, M. (2011) Medial prefrontal gray matter volume reductions in users of amphetamine-type stimulants revealed by combined tract-based spatial statistics and voxel-based morphometry. Neuroimage 54, 794–801.Google Scholar

  • Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use. Computers in human behavior 17(2), 187–195.Google Scholar

  • Dong, G., and Potenza, M. N. (2014). A cognitive-behavioral model of Internet gaming disorder: theoretical underpinnings and clinical implications. Journal of psychiatric research 58, 7–11.Google Scholar

  • Ersche, K., D., Williams, G., B., Robbins, T., W., Bullmore, E., T. (2013) Meta-analysis of structural brain abnormalities associated with stimulant drug dependence and neuroimaging of addiction vulnerability and resilience. Curr Opin Neurobiol 23, 615–624.Google Scholar

  • Everitt, B., J., Robbins, T., W. (2016). Drug addiction: updating actions to habits to compulsions ten years on. Annual Review of Psychology 67(1), 23–50.Google Scholar

  • Finn, S. (1992). Television “addiction?” An evaluation of four competing media-use models. Journalism Quarterly 69(2), 422–435.Google Scholar

  • Gindrat, A. D., Chytiris, M., Balerna, M., Rouiller, E. M., and Ghosh, A. (2015). Use-dependent cortical processing from fingertips in touchscreen phone users. Current Biology 25(1), 109–116.Google Scholar

  • Haber, S., N. (2016). Corticostriatal circuitry. Dialogues in Clinical Neuroscience 18(1), 7–21.Google Scholar

  • Ho, R. C., Zhang, M. W., Tsang, T. Y., Toh, A. H., Pan, F., Lu, Y., … and Watanabe, H. (2014). The association between internet addiction and psychiatric co-morbidity: a meta-analysis. BMC psychiatry 14(1), 183.Google Scholar

  • Internetworldstats.com: https://www.internetworldstats.com/stats.htm, accessed on 27th March 2019Google Scholar

  • King, D. L. (2018). Comment on the global gaming industry’s statement on ICD-11 gaming disorder: a corporate strategy to disregard harm and deflect social responsibility. Addiction 113(11), 2145–2146.Google Scholar

  • King, D. L., Delfabbro, P. H., Griffiths, M. D., and Gradisar, M. (2011). Assessing clinical trials of Internet addiction treatment: A systematic review and CONSORT evaluation. Clinical psychology review 31(7), 1110–1116.Google Scholar

  • Koob, G., F., Volkow, N., D. (2016). Neurobiology of addiction: a neurocircuitry analysis. Lancet Psychiatry 3(8), 760–773.Google Scholar

  • Kühn, S., Gallinat, J. (2011). Common biology of craving across legal and illegal drugs – a quantitative meta-analysis of cue-reactivity brain response. European Journal of Neuroscience 33(7), 1318–1326.Google Scholar

  • Lee, J., Hwang, J. Y., Park, S. M., Jung, H. Y., Choi, S. W., Lee, J. Y., and Choi, J. S. (2014). Differential resting-state EEG patterns associated with comorbid depression in Internet addiction. Progress in Neuro-Psychopharmacology and Biological Psychiatry 50, 21–26.Google Scholar

  • Lin, Y. H., Lin, Y. C., Lee, Y. H., Lin, P. H., Lin, S. H., Chang, L. R., … and Kuo, T. B. (2015). Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App). Journal of psychiatric research 65, 139–145.Google Scholar

  • Millner, M. (2012). Fever reading: affect and reading badly in the early American public sphere. UPNE.Google Scholar

  • Montag, C. (2019). The Neuroscience of Smartphone/Social Media Usage and the Growing Need to Include Methods from ‘Psychoinformatics’. In Information Systems and Neuroscience(pp. 275–283). Springer, Cham.Google Scholar

  • Montag, C., Becker, B., and Gan, C. (2018a). The multi-purpose application WeChat: a review on recent research. Frontiers in Psychology 9, 2247.Google Scholar

  • Montag, C., Błaszkiewicz, K., Lachmann, B., Sariyska, R., Andone, I., Trendafilov, B., and Markowetz, A. (2015c). Recorded behavior as a valuable resource for diagnostics in mobile phone addiction: evidence from psychoinformatics. Behavioral Sciences 5(4), 434–442.Google Scholar

