Addiction and Quantitative Electroencephalography

Jaewon Lee

doi:10.4306/jknpa.2019.58.2.115

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Lee: Addiction and Quantitative Electroencephalography

Special Article

The Clinical Use of Electroencephalography in Psychiatry

Journal of Korean Neuropsychiatric Association 2019; 58(2): 115-124.

Published online: 31 May 2019

DOI: https://doi.org/10.4306/jknpa.2019.58.2.115

Addiction and Quantitative Electroencephalography

Jaewon Lee, MD, PhD

Easybrain Clinic, Seoul, Korea.

Address for correspondence: Jaewon Lee, MD, PhD. Easybrain Clinic, 174 Saimdang-ro, Seocho-gu, Seoul 06627, Korea. Tel +82-2-583-9080, Fax +82-2-583-9082, sonton21@gmail.com

Received 26 April 2019 Revised 8 May 2019 Accepted 8 May 2019

Korean Neuropsychiatric Association

Abstract

Quantitative electroencephalography (QEEG) has a long history and its clinical usefulness has gradually become well known. QEEG is a noninvasive, easy, comfortable and inexpensive way to check the brain status, but it is not specific to a diagnosis and requires sufficient experience in its clinical interpretation. The techniques and parameters of QEEG are increasingly being developed and studied, so their utilization will become more widespread in the future. QEEG in addiction disorders has not been fully studied, but it has many possibilities. The symptoms of addiction disorder and QEEG characteristics in some addictions show features that are clinically beneficial to diagnosis and treatment. Various complementary studies in the future are expected to make it more useful in clinics.

Keywords: Quantitative electroencephalography, Addiction, Alcohol addiction, Internet gaming disorder

Notes

^{Conflicts of Interest} The author has no financial conflicts of interest.

References

1. Olejniczak P. Neurophysiologic basis of EEG. J Clin Neurophysiol. 2006; 23:186–189.

2. Nunez PL. The brain wave equation: a model for the EEG. Math Biosci. 1974; 21:279–297.

3. Smith SJ. EEG in the diagnosis, classification, and management of patients with epilepsy. J Neurol Neurosurg Psychiatry. 2005; 76:Suppl 2. ii2–ii7.

4. Ely EW, Truman B, Manzi DJ, Sigl JC, Shintani A, Bernard GR. Consciousness monitoring in ventilated patients: bispectral EEG monitors arousal not delirium. Intensive Care Med. 2004; 30:1537–1543.

5. Frank Y, Kravath RE, Pollak CP, Weitzman ED. Obstructive sleep apnea and its therapy: clinical and polysomnographic manifestations. Pediatrics. 1983; 71:737–742.

6. Alper KR, Prichep LS, Kowalik S, Rosenthal MS, John ER. Persistent QEEG abnormality in crack cocaine users at 6 months of drug abstinence. Neuropsychopharmacology. 1998; 19:1–9.

7. Bares M, Brunovsky M, Kopecek M, Stopkova P, Novak T, Kozeny J, et al. Changes in QEEG prefrontal cordance as a predictor of response to antidepressants in patients with treatment resistant depressive disorder: a pilot study. J Psychiatr Res. 2007; 41:319–325.

8. Kim BN, Shin SU, Kwon JS, Shin MS, Cho SC, Hong KE. QEEG findings in attention deficit/hyperactivity disorder. J Korean Neuropsychiatr Assoc. 2000; 39:208–218.

9. Gschwandtner U, Zimmermann R, Pflueger MO, Riecher-Rössler A, Fuhr P. Negative symptoms in neuroleptic-naïve patients with first-episode psychosis correlate with QEEG parameters. Schizophr Res. 2009; 115:231–236.

10. Jokić-Begić N, Begić D. Quantitative electroencephalogram (qEEG) in combat veterans with post-traumatic stress disorder (PTSD). Nord J Psychiatry. 2003; 57:351–355.

