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Updated: Aug 19, 2026
Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
Resting-state EEG microstate dynamics indicate altered brain network temporal organization in age-related hearing
Yurun Chen1, Qiaoyu Liu1, Yaohan Chen1
1Department of Otorhinolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Objective:
Age-related hearing loss (ARHL) is increasingly recognized as a condition that involves changes in the central nervous system beyond the auditory pathway, with growing evidence showing altered large-scale brain network connectivity. However, how ARHL reshapes the temporal organization of large-scale brain networks remains poorly understood. This study aimed to investigate whether ARHL is associated with alterations in resting-state electroencephalogram (EEG) microstate dynamics and to examine the relationship between microstate features and auditory function.
Methods:
Resting-state EEGs were recorded in 45 older adults with ARHL and 50 age-matched normal-hearing (NH) controls. Microstate analysis was performed using a seven-class model. Group differences in microstate parameters were assessed. Correlation analyses were conducted to examine associations between microstate metrics and audiological measures, including pure-tone audiometry (PTA) thresholds and speech-in-noise (SIN) perception.
Results:
Compared with NH controls, participants with ARHL exhibited reduced microstate G time coverage at the nominal significance level (uncorrected p < 0.05, FDR-adjusted q ≥ 0.05). In addition, the ARHL group showed significantly (FDR-adjusted q < 0.05) increased transition probabilities (TPs) from C to F and from F to C. Conversely, the TP from D to G was significantly reduced, whereas the TP from G to D showed a reduction at the nominal significance level. Across all participants, after controlling for age and sex, microstate G time coverage and TP from D to G were negatively correlated with PTA thresholds, whereas the TPs from C to F and from F to C were positively correlated with PTA thresholds. Furthermore, microstate G time coverage showed a nominal negative correlation with the SIN threshold.
Conclusion:
ARHL is associated with altered resting-state EEG microstate dynamics, mainly reflected by changes in TPs among sensorimotor and higher-order cognitive networks. Resting-state EEG microstate analysis provides a comprehensive and systematic framework for studying brain network temporal reorganization induced by auditory decline.
