Eye opening rapidly reshaped pediatric EEG microstates in a 110-child cohort
Resting EEG microstates in children changed in measurable ways when the eyes opened, and the pattern held across multiple analytic approaches. In a cohort of 110 participants from the Healthy Brain Network, paired eyes-closed and eyes-open recordings showed that eye opening shortened A and C microstate segments, increased the occurrence of all four K = 4 classes, and shifted coverage away from C toward B. The signal was not subtle. It was a broad-state reorganization that appeared within the same child, under the same resting condition, with only the visual state changing.
Shorter segments, more frequent switching, and a redistributed resting-state map
The most direct finding was temporal: eye opening reduced the duration of A and C segments. At the same time, the occurrence of every one of the four K = 4 microstate classes rose. Coverage also moved in a different direction, with class C giving up ground to class B. In practical terms, the resting EEG did not merely become noisier when the child opened their eyes; it reorganized into shorter-lived states that cycled more often.
This pattern fits the biology of wakeful sensory engagement. Even at rest, opening the eyes increases afferent visual input and changes large-scale cortical coordination. Microstates are brief topographic snapshots of coordinated brain activity, so a shift toward shorter segments and altered coverage is consistent with a brain that is processing more incoming information and switching between network configurations with greater speed.
The effect was not isolated to a single analytic definition. After participant-wise duration matching and template re-estimation, all eight significant K = 4 temporal effects kept the same direction. In other words, the eye-condition difference survived attempts to make the eyes-closed and eyes-open segments more comparable and to recalculate the microstate templates themselves.
Model order changed the apparent microstate story
The analysis did not stop at K = 4. Broad sensitivity to eye state also appeared at K = 6, where the architecture of the microstate maps shifted again. A stable fourth K = 4 map showed little correspondence with adult microstate D, while a D-like map emerged only at K = 6. That finding is clinically and methodologically important because it warns against assuming that pediatric microstate labels map neatly onto adult conventions.
In developmental EEG, the number of clusters chosen for analysis can change the interpretation of the resting brain. Here, the same child data yielded one picture at K = 4 and a different picture at K = 6. The brain state being measured is real; the way it is partitioned is also part of the result. Pediatric studies that ignore model order risk calling two different topographies by the same name.
ADHD, anxiety, and comparison groups showed similar response profiles
The cohort included a comparison group without the target diagnoses, an ADHD-only group, and an ADHD-plus-anxiety group. Change-score and baseline-adjusted analyses produced comparable eyes-closed to eyes-open response profiles across those groups. On the surface, that means the basic reorganization induced by eye opening was not confined to one diagnostic subgroup.
The absence of a strong group split is informative. It suggests that the visual-state effect may sit closer to a shared developmental physiology than to a diagnosis-specific biomarker, at least under the conditions tested here. For clinicians and researchers looking for a microstate signature of ADHD or anxiety during quiet rest, the eye condition itself may be an equally powerful source of variance. Ignoring whether the child’s eyes were open or closed would blur any attempt to separate developmental signal from diagnostic signal.
Alpha reactivity and switching did not behave uniformly across analytic choices
The association between posterior alpha reactivity and switching varied in both magnitude and direction depending on segmentation specification. That variability matters because it shows how closely microstate interpretation can depend on the exact analytic pipeline. Posterior alpha is commonly treated as a marker of visual disengagement or cortical idling, yet the relationship between alpha reactivity and microstate transitions here was not stable across every way of slicing the data.
This is a warning against overreading a single coefficient. If switching behavior tracks alpha differently depending on how templates are defined, then microstate transition metrics are not purely biological readouts; they are biological readouts filtered through analytic choices. The resting EEG in children is sensitive to state, but the measurement is also sensitive to definition.
Why this matters for pediatric EEG research
These findings push pediatric microstate work toward stricter reporting standards. Eye condition, model order, temporal smoothing, and analyzed duration all altered the picture enough to merit explicit specification in developmental and clinical studies. Without those details, two papers can appear to disagree when they are actually measuring different versions of the same signal.
For translational EEG research, the implication is straightforward. A child’s resting-state microstate profile cannot be interpreted in isolation from the recording condition. Eye opening changes the sensory context, the temporal footprint of the microstates, and the apparent balance between classes. A stable biomarker will need to survive all of that, not just one carefully chosen analysis.
The study’s funding came from the Zhejiang Provincial Health Commission Science and Technology Program Project, and the data came from the Healthy Brain Network biobank. The work was performed on de-identified public data under existing governance approvals, with no competing interests declared. Its most durable message is methodological as much as physiological: pediatric EEG microstates are real, but their meaning depends on how, and under what eye condition, they are measured.