11. Pop-Jordanova N, Zorcec T, Demerdzieva A, Gucev Z. QEEG characteristics and spectrum weighted frequency for children diagnosed as autistic spectrum disorder. Nonlinear Biomed Phys. 2010; 4:4.

12. Duff J. The usefulness of quantitative EEG (QEEG) and neurotherapy in the assessment and treatment of post-concussion syndrome. Clin EEG Neurosci. 2004; 35:198–209.

13. Arns M, Drinkenburg W, Kenemans JL. The effects of QEEG-informed neurofeedback in ADHD: an open-label pilot study. Appl Psychophysiol Biofeedback. 2012; 37:171–180.

14. Hunter AM, Leuchter AF. Changes in resting-state quantitative electroencephalography (qEEG) and symptom severity during repetitive transcranial magnetic stimulation (rTMS) treatment in major depressive disorder (MDD): case-studies. Brain Stimul. 2016; 9:e4–e5.

15. Thatcher RW. Normative EEG databases and EEG biofeedback. J Neurother. 1998; 2:8–39.

16. Evans JR, Abarbanel A. Introduction to quantitative EEG and neurofeedback. London: Elsevier;1999.

17. Cooley JW, Lewis PA, Welch PD. Historical notes on the fast Fourier transform. Proc IEEE. 1967; 55:1675–1677.

18. Kaiser DA. Basic principles of quantitative EEG. J Adult Dev. 2005; 12:99–104.

19. Dietsch G. Fourier-analyse von elektrencephalogrammen des menschen. Pflugers Arch Gesamte Physiol Menschen Tiere. 1932; 230:106–112.

20. Brazier MAB, Cobb WA, Fischgold H, Gastaut H, Gloor P, Hess R, et al. Preliminary proposal for an EEG terminology by the Terminology Committee of the International Federation for electroencephalography and clinical neurophysiology. Electroencephalogr Clin Neurophysiol. 1961; 13:646–650.

21. Berger H. Über das elektrenkephalogramm des menschen. Eur Arch Psychiatry Clin Neurosci. 1929; 87:527–570.

22. Cooley JW, Tukey JW. An algorithm for the machine calculation of complex Fourier series. Math Comput. 1965; 19:297–301.

23. Nowlis DP, Kamiya J. The control of electroencephalographic alpha rhythms through auditory feedback and the associated mental activity. Psychophysiology. 1970; 6:476–484.

24. Sterman MB, Friar L. Suppression of seizures in an epileptic following sensorimotor EEG feedback training. Electroencephalogr Clin Neurophysiol. 1972; 33:89–95.

25. Prichep LS, John ER. QEEG profiles of psychiatric disorders. Brain Topogr. 1992; 4:249–257.

26. Thatcher RW, Walker RA, Biver CJ, North DN, Curtin R. Quantitative EEG normative databases: validation and clinical correlation. J Neurother. 2003; 7:87–121.

27. Thatcher RW, Lubar JF. History of the scientific standards of QEEG normative databases. In : Budzynski TH, Budzynski HK, Evans JR, Abarbanel A, editors. Introduction to quantitative EEG and neurofeedback: advanced theory and applications. London: Academic Press;2009. p. 29–59.

28. Dressler O, Schneider G, Stockmanns G, Kochs EF. Awareness and the EEG power spectrum: analysis of frequencies. Br J Anaesth. 2004; 93:806–809.

29. Loo SK, Cho A, Hale TS, McGough J, McCracken J, Smalley SL. Characterization of the theta to beta ratio in ADHD: identifying potential sources of heterogeneity. J Atten Disord. 2013; 17:384–392.

30. Kim JW, Lee J, Kim BN, Kang T, Min KJ, Han DH, et al. Theta-phase gamma-amplitude coupling as a neurophysiological marker of attention deficit/hyperactivity disorder in children. Neurosci Lett. 2015; 603:25–30.

31. Bo H, Qingyu T, Fusheng Y, Tian-Xiang C. ApEn and cross-ApEn: property, fast algorithm and preliminary application to the study of EEG and cognition. Signal Process. 1999; 15:100–108.