  • Montag, C., Błaszkiewicz, K., Sariyska, R., Lachmann, B., Andone, I., Trendafilov, B., … and Markowetz, A. (2015). Smartphone usage in the 21st century: who is active on WhatsApp?. BMC research notes 8(1), 331.Google Scholar

  • Montag, C., and Diefenbach, S. (2018). Towards homo digitalis: Important research issues for psychology and the neurosciences at the dawn of the internet of things and the digital society. Sustainability 10(2), 415.Google Scholar

  • Montag, C., Duke, É., and Markowetz, A. (2016). Toward Psychoinformatics: Computer science meets psychology. Computational and mathematical methods in medicine, 2016. https://www.hindawi.com/journals/cmmm/2016/2983685/abs/Google Scholar

  • Montag, C., Duke, É., and Reuter, M. (2017). A short summary of neuroscientific findings on Internet addiction. In Internet Addiction (pp. 209–218). Springer, Cham.Google Scholar

  • Montag, C. and Elhai, J. D. (in press). A new agenda for personality psychology in the digital age? Personality and Individual Differences.Google Scholar

  • Montag, C., Kirsch, P., Sauer, C., Markett, S., and Reuter, M. (2012). The role of the CHRNA4 gene in Internet addiction: a case-control study. Journal of addiction medicine 6(3), 191–195.Google Scholar

  • Montag, C., Markowetz, A., Blaszkiewicz, K., Andone, I., Lachmann, B., Sariyska, R., … and Weber, B. (2017). Facebook usage on smartphones and gray matter volume of the nucleus accumbens. Behavioural brain research 329, 221–228.Google Scholar

  • Montag, C., and Panksepp, J. (2017). Primary emotional systems and personality: an evolutionary perspective. Frontiers in psychology 8, 464.Google Scholar

  • Montag, C., and Reuter, M. (2017a). Internet Addiction. Springer International Publishing.Google Scholar

  • Montag, C., and Reuter, M. (2017b). Molecular genetics, personality, and Internet addiction revisited. In Internet Addiction (pp. 141–160). Springer, Cham.Google Scholar

  • Montag, C., Reuter, M., and Markowetz, A. (2015a). The impact of Psychoinformatics on internet addiction. In Internet Addiction(pp. 143–150). Springer, Cham.Google Scholar

  • Montag, C., Sindermann, C., Becker, B., and Panksepp, J. (2016). An affective neuroscience framework for the molecular study of Internet addiction. Frontiers in psychology 7, 1906.Google Scholar

  • Montag, C., Zhao, Z., Sindermann, C., Xu, L., Fu, M., Li, J., … and Becker, B. (2018b). Internet Communication Disorder and the structure of the human brain: initial insights on WeChat addiction. Scientific reports 8(1), 2155.Google Scholar

  • NewYorkTimes.com, https://www.nytimes.com/2018/06/17/business/video-game-addiction.html (visited on 7th December 2018)Google Scholar

  • Peterka-Bonetta, J., Sindermann, C., Sha, P., Zhou, M., and Montag, C. (2019). The relationship between Internet Use Disorder, depression and burnout among Chinese and German college students. Addictive behaviors 89, 188–199.Google Scholar

  • Petry, N. M., and O’Brien, C. P. (2013). Internet gaming disorder and the DSM‐5. Addiction 108(7), 1186–1187.Google Scholar

  • Pontes, H. M., and Griffiths, M. D. (2015). Measuring DSM-5 Internet gaming disorder: Development and validation of a short psychometric scale. Computers in Human Behavior 45, 137–143.Google Scholar

  • Pontes, H. M., Schivinski, B., Sindermann, C., Li, M., Becker, B., Zhou, M. and Montag, C. (9999). Measurement and conceptualization of Gaming Disorder according to the World Health Organization framework: The development of the Gaming Disorder Test. International Journal of Mental Health and Addiction.Google Scholar

  • Potenza, M. N., Higuchi, S., and Brand, M. (2018). Call for research into a wider range of behavioural addictions. Nature 555, 30.Google Scholar

