Resting-state EEG microstate analysis of internet gaming disorder and alcohol use disorder
- Authors
- Kim, Ji Sun; Song, Young Wook; Kim, Sungkean; Lee, Ji-Yoon; Yoo, So Young; Jang, Joon Hwan; Choi, Jung-Seok
- Issue Date
- Dec-2024
- Publisher
- Les Laboratoires Servier
- Keywords
- Electroencephalography; microstate analysis; internet gaming disorder; alcohol use disorder; microstate features
- Citation
- Dialogues in Clinical Neuroscience, v.26, no.1, pp 89 - 102
- Pages
- 14
- Indexed
- SCIE
SCOPUS
- Journal Title
- Dialogues in Clinical Neuroscience
- Volume
- 26
- Number
- 1
- Start Page
- 89
- End Page
- 102
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/121245
- DOI
- 10.1080/19585969.2024.2432913
- ISSN
- 1294-8322
1958-5969
- Abstract
- IntroductionTo investigate the neurophysiological aspects of addiction, the microstate characteristics of internet gaming disorder (IGD), alcohol use disorder (AUD), and healthy control (HC) groups were compared using resting-state electroencephalography (EEG).MethodsIn total, 199 young adults (75 patients with IGD, 57 patients with AUD, and 67 HCs) participated in this study. We conducted EEG microstate analysis among the groups and also compared the obtained parameters with the results of psychological assessments.ResultsThe global explained variance, occurrence, and coverage of microstate C were significantly lower in the AUD group than in the IGD group. Additionally, rates of transition from microstates A, B, and D to C were significantly lower in the AUD group than in the IGD group, whereas rates of transition from microstate A to B were lower in the IGD group compared to HCs. Furthermore, the occurrence of microstate C and transition from microstate B to C were negatively correlated with the Alcohol Use Disorder Identification and Behavioural Inhibition Scale score.ConclusionThere were significant differences in microstate characteristics among the groups, which correlated with the psychological scores. These findings suggest that microstate features can be used as neuromarkers in clinical settings to differentiate between addictive disorders and evaluate the pathophysiology of AUD and IGD.
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