32. Harmon-Jones E, Allen JJ. Anger and frontal brain activity: EEG asymmetry consistent with approach motivation despite negative affective valence. J Pers Soc Psychol. 1998; 74:1310–1316.

33. Thatcher RW, North D, Biver C. EEG and intelligence: relations between EEG coherence, EEG phase delay and power. Clin Neurophysiol. 2005; 116:2129–2141.

34. Stam CJ, Nolte G, Daffertshofer A. Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources. Hum Brain Mapp. 2007; 28:1178–1193.

35. Chiang J, Wang ZJ, McKeown MJ. Sparse multivariate autoregressive (MAR)-based partial directed coherence (PDC) for electroencephalogram (EEG) analysis. In : IEEE Signal Processing Society. 2009 IEEE International Conference on Acoustics, Speech and Signal Processing; 2009 Apr 19–24; Taipei, Taiwan. IEEE;2009. p. 457–460.

36. Nikulin VV, Brismar T. Long-range temporal correlations in electroencephalographic oscillations: relation to topography, frequency band, age and gender. Neuroscience. 2005; 130:549–558.

37. Pijn JP, Van Neerven J, Noest A, Lopes da Silva FH. Chaos or noise in EEG signals; dependence on state and brain site. Electroencephalogr Clin Neurophysiol. 1991; 79:371–381.

38. Gasser T, Verleger R, Bächer P, Sroka L. Development of the EEG of school-age children and adolescents. I. Analysis of band power. Electroencephalogr Clin Neurophysiol. 1988; 69:91–99.

39. Steriade M, Dossi RC, Nuñez A. Network modulation of a slow intrinsic oscillation of cat thalamocortical neurons implicated in sleep delta waves: cortically induced synchronization and brainstem cholinergic suppression. J Neurosci. 1991; 11:3200–3217.

40. Amzica F, Nuñez A, Steriade M. Delta frequency (1–4 Hz) oscillations of perigeniculate thalamic neurons and their modulation by light. Neuroscience. 1992; 51:285–294.

41. Mormann F, Osterhage H, Andrzejak RG, Weber B, Fernández G, Fell J, et al. Independent delta/theta rhythms in the human hippocampus and entorhinal cortex. Front Hum Neurosci. 2008; 2:3.

42. Steriade M. Acetylcholine systems and rhythmic activities during the waking--sleep cycle. Prog Brain Res. 2004; 145:179–196.

43. Knyazev GG. EEG delta oscillations as a correlate of basic homeostatic and motivational processes. Neurosci Biobehav Rev. 2012; 36:677–695.

44. Sauseng P, Griesmayr B, Freunberger R, Klimesch W. Control mechanisms in working memory: a possible function of EEG theta oscillations. Neurosci Biobehav Rev. 2010; 34:1015–1022.

45. Schulman JJ, Cancro R, Lowe S, Lu F, Walton KD, Llinás RR. Imaging of thalamocortical dysrhythmia in neuropsychiatry. Front Hum Neurosci. 2011; 5:69.

46. Fuggetta G, Bennett MA, Duke PA, Young AM. Quantitative electroencephalography as a biomarker for proneness toward developing psychosis. Schizophr Res. 2014; 153:68–77.

47. Zobeiri M, Van Luijtelaar G, Budde T, Sysoev IV. The brain network in a model of thalamocortical dysrhythmia. Brain Connect. 2019; 9:273–284.

48. Leuchter AF, Cook IA, Jin Y, Phillips B. The relationship between brain oscillatory activity and therapeutic effectiveness of transcranial magnetic stimulation in the treatment of major depressive disorder. Front Hum Neurosci. 2013; 7:37.

49. Sukhodolsky DG, Leckman JF, Rothenberger A, Scahill L. The role of abnormal neural oscillations in the pathophysiology of co-occurring Tourette syndrome and attention-deficit/hyperactivity disorder. Eur Child Adolesc Psychiatry. 2007; 16:Suppl 1. 51–59.

