ArticleFrontiers in psychiatry2022
Altered resting-state electroencephalography microstate characteristics in young male smokers.
Article in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 10 citations in OpenAlex.
- EEG Microstate Correlates of Emotional Processing in Patients with Alcohol use Disorder and Healthy Controls: An Exploratory Resting-EEG Study.Brain topography · 2026Article
- Signs of Problematic Internet use Affect Resting-State EEG Microstates.Brain topography · 2025Article
- The Phase-Amplitude Coupling Changes Induced by Smoking Cue After 12-H Abstinence in Young Smokers.Addiction biology · 2025Article
- Article
- Hypnosis efficacy on nicotine addiction: An analysis of EEG microstates and brain oscillation entropy.AIMS neuroscience · 2025Article
- Abnormal power and spindle wave activity during sleep in young smokers.Frontiers in neuroscience · 2025Article
- Brain temporal dynamics correlate with clinical traits, spontaneous arm movements, and recovery in middle cerebral artery stroke.Frontiers in human neuroscience · 2025Article
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of nicotine addiction was associated with the abnormalities of intrinsic functional networks during the resting state in young adult smokers. As a whole-brain imaging approach, EEG microstate analysis treated multichannel EEG recordings as a series of quasi-steady microscopic states which were related to the resting-state networks (RSNs) found by fMRI. The aim of this study was to examine whether the resting-state EEG microstate analysis may provide novel insights into the abnormal temporal properties of intrinsic brain activities in young smokers. We used 64-channel resting-state EEG datasets to investigate alterations in microstate characteristics between twenty-five young smokers and 25 age- and gender-matched non-smoking controls. Four classic EEG microstates (microstate A, B, C, and D) were obtained, and the four temporal parameters of each microstate were extracted, i.e., duration, occurrence, coverage, and transition probabilities. Compared with non-smoking controls, young smokers showed decreased occurrence of microstate C and increased duration of microstate D. Furthermore, both the duration and coverage of microstate D were significantly negatively correlated with Fagerstrom Test of Nicotine Dependence (FTND) in young smoker group. The complex changes in the microstate time-domain parameters might correspond to the abnormalities of RSNs in analyses of FC measured with fMRI in the previous studies and indicate the altered specific brain functions in young smokers. Microstate D could be potentially represented as a selective biomarker for predicting the dependence degree of adolescent smokers on cigarettes. These results suggested that EEG microstate analysis might detect the deviant functions of large-scale cortical activities in young smokers and provide a new perspective for the study of brain networks of adolescent smokers.
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