  • Rehbein, F., Kliem, S., Baier, D., Mößle, T., and Petry, N. M. (2015). Prevalence of internet gaming disorder in German adolescents: Diagnostic contribution of the nine DSM‐5 criteria in a state‐wide representative sample. Addiction 110(5), 842–851.Google Scholar

  • Robbins, T. W., Gillan, C. M., Smith, D. G., de Wit, S., and Ersche, K. D. (2012). Neurocognitive endophenotypes of impulsivity and compulsivity: towards dimensional psychiatry. Trends in cognitive sciences 16(1), 81–91.Google Scholar

  • Sariyska, R., Reuter, M., Bey, K., Sha, P., Li, M., Chen, Y. F., … and Montag, C. (2014). Self-esteem, personality and internet addiction: a cross-cultural comparison study. Personality and Individual Differences 61, 28–33.Google Scholar

  • Sariyska, R., Lachmann, B., Markett, S., Reuter, M., and Montag, C. (2017). Individual differences in implicit learning abilities and impulsive behavior in the context of Internet addiction and Internet Gaming Disorder under the consideration of gender. Addictive behaviors reports 5, 19–28.Google Scholar

  • Statista.com (Facebook statistics): https://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/, (Smartphone statistics): https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/, both accessed on 27th March 2019Google Scholar

  • Sutherland, M., T., Riedel, M., C., Flannery, J., S., Yanes, J., A., Fox, P., T., Stein, E., A., Laird, A., R (2016) Chronic cigarette smoking is linked with structural alterations in brain regions showing acute nicotinic functional modulations. Behav Brain Funct 12, 16.Google Scholar

  • Targhetta, R., Nalpas, B., and Perney, P. (2013). Argentine tango: Another behavioral addiction?. Journal of Behavioral Addictions 2(3), 179–186.Google Scholar

  • Tao, R., Huang, X., Wang, J., Zhang, H., Zhang, Y., and Li, M. (2010). Proposed diagnostic criteria for internet addiction. Addiction 105(3), 556–564.Google Scholar

  • Vogel, E. A., Rose, J. P., Roberts, L. R., and Eckles, K. (2014). Social comparison, social media, and self-esteem. Psychology of Popular Media Culture 3(4), 206–222.Google Scholar

  • Yao, Y. W., Liu, L., Ma, S. S., Shi, X. H., Zhou, N., Zhang, J. T., and Potenza, M. N. (2017). Functional and structural neural alterations in Internet gaming disorder: A systematic review and meta-analysis. Neuroscience and Biobehavioral Reviews 83, 313–324.Google Scholar

  • Young, K. S. (1996). Psychology of computer use: XL. Addictive use of the Internet: a case that breaks the stereotype. Psychological reports 79(3), 899–902.Google Scholar

  • Winkler, A., Dörsing, B., Rief, W., Shen, Y., and Glombiewski, J. A. (2013). Treatment of internet addiction: a meta-analysis. Clinical psychology review 33(2), 317–329.Google Scholar

  • World Health Organization, http://www.who.int/features/qa/gaming-disorder/en/, accessed on 27th November 2018Google Scholar

  • Xiao, P., Dai, Z., Zhong, J., Shi, H., Pan, P. (2015) Regional gray matter deficits sin alcohol dependence: A meta-analysis of voxel-based morphometry studies. Drug Alcohol Depend 153,22–28.Google Scholar

  • Zhao, Z., Ma, X., Geng, Y., Zhao, W., Zhou, F., Wang, J., Markett, S., Ma, Y., Biswal, B., Kendrick, K., Becker, B. (2019). Oxytocin differentially modulates specific dorsal and ventral striatal functional connections with frontal and cerebellar regions. NeuroImage 184, 781–789.Google Scholar

  • Zhou, F., Montag, C., Sariyska, R., Lachmann, B., Reuter, M., Weber, B., … and Becker, B. (2019). Orbitofrontal gray matter deficits as marker of Internet gaming disorder: converging evidence from a cross‐sectional and prospective longitudinal design. Addiction Biology 24(1), 100–109.Google Scholar

