J Korean Med Sci.  2017 Jul;32(7):1160-1165. 10.3346/jkms.2017.32.7.1160.

Comparison of Electroencephalography (EEG) Coherence between Major Depressive Disorder (MDD) without Comorbidity and MDD Comorbid with Internet Gaming Disorder

• Youh J
• Hong JS
• Han DH
• Chung US
• Min KJ
• Lee YS
• Kim SM

• KMID: 2379612
• DOI: http://doi.org/10.3346/jkms.2017.32.7.1160

Abstract

Internet gaming disorder (IGD) has many comorbid psychiatric problems including major depressive disorder (MDD). In the present study, we compared the neurobiological differences between MDD without comorbidity (MDD-only) and MDD comorbid with IGD (MDD+IGD) by analyzing the quantitative electroencephalogram (QEEG) findings. We recruited 14 male MDD+IGD (mean age, 20.0 ± 5.9 years) and 15 male MDD-only (mean age, 20.3 ± 5.5 years) patients. The electroencephalography (EEG) coherences were measured using a 21-channel digital EEG system and computed to assess synchrony in the frequency ranges of alpha (7.5-12.5 Hz) and beta (12.5-35.0 Hz) between the following 12 electrode site pairs: inter-hemispheric (Fp1-Fp2, F7-F8, T3-T4, and P3-P4) and intra-hemispheric (F7-T3, F8-T4, C3-P3, C4-P4, T5-O1, T6-O2, P3-O1, and P4-O2) pairs. Differences in inter- and intra-hemispheric coherence values for the frequency bands between groups were analyzed using the independent t-test. Inter-hemispheric coherence value for the alpha band between Fp1-Fp2 electrodes was significantly lower in MDD+IGD than MDD-only patients. Intra-hemispheric coherence value for the alpha band between P3-O1 electrodes was higher in MDD+IGD than MDD-only patients. Intra-hemispheric coherence values for the beta band between F8-T4, T6-O2, and P4-O2 electrodes were higher in MDD+IGD than MDD-only patients. There appears to be an association between decreased inter-hemispheric connectivity in the frontal region and vulnerability to attention problems in the MDD+IGD group. Increased intra-hemisphere connectivity in the fronto-temporo-parieto-occipital areas may result from excessive online gaming.

Keyword

Internet Gaming Disorder; Major Depressive Disorder; Quantitative Electroencephalogram; Coherence

MeSH Terms

Comorbidity*
Depressive Disorder, Major*
Electrodes
Electroencephalography*
Humans
Immunoglobulin D
Internet*
Male
Immunoglobulin D

Figure

• 

  Fig. 1 Comparison of coherence between MDD+IGD and MDD-only groups. (A) Inter-hemispheric coherence. The value for the alpha band between Fp1–Fp2 electrodes was significantly lower in the MDD+IGD group than the MDD-only group. (B) Intra-hemispheric coherence. The value for the alpha band between P3–O1 electrodes and the beta band between F8–T4, T6–O2, and P4–O2 electrodes were higher in the MDD+IGD group than the MDD-only group. MDD+IGD = major depressive disorder comorbid with internet gaming disorder, MDD-only = major depressive disorder without comorbidity.

Reference

1. Mak KK, Lai CM, Watanabe H, Kim DI, Bahar N, Ramos M, Young KS, Ho RC, Aum NR, Cheng C. Epidemiology of Internet behaviors and addiction among adolescents in six Asian countries. Cyberpsychol Behav Soc Netw. 2014; 17:720–728.

2. Young KS. Internet addiction: the emergence of a new clinical disorder. Cyberpsychol Behav. 2009; 1:237–244.

3. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders: DSM-5®. 5th ed. Washington, D.C.: American Psychiatric Association;2013.

4. Han DH, Kim SM, Bae S, Renshaw PF, Anderson JS. Brain connectivity and psychiatric comorbidity in adolescents with Internet gaming disorder. Addict Biol. 2017; 22:802–812.

5. Park JH, Han DH, Kim BN, Cheong JH, Lee YS. Correlations among social anxiety, self-esteem, impulsivity, and game genre in patients with problematic online game playing. Psychiatry Investig. 2016; 13:297–304.

6. Leuchter AF, Hunter AM, Krantz DE, Cook IA. Intermediate phenotypes and biomarkers of treatment outcome in major depressive disorder. Dialogues Clin Neurosci. 2014; 16:525–537.

7. Choi JS, Park SM, Lee J, Hwang JY, Jung HY, Choi SW, Kim DJ, Oh S, Lee JY. Resting-state beta and gamma activity in Internet addiction. Int J Psychophysiol. 2013; 89:328–333.

8. Son KL, Choi JS, Lee J, Park SM, Lim JA, Lee JY, Kim SN, Oh S, Kim DJ, Kwon JS. Neurophysiological features of Internet gaming disorder and alcohol use disorder: a resting-state EEG study. Transl Psychiatry. 2015; 5:e628.

9. Park JH, Hong JS, Han DH, Min KJ, Lee YS, Kee BS, Kim SM. Comparison of QEEG findings between adolescents with attention deficit hyperactivity disorder (ADHD) without comorbidity and ADHD comorbid with Internet gaming disorder. J Korean Med Sci. 2017; 32:514–521.

10. Olbrich S, Arns M. EEG biomarkers in major depressive disorder: discriminative power and prediction of treatment response. Int Rev Psychiatry. 2013; 25:604–618.

11. Jaworska N, Blier P, Fusee W, Knott V. α power, α asymmetry and anterior cingulate cortex activity in depressed males and females. J Psychiatr Res. 2012; 46:1483–1491.