50. Velikova S, Locatelli M, Insacco C, Smeraldi E, Comi G, Leocani L. Dysfunctional brain circuitry in obsessive-compulsive disorder: source and coherence analysis of EEG rhythms. Neuroimage. 2010; 49:977–983.

51. Markand ON. Alpha rhythms. J Clin Neurophysiol. 1990; 7:163–190.

52. Watkins JC, Evans RH. Excitatory amino acid transmitters. Annu Rev Pharmacol Toxicol. 1981; 21:165–204.

53. McCormick DA. GABA as an inhibitory neurotransmitter in human cerebral cortex. J Neurophysiol. 1989; 62:1018–1027.

54. Larson CL, Davidson RJ, Abercrombie HC, Ward RT, Schaefer SM, Jackson DC, et al. Relations between PET-derived measures of thalamic glucose metabolism and EEG alpha power. Psychophysiology. 1998; 35:162–169.

55. Laufs H, Kleinschmidt A, Beyerle A, Eger E, Salek-Haddadi A, Preibisch C, et al. EEG-correlated fMRI of human alpha activity. Neuroimage. 2003; 19:1463–1476.

56. Lozano-Soldevilla D, Ter Huurne N, Cools R, Jensen O. GABAergic modulation of visual gamma and alpha oscillations and its consequences for working memory performance. Curr Biol. 2014; 24:2878–2887.

57. Jensen O, Gelfand J, Kounios J, Lisman JE. Oscillations in the alpha band (9-12 Hz) increase with memory load during retention in a short-term memory task. Cereb Cortex. 2002; 12:877–882.

58. Jensen O, Mazaheri A. Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Front Hum Neurosci. 2010; 4:186.

59. Roopun AK, Middleton SJ, Cunningham MO, LeBeau FE, Bibbig A, Whittington MA, et al. A beta2-frequency (20-30 Hz) oscillation in nonsynaptic networks of somatosensory cortex. Proc Natl Acad Sci U S A. 2006; 103:15646–15650.

60. Nakamura S, Sadato N, Oohashi T, Nishina E, Fuwamoto Y, Yonekura Y. Analysis of music-brain interaction with simultaneous measurement of regional cerebral blood flow and electroencephalogram beta rhythm in human subjects. Neurosci Lett. 1999; 275:222–226.

61. Seo SH, Lee JT. Stress and EEG. In : Crisan M, editor. Convergence and Hybrid Information Technologies. Rijeka: IntechOpen;2010.

62. Knott V, Mahoney C, Kennedy S, Evans K. EEG power, frequency, asymmetry and coherence in male depression. Psychiatry Res. 2001; 106:123–140.

63. Loo SK, Arns M. Should the EEG–based theta to beta ratio be used to diagnose ADHD? The ADHD Report. 2015; 23:8–13.

64. Gloss D, Varma JK, Pringsheim T, Nuwer MR. Practice advisory: the utility of EEG theta/beta power ratio in ADHD diagnosis: report of the guideline development, dissemination, and implementation subcommittee of the American Academy of Neurology. Neurology. 2016; 87:2375–2379.

65. Norman RM, Malla AK, Williamson PC, Morrison-Stewart SL, Helmes E, Cortese L. EEG coherence and syndromes in schizophrenia. Br J Psychiatry. 1997; 170:411–415.

66. Tas C, Cebi M, Tan O, Hızlı-Sayar G, Tarhan N, Brown EC. EEG power, cordance and coherence differences between unipolar and bipolar depression. J Affect Disord. 2015; 172:184–190.

67. Locatelli T, Cursi M, Liberati D, Franceschi M, Comi G. EEG coherence in Alzheimer's disease. Electroencephalogr Clin Neurophysiol. 1998; 106:229–237.

68. Murias M, Webb SJ, Greenson J, Dawson G. Resting state cortical connectivity reflected in EEG coherence in individuals with autism. Biol Psychiatry. 2007; 62:270–273.

