Journal of the Korean Academy of Child and Adolescent Psychiatry

Korean Academy of Child and Adolescent Psychiatry (대한소아청소년정신의학회)
권호 표지
DOI QR코드

DOI QR Code

Reduced Volume of a Brainstem Substructure in Adolescents with Problematic Smartphone Use

  • Cho, In Hee (Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Yoo, Jae Hyun (Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Chun, Ji-Won (Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Cho, Hyun (Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Kim, Jin-Young (Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Choi, Jihye (Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Kim, Dai-Jin (Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea)
  • Received : 2021.03.23
  • Accepted : 2021.05.10
  • Published : 2021.10.01
Download PDF
⟨ Previous Next ⟩

Abstract

Objectives: Despite the growing concern regarding the adverse effects related to problematic smartphone use (PSU), little is known about underlying morphologic changes in the brain. The brainstem is a deep brain structure that consists of several important nuclei associated with emotions, sensations, and motor functions. In this study, we sought to examine the difference in the volume of brainstem substructures among adolescents with and without PSU. Methods: A total of 87 Korean adolescents participated in this study. The PSU group (n=20, age=16.2±1.1, female:male=12:8) was designated if participants reported a total Smartphone Addiction Proneness Scale (SAPS) score of ≥42, whereas the remaining participants were assigned to the control group (n=67, age=15.3±1.7, female:male=19:48). High-resolution T1 magnetic resonance imaging was performed, and the volume of each of the four brainstem substructures [midbrain, pons, medulla, and superior cerebellar peduncle (SCP)] was measured. Analysis of covariance was conducted to reveal group differences after adjusting for effects of age, gender, whole brainstem volume, depressive symptoms, and impulsivity. Results: The PSU group showed a significantly smaller volume of the SCP than the control group (F=8.273, p=0.005). The volume of the SCP and the SAPS score were negatively correlated (Pearson's r=-0.218, p=0.047). Conclusion: The present study is the first to reveal an altered volume of the brainstem substructure among adolescents with PSU. This finding suggests that the altered white matter structure in the brainstem could be one of the neurobiological mechanisms underlying behavioral changes in PSU.

Keywords

Acknowledgement

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2014M3C7A1062893).

