Jaewon Lee1, Jae Yeon Hwang2, Su Mi Park3, Hee Yeon Jung4, Sam-Wook Choi1, Dai Jin Kim5, Jun-Young Lee4, Jung-Seok Choi6. 1. Department of Psychiatry, Gangnam Eulji Hospital, Eulji University, Seoul, Republic of Korea. 2. Department of Psychiatry, Kangdong Sacred Heart Hospital, Seoul, Republic of Korea. 3. Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea. 4. Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea; Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea. 5. Department of Psychiatry, Seoul St. Mary's Hospital, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea. 6. Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea; Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea. Electronic address: choijs73@gmail.com.
Abstract
OBJECTIVE: Many researchers have reported a relationship between Internet addiction and depression. In the present study, we compared the resting-state quantitative electroencephalography (QEEG) activity of treatment-seeking patients with comorbid Internet addiction and depression with those of treatment-seeking patients with Internet addiction without depression, and healthy controls to investigate the neurobiological markers that differentiate pure Internet addiction from Internet addiction with comorbid depression. METHOD: Thirty-five patients diagnosed with Internet addiction and 34 age-, sex-, and IQ-matched healthy controls were enrolled in this study. Patients with Internet addiction were divided into two groups according to the presence (N=18) or absence (N=17) of depression. Resting-state, eye-closed QEEG was recorded, and the absolute and relative power of the brain were analyzed. RESULTS: The Internet addiction group without depression had decreased absolute delta and beta powers in all brain regions, whereas the Internet addiction group with depression had increased relative theta and decreased relative alpha power in all regions. These neurophysiological changes were not related to clinical variables. CONCLUSION: The current findings reflect differential resting-state QEEG patterns between both groups of participants with Internet addiction and healthy controls and also suggest that decreased absolute delta and beta powers are neurobiological markers of Internet addiction.
OBJECTIVE: Many researchers have reported a relationship between Internet addiction and depression. In the present study, we compared the resting-state quantitative electroencephalography (QEEG) activity of treatment-seeking patients with comorbid Internet addiction and depression with those of treatment-seeking patients with Internet addiction without depression, and healthy controls to investigate the neurobiological markers that differentiate pure Internet addiction from Internet addiction with comorbid depression. METHOD: Thirty-five patients diagnosed with Internet addiction and 34 age-, sex-, and IQ-matched healthy controls were enrolled in this study. Patients with Internet addiction were divided into two groups according to the presence (N=18) or absence (N=17) of depression. Resting-state, eye-closed QEEG was recorded, and the absolute and relative power of the brain were analyzed. RESULTS: The Internet addiction group without depression had decreased absolute delta and beta powers in all brain regions, whereas the Internet addiction group with depression had increased relative theta and decreased relative alpha power in all regions. These neurophysiological changes were not related to clinical variables. CONCLUSION: The current findings reflect differential resting-state QEEG patterns between both groups of participants with Internet addiction and healthy controls and also suggest that decreased absolute delta and beta powers are neurobiological markers of Internet addiction.
Authors: Jacquelyn L Meyers; Jian Zhang; Niklas Manz; Madhavi Rangaswamy; Chella Kamarajan; Leah Wetherill; David B Chorlian; Sun J Kang; Lance Bauer; Victor Hesselbrock; John Kramer; Samuel Kuperman; John I Nurnberger; Jay Tischfield; Jen Chyong Wang; Howard J Edenberg; Alison Goate; Tatiana Foroud; Bernice Porjesz Journal: Int J Psychophysiol Date: 2016-12-28 Impact factor: 2.997
Authors: J L Meyers; J Zhang; J C Wang; J Su; S I Kuo; M Kapoor; L Wetherill; S Bertelsen; D Lai; J E Salvatore; C Kamarajan; D Chorlian; A Agrawal; L Almasy; L Bauer; K K Bucholz; G Chan; V Hesselbrock; L Koganti; J Kramer; S Kuperman; N Manz; A Pandey; M Seay; D Scott; R E Taylor; D M Dick; H J Edenberg; A Goate; T Foroud; B Porjesz Journal: Mol Psychiatry Date: 2017-01-10 Impact factor: 15.992
Authors: K-L Son; J-S Choi; J Lee; S M Park; J-A Lim; J Y Lee; S N Kim; S Oh; D J Kim; J S Kwon Journal: Transl Psychiatry Date: 2015-09-01 Impact factor: 6.222