69. Guevara MA, Corsi-Cabrera M. EEG coherence or EEG correlation? Int J Psychophysiol. 1996; 23:145–153.

70. Alkire MT, Hudetz AG, Tononi G. Consciousness and anesthesia. Science. 2008; 322:876–880.

71. Bullock TH, McClune MC, Achimowicz JZ, Iragui-Madoz VJ, Duckrow RB, Spencer SS. Temporal fluctuations in coherence of brain waves. Proc Natl Acad Sci U S A. 1995; 92:11568–11572.

72. Kowalski JW, Gawel M, Pfeffer A, Barcikowska M. The diagnostic value of EEG in Alzheimer disease: correlation with the severity of mental impairment. J Clin Neurophysiol. 2001; 18:570–575.

73. Gawel M, Zalewska E, Szmidt-Sałkowska E, Kowalski J. The value of quantitative EEG in differential diagnosis of Alzheimer's disease and subcortical vascular dementia. J Neurol Sci. 2009; 283:127–133.

74. Clarke AR, Barry RJ, McCarthy R, Selikowitz M. EEG-defined subtypes of children with attention-deficit/hyperactivity disorder. Clin Neurophysiol. 2001; 112:2098–2105.

75. Schiller MJ. Quantitative electroencephalography in guiding treatment of major depression. Front Psychiatry. 2018; 9:779.

76. 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.

77. Hammond DC. QEEG-guided neurofeedback in the treatment of obsessive compulsive disorder. J Neurother. 2003; 7:25–52.

78. Hackett N. QEEG phenotypes, depression and TMS. Prog Neurol Psychiatry. 2018; 22:23–26.

79. Harwood HJ, Fountain D, Fountain G. Economic cost of alcohol and drug abuse in the United States, 1992: a report. Addiction. 1999; 94:631–635.

80. Alavi SS, Ferdosi M, Jannatifard F, Eslami M, Alaghemandan H, Setare M. Behavioral addiction versus substance addiction: correspondence of psychiatric and psychological views. Int J Prev Med. 2012; 3:290–294.

81. Blanco C, Moreyra P, Nunes EV, Saiz-Ruiz J, Ibanez A. Pathological gambling: addiction or compulsion? Semin Clin Neuropsychiatry. 2001; 6:167–176.

82. Volkow ND, Wang GJ, Fowler JS, Tomasi D, Telang F. Addiction: beyond dopamine reward circuitry. Proc Natl Acad Sci U S A. 2011; 108:15037–15042.

83. Haber SN. Convergence of limbic, cognitive, and motor cortico-striatal circuits with dopamine pathways in primate brain. In : Iversen LL, Iversen SD, Dunnet SB, Bjorklund A, editors. Dopamine Handbook. New York: Oxford University Press;2010. p. 38–48.

84. Smith KS, Mahler SV, Peciña S, Berridge KC. Hedonic hotspots: generating sensory pleasure in the brain. In : Kringelbach ML, Berridge KC, editors. Pleasures of the brain. Oxford: Oxford University Press;2010. p. 27–49.

85. Berridge KC, Robinson TE. What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience? Brain Res Brain Res Rev. 1998; 28:309–369.

86. Castro DC, Berridge KC. Opioid hedonic hotspot in nucleus accumbens shell: mu, delta, and kappa maps for enhancement of sweetness “liking” and “wanting”. J Neurosci. 2014; 34:4239–4250.

87. Blum K, Modestino EJ, Badgaiyan RD, Baron D, Thanos PK, Elman I, et al. Analysis of evidence for the combination of pro-dopamine regulator (KB220PAM) and naltrexone to prevent opioid use disorder relapse. EC Psychol Psychiatr. 2018; 7:564–579.

88. Comings DE, Blum K. Reward deficiency syndrome: genetic aspects of behavioral disorders. Prog Brain Res. 2000; 126:325–341.