12. Bruder GE, Sedoruk JP, Stewart JW, McGrath PJ, Quitkin FM, Tenke CE. Electroencephalographic alpha measures predict therapeutic response to a selective serotonin reuptake inhibitor antidepressant: pre- and post-treatment findings. Biol Psychiatry. 2008; 63:1171–1177.

13. Shaw JC. An introduction to the coherence function and its use in EEG signal analysis. J Med Eng Technol. 1981; 5:279–288.

14. Jeong HG, Ko YH, Han C, Kim YK, Joe SH. Distinguishing quantitative electroencephalogram findings between adjustment disorder and major depressive disorder. Psychiatry Investig. 2013; 10:62–68.

15. Olbrich S, Tränkner A, Chittka T, Hegerl U, Schönknecht P. Functional connectivity in major depression: increased phase synchronization between frontal cortical EEG-source estimates. Psychiatry Res. 2014; 222:91–99.

16. Lee TW, Wu YT, Yu YW, Chen MC, Chen TJ. The implication of functional connectivity strength in predicting treatment response of major depressive disorder: a resting EEG study. Psychiatry Res. 2011; 194:372–377.

17. Sun Y, Li Y, Zhu Y, Chen X, Tong S. Electroencephalographic differences between depressed and control subjects: an aspect of interdependence analysis. Brain Res Bull. 2008; 76:559–564.

18. Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J. An inventory for measuring depression. Arch Gen Psychiatry. 1961; 4:561–571.

19. First MB, Williams JB, Karg RS, Spitzer RL. User's Guide for the SCID-5-CV Structured Clinical Interview for DSM-5 Disorders: Clinician Version. Arlington, VA: American Psychiatric Association;2016.

20. Yoo HJ, Cho SC, Ha J, Yune SK, Kim SJ, Hwang J, Chung A, Sung YH, Lyoo IK. Attention deficit hyperactivity symptoms and Internet addiction. Psychiatry Clin Neurosci. 2004; 58:487–494.

21. Beck AT, Epstein N, Brown G, Steer RA. An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol. 1988; 56:893–897.

22. Conners C. Conners' Rating Scales--Revised: Technical Manual. North Tonawanda, NY: Multi-Health Systems;1997.

23. Bahn GH, Shin MS, Cho SC, Hong KE. A preliminary study for the development of the assessment scale for ADHD in adolescents: reliability and validity for CASS (S). J Child Adolesc Psychiatry. 2001; 12:218–224.

24. DuPaul GJ. Parent and teacher ratings of ADHD symptoms: psychometric properties in a community-based sample. J Clin Child Psychol. 1991; 20:245–253.

25. So YK, Noh JS, Kim YS, Ko SG, Koh YJ. The reliability and validity of Korean parent and teacher ADHD rating scale. J Korean Neuropsychiatr Assoc. 2002; 41:283–289.

26. Tabachnick BG, Fidell LS. Using Multivariate Statistics. 2nd ed. New York, NY: Harper & Row;1989.

27. Olbrich S, van Dinteren R, Arns M. Personalized medicine: review and perspectives of promising baseline EEG biomarkers in major depressive disorder and attention deficit hyperactivity disorder. Neuropsychobiology. 2015; 72:229–240.

28. Barry RJ, Clarke AR, McCarthy R, Selikowitz M. EEG coherence in attention-deficit/hyperactivity disorder: a comparative study of two DSM-IV types. Clin Neurophysiol. 2002; 113:579–585.

29. Yen JY, Ko CH, Yen CF, Wu HY, Yang MJ. The comorbid psychiatric symptoms of Internet addiction: attention deficit and hyperactivity disorder (ADHD), depression, social phobia, and hostility. J Adolesc Health. 2007; 41:93–98.

30. Han DH, Lee YS, Na C, Ahn JY, Chung US, Daniels MA, Haws CA, Renshaw PF. The effect of methylphenidate on Internet video game play in children with attention-deficit/hyperactivity disorder. Compr Psychiatry. 2009; 50:251–256.

31. 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.

32. Jeong BS, Han DH, Kim SM, Lee SW, Renshaw PF. White matter connectivity and Internet gaming disorder. Addict Biol. 2016; 21:732–742.

33. González JJ, Méndez LD, Mañas S, Duque MR, Pereda E, De Vera L. Performance analysis of univariate and multivariate EEG measurements in the diagnosis of ADHD. Clin Neurophysiol. 2013; 124:1139–1150.

34. Barry RJ, Clarke AR. Resting state brain oscillations and symptom profiles in attention deficit/hyperactivity disorder. Suppl Clin Neurophysiol. 2013; 62:275–287.

35. Rieck RW, Ansari MS, Whetsell WO Jr, Deutch AY, Kessler RM. Distribution of dopamine D2-like receptors in the human thalamus: autoradiographic and PET studies. Neuropsychopharmacology. 2004; 29:362–372.

36. Bavelier D, Green CS, Han DH, Renshaw PF, Merzenich MM, Gentile DA. Brains on video games. Nat Rev Neurosci. 2011; 12:763–768.

37. 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.

38. De Benedictis A, Duffau H, Paradiso B, Grandi E, Balbi S, Granieri E, Colarusso E, Chioffi F, Marras CE, Sarubbo S. Anatomo-functional study of the temporo-parieto-occipital region: dissection, tractographic and brain mapping evidence from a neurosurgical perspective. J Anat. 2014; 225:132–151.

39. Britz J, Van De Ville D, Michel CM. BOLD correlates of EEG topography reveal rapid resting-state network dynamics. Neuroimage. 2010; 52:1162–1170.

40. Musso F, Brinkmeyer J, Mobascher A, Warbrick T, Winterer G. Spontaneous brain activity and EEG microstates. A novel EEG/fMRI analysis approach to explore resting-state networks. Neuroimage. 2010; 52:1149–1161.