  • Zhou, F., Zimmermann, K., Xin, F., Scheele, D., Dau, W., Banger, M., Weber, B., Hurlemann, R., Kendrick, K., Becker, B. (2018) Shifted balance of dorsal versus ventral striatal communication with frontal reward and regulatory regions in cannabis dependent males. Human Brain Mapping 39, 5062–5073.Google Scholar

  • Zimmermann, K., Kendrick, K., Scheele, D., Dau, W., Banger, M., Maier, W., Weber, B., Ma, Y., Hurlemann, R., Becker, B. (2018) Altered reward processing in abstinent dependent cannabis users: social context matters. BioRxiv.org; https://doi.org/10.1101/278044 (preprint)Google Scholar

  • Zimmermann, K., Yao, S., Heinz, M., Zhou, F., Dau, W., Banger, M., Weber, B., Hurlemann, R., Becker, B. (2017) Altered orbitofrontal activity and dorsal striatal connectivity during emotional processing in dependent marijuana users after 28-days of abstinence. Psychopharmacology (Berl) 235, 849–859.Google Scholar

About the article

Prof. Dr. Benjamin Becker

Benjamin Becker is currently a thousand talent awarded Professor and head of the Neurotherapy – Social Cognition and Affective Neuroscience (neuSCAN.net) Laboratory at the University of Electronic Science and Technology of China (UESTC) as well as Agreement Professor at the Fourth People’s Hospital in Chengdu (China). He received his Diploma in Psychology (2005) and PhD (2010) at the University of Trier and Heinrich Heine University of Duesseldorf in Germany, respectively. During his postdoctoral studies at the Departments of Psychiatry in Cologne and Bonn (Germany) his research employed advanced neuroimaging approaches to explore the emotional circuits of the human brain in healthy subjects and determine dysregulations of these circuits in patients with neuropsychiatric disorders, particularly substance use disorders. His current projects are funded by competitive national and international research grants and aim to develop innovative neuromodulatory strategies to regulate cognition-emotion circuitries via pharmacological and real-time neurofeedback approaches with the ultimate aim to establish better treatments for neuropsychiatric disorders. He is editorial board member of Psychopharmacology and BMC Neuroscience.

Prof. Dr. Christian Montag

Christian Montag received his diploma in psychology in September 2006 at Justus-Liebig-University in Giessen, Germany. In 2009 he achieved his PhD degree on his psychobiological works testing Gray’s revised reinforcement sensitivity theory and in 2011 he got the venia legendi for psychology at the University of Bonn, Germany. Since September 2014 he is Professor for Molecular Psychology at Ulm University, Germany (Heisenberg-Professor funded by the German Research Foundation). In addition, in February 2016 he has been appointed as agreement/visiting professor at the University of Electronic Science and Technology (UESTC) in Chengdu, China. Christian Montag is currently on the editorial board of the journals Personality Neuroscience, Addictive Behaviors, International Journal of Environmental Research and Public Health and Digital Psychology. Moreover, he is (co-) editor of the book series Studies in Neuroscience, Psychology and Behavioral Economics.

Christian Montag is interested in the molecular genetics of personality and emotions. He combines molecular genetics with brain imaging techniques such as structural/functional MRI to better understand individual differences in human nature. Adding to this he conducts research in the fields of Affective Neuroscience, Neuroeconomics and (Internet) addiction including new approaches from Psychoinformatics. Psychoinformatics describes the collaboration between computer science and psychology to predict psychological variables such as personality from human-machine interaction data (e. g. smartphone data). See for an exemplarily approach the work mentioned in the reference section by Montag et al. (2015c) and Montag et al. (2016).

Published Online: 2019-06-04

Published in Print: 2019-05-27

Citation Information: Neuroforum, Volume 25, Issue 2, Pages 99–107, ISSN (Online) 2363-7013, ISSN (Print) 0947-0875, DOI: https://doi.org/10.1515/nf-2018-0026.

Export Citation

© 2019 Walter de Gruyter GmbH, Berlin/Boston.Get Permission

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

Christian Montag, Bernd Lachmann, Marc Herrlich, and Katharina Zweig
International Journal of Environmental Research and Public Health, 2019, Volume 16, Number 14, Page 2612

Comments (0)

Please log in or register to comment.
Log in