References

  1. Sohn SY, Rees P, Wildridge B, Kalk NJ, Carter B. Prevalence of problematic smartphone usage and associated mental health outcomes amongst children and young people: a systematic review, meta-analysis and GRADE of the evidence. BMC Psychiatry 2019;19:356. https://doi.org/10.1186/s12888-019-2350-x
  2. National Information Society Agency. 2019 the survey on smartphone overdependence (report no. NIA VIII-RSE-C-19067). Daegu: National Information Society Agency;2019.
  3. Bianchi A, Phillips JG. Psychological predictors of problem mobile phone use. Cyberpsychol Behav 2005;8:39-51. https://doi.org/10.1089/cpb.2005.8.39
  4. Demirci K, Akgonul M, Akpinar A. Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. J Behav Addict 2015;4:85-92. https://doi.org/10.1556/2006.4.2015.010
  5. Matar Boumosleh J, Jaalouk D. Depression, anxiety, and smartphone addiction in university students-A cross sectional study. PLoS One 2017;12:e0182239. https://doi.org/10.1371/journal.pone.0182239
  6. Grant JE, Lust K, Chamberlain SR. Problematic smartphone use associated with greater alcohol consumption, mental health issues, poorer academic performance, and impulsivity. J Behav Addict 2019;8:335-342. https://doi.org/10.1556/2006.8.2019.32
  7. Chen J, Liang Y, Mai C, Zhong X, Qu C. General deficit in inhibitory control of excessive smartphone users: evidence from an eventrelated potential study. Front Psychol 2016;7:511.
  8. Montag C, Markowetz A, Blaszkiewicz K, Andone I, Lachmann B, Sariyska R, et al. Facebook usage on smartphones and gray matter volume of the nucleus accumbens. Behav Brain Res 2017;329:221-228. https://doi.org/10.1016/j.bbr.2017.04.035
  9. Montag C, Zhao Z, Sindermann C, Xu L, Fu M, Li J, et al. Internet Communication Disorder and the structure of the human brain: initial insights on WeChat addiction. Sci Rep 2018;8:2155. https://doi.org/10.1038/s41598-018-19904-y
  10. Horvath J, Mundinger C, Schmitgen MM, Wolf ND, Sambataro F, Hirjak D, et al. Structural and functional correlates of smartphone addiction. Addict Behav 2020;105:106334. https://doi.org/10.1016/j.addbeh.2020.106334
  11. Lee D, Namkoong K, Lee J, Lee BO, Jung YC. Lateral orbitofrontal gray matter abnormalities in subjects with problematic smartphone use. J Behav Addict 2019;8:404-411. https://doi.org/10.1556/2006.8.2019.50
  12. Tymofiyeva O, Yuan JP, Kidambi R, Huang CY, Henje E, Rubinstein ML, et al. Neural correlates of smartphone dependence in adolescents. Front Hum Neurosci 2020;14:564629. https://doi.org/10.3389/fnhum.2020.564629
  13. Chun JW, Choi J, Cho H, Choi MR, Ahn KJ, Choi JS, et al. Role of frontostriatal connectivity in adolescents with excessive smartphone use. Front Psychiatry 2018;9:437. https://doi.org/10.3389/fpsyt.2018.00437
  14. Hurley RA, Flashman LA, Chow TW, Taber KH. The brainstem: anatomy, assessment, and clinical syndromes. J Neuropsychiatry Clin Neurosci 2010;22:iv, 1-7.
  15. Siciliano CA, Noamany H, Chang CJ, Brown AR, Chen X, Leible D, et al. A cortical-brainstem circuit predicts and governs compulsive alcohol drinking. Science 2019;366:1008-1012. https://doi.org/10.1126/science.aay1186
  16. Shinohara F, Asaoka Y, Kamii H, Minami M, Kaneda K. Stress augments the rewarding memory of cocaine via the activation of brainstem-reward circuitry. Addict Biol 2019;24:509-521. https://doi.org/10.1111/adb.12617
  17. Bissonette GB, Roesch MR. Development and function of the midbrain dopamine system: what we know and what we need to. Genes Brain Behav 2016;15:62-73. https://doi.org/10.1111/gbb.12257
  18. Kim D, Lee Y, Lee J, Nam JK, Chung Y. Development of Korean smartphone addiction proneness scale for youth. PLoS One 2014;9:e97920. https://doi.org/10.1371/journal.pone.0097920
  19. Beck AT, Steer RA, Brown GK. Beck depression inventory-II. San Antonio: Psychological Corporation;1996.
  20. Tangney JP, Baumeister RF, Boone AL. High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. J Pers 2004;72:271-324. https://doi.org/10.1111/j.0022-3506.2004.00263.x
  21. Iglesias JE, Van Leemput K, Bhatt P, Casillas C, Dutt S, Schuff N, et al. Bayesian segmentation of brainstem structures in MRI. Neuroimage 2015;113:184-195. https://doi.org/10.1016/j.neuroimage.2015.02.065
  22. 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. https://doi.org/10.1186/1744-9081-8-41
  23. Zhang JT, Yao YW, Potenza MN, Xia CC, Lan J, Liu L, et al. Effects of craving behavioral intervention on neural substrates of cue-induced craving in internet gaming disorder. Neuroimage Clin 2016; 12:591-599. https://doi.org/10.1016/j.nicl.2016.09.004
  24. Tao J, Wang X, Zhong Z, Han H, Liu S, Wen S, et al. Alterations of white matter fractional anisotropy in unmedicated obsessive-compulsive disorder. Neuropsychiatr Dis Treat 2017;13:69-76. https://doi.org/10.2147/ndt.s123669
  25. Lazaro L, Calvo A, Ortiz AG, Ortiz AE, Morer A, Moreno E, et al. Microstructural brain abnormalities and symptom dimensions in child and adolescent patients with obsessive-compulsive disorder: a diffusion tensor imaging study. Depress Anxiety 2014;31:1007-1017. https://doi.org/10.1002/da.22330
  26. Bora E, Yucel M, Fornito A, Pantelis C, Harrison BJ, Cocchi L, et al. White matter microstructure in opiate addiction. Addict Biol 2012;17:141-148. https://doi.org/10.1111/j.1369-1600.2010.00266.x
  27. O'Neill J, Cardenas VA, Meyerhoff DJ. Separate and interactive effects of cocaine and alcohol dependence on brain structures and metabolites: quantitative MRI and proton MR spectroscopic imaging. Addict Biol 2001;6:347-361. https://doi.org/10.1080/13556210020077073
  28. Catani M, Jones DK, Daly E, Embiricos N, Deeley Q, Pugliese L, et al. Altered cerebellar feedback projections in Asperger syndrome. Neuroimage 2008;41:1184-1191. https://doi.org/10.1016/j.neuroimage.2008.03.041
  29. Hanaie R, Mohri I, Kagitani-Shimono K, Tachibana M, Azuma J, Matsuzaki J, et al. Altered microstructural connectivity of the superior cerebellar peduncle is related to motor dysfunction in children with autistic spectrum disorders. Cerebellum 2013;12:645-656. https://doi.org/10.1007/s12311-013-0475-x
  30. Shadmehr R, Krakauer JW. A computational neuroanatomy for motor control. Exp Brain Res 2008;185:359-381. https://doi.org/10.1007/s00221-008-1280-5
  31. Koob GF. Drug addiction: the yin and yang of hedonic homeostasis. Neuron 1996;16:893-896. https://doi.org/10.1016/S0896-6273(00)80109-9
  32. Bauer DJ, Kerr AL, Swain RA. Cerebellar dentate nuclei lesions reduce motivation in appetitive operant conditioning and open field exploration. Neurobiol Learn Mem 2011;95:166-175. https://doi.org/10.1016/j.nlm.2010.12.009
  33. Thoma P, Bellebaum C, Koch B, Schwarz M, Daum I. The cerebellum is involved in reward-based reversal learning. Cerebellum 2008;7:433-443. https://doi.org/10.1007/s12311-008-0046-8