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Updated: May 24, 2025

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
Using EEG microstates to examine whole-brain neuronal networks during offline rest consolidation after visual
Di Wu1, Na Liu2, Yifan Wang1
1Department of Medical Psychology, Air Force Medical University, Xi'an, China.
Abstract:
Visual perceptual learning (VPL) leads to improvements in visual skills after practice or training in visual perceptual tasks. Evidence suggests that newly formed skills are preferentially consolidated by the brain during offline task-free periods. Additionally, VPL can lead to changes in brain areas associated with higher cognitive functions. Thus, training may result in changes in whole-brain networks during the offline consolidation period. To test this inference, electroencephalography (EEG) microstates were used to explore the dynamic characteristics of the whole-brain network during consolidation periods after training. Forty-five healthy young adults were randomly divided into three groups for training with moderate, easy and difficult intensity. The participants were trained on a coherent motion discrimination task, and the coherence threshold and resting EEG were measured before and after training. The results showed that visual performance improved only in the moderate training group and not in the easy or difficult training groups. Microstate analyses revealed significant decreases in the duration and occurrence rate of microstate C (often associated with the default mode network) during offline consolidation following moderate training. Moreover, the duration of microstate D (often associated with the dorsal attention network) significantly increased. However, moderate training did not change the duration or occurrence rate of microstate B (often associated with the visual network). This study revealed the activity of whole-brain networks in the consolidation period after VPL.
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