89. Blum K, Braverman ER, Holder JM, Lubar JF, Monastra VJ, Miller D, et al. Reward deficiency syndrome: a biogenetic model for the diagnosis and treatment of impulsive, addictive, and compulsive behaviors. J Psychoactive Drugs. 2000; Suppl. i–iv. 1–112.

90. Blum K, Chen AL, Oscar-Berman M, Chen TJ, Lubar J, White N, et al. Generational association studies of dopaminergic genes in reward deficiency syndrome (RDS) subjects: selecting appropriate phenotypes for reward dependence behaviors. Int J Environ Res Public Health. 2011; 8:4425–4459.

91. 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.

92. Bardo MT, Donohew RL, Harrington NG. Psychobiology of novelty seeking and drug seeking behavior. Behav Brain Res. 1996; 77:23–43.

93. Prichep LS, Alper K, Kowalik SC, Rosenthal M. Neurometric QEEG studies of crack cocaine dependence and treatment outcome. J Addict Dis. 1996; 15:39–53.

94. Lee J, Yun K. Alcohol reduces cross-frequency theta-phase gamma-amplitude coupling in resting electroencephalography. Alcohol Clin Exp Res. 2014; 38:770–776.

95. Mumtaz W, Vuong PL, Malik AS, Rashid RBA. A review on EEG-based methods for screening and diagnosing alcohol use disorder. Cogn Neurodyn. 2018; 12:141–156.

96. Winterer G, Klöppel B, Heinz A, Ziller M, Dufeu P, Schmidt LG, et al. Quantitative EEG (QEEG) predicts relapse in patients with chronic alcoholism and points to a frontally pronounced cerebral disturbance. Psychiatry Res. 1998; 78:101–113.

97. Rangaswamy M, Porjesz B, Chorlian DB, Choi K, Jones KA, Wang K, et al. Theta power in the EEG of alcoholics. Alcohol Clin Exp Res. 2003; 27:607–615.

98. Rangaswamy M, Porjesz B, Chorlian DB, Wang K, Jones KA, Bauer LO, et al. Beta power in the EEG of alcoholics. Biol Psychiatry. 2002; 52:831–842.

99. Costa L, Bauer L. Quantitative electroencephalographic differences associated with alcohol, cocaine, heroin and dual-substance dependence. Drug Alcohol Depend. 1997; 46:87–93.

100. Enoch MA, White KV, Harris CR, Robin RW, Ross J, Rohrbaugh JW, et al. Association of low-voltage alpha EEG with a subtype of alcohol use disorders. Alcohol Clin Exp Res. 1999; 23:1312–1319.

101. Finn PR, Justus A. Reduced EEG alpha power in the male and female offspring of alcoholics. Alcohol Clin Exp Res. 1999; 23:256–262.

102. Lee J, Hwang JY, Park SM, Jung HY, Choi SW, Kim DJ, et al. Differential resting-state EEG patterns associated with comorbid depression in internet addiction. Prog Neuropsychopharmacol Biol Psychiatry. 2014; 50:21–26.

103. Son KL, Choi JS, Lee J, Park SM, Lim JA, Lee JY, et al. Neurophysiological features of internet gaming disorder and alcohol use disorder: a resting-state EEG study. Transl Psychiatry. 2015; 5:e628.

104. Kim YJ, Lee JY, Oh S, Park M, Jung HY, Sohn BK, et al. Associations between prospective symptom changes and slow-wave activity in patients with internet gaming disorder: a resting-state EEG study. Medicine (Baltimore). 2017; 96:e6178.

105. Choi JS, Park SM, Lee J, Hwang JY, Jung HY, Choi SW, et al. Resting-state beta and gamma activity in internet addiction. Int J Psychophysiol. 2013; 89:328–333.

106. Herremans SC, Baeken C. The current perspective of neuromodulation techniques in the treatment of alcohol addiction: a systematic review. Psychiatr Danub. 2012; 24:Suppl 1. S14–S20.

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