Spontaneous brain microstates correlate with impaired inhibitory control in internet addiction disorder

Yawei Qi; Yuting Liu; Ziyou Yan; Xinhe Zhang; Qinghua He

doi:10.1016/j.pscychresns.2023.111686

Spontaneous brain microstates correlate with impaired inhibitory control in internet addiction disorder

Psychiatry Res Neuroimaging. 2023 Sep:334:111686. doi: 10.1016/j.pscychresns.2023.111686. Epub 2023 Jul 19.

Authors

Yawei Qi¹, Yuting Liu², Ziyou Yan¹, Xinhe Zhang³, Qinghua He⁴

Affiliations

¹ Faculty of Psychology, MOE Key Laboratory of Cognition and Personality, Southwest University, Chongqing, China.
² Faculty of Psychology, MOE Key Laboratory of Cognition and Personality, Southwest University, Chongqing, China; Xiangcheng Dajiang Middle School, Chengdu, China.
³ Faculty of Psychology, MOE Key Laboratory of Cognition and Personality, Southwest University, Chongqing, China. Electronic address: zhangxinhe@swu.edu.cn.
⁴ Faculty of Psychology, MOE Key Laboratory of Cognition and Personality, Southwest University, Chongqing, China; Southwest University Branch, Collaborative Innovation Center of Assessment toward Basic Education Quality, Chongqing, China. Electronic address: heqinghua@swu.edu.cn.

PMID: 37487311
DOI: 10.1016/j.pscychresns.2023.111686

Abstract

The prevalence of the Internet addiction disorder (IAD) has been on the rise, making it increasingly imperative to explore the neurophysiological markers of it. Using the whole-brain imaging approach of EEG microstate analysis, which treats multichannel EEG recordings as a series of quasi-steady states, similar as the resting-state networks found by fMRI, the present study aimed to investigate the specificity of the IAD in class C of the four canonical microstates. The existing EEG data of 40 participants (N = 20 for each group) was used, and correlation between the time parameters of microstate C and the performance of the Go/NoGo task was analyzed. Results suggested that the duration and coverage of class C were significantly reduced in the IAD group as compared to the healthy control (HC) group. Furthermore, the duration of class C had a significant inverse correlation with Go RTs in the IAD group. These results implied that class C might serve as a neurophysiological marker of IAD, helping to understand the underlying neural mechanism of inhibitory control in IAD.

Keywords: Electroencephalogram (EEG); Inhibitory control; Internet addiction disorders (IAD); Microstate analysis; Resting-state.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Brain / diagnostic imaging
Brain / physiology
Brain Mapping
Electroencephalography*
Humans
Internet Addiction Disorder*
Magnetic Resonance Imaging