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Yet, how distinct facets of this variability evolve from childhood to older adulthood remains poorly understood, limiting mechanistic models of neurocognitive aging. Here, we characterize lifespan neural variability using an integrated empirical-computational approach. We analyzed high-density EEG cohort data spanning 111 healthy individuals aged 9\u201375 years, recorded at rest and during a passive and an attended auditory oddball stimulation task. We extracted scale-dependent measures of EEG fluctuation amplitude and entropy, together with millisecond-resolved phase-synchrony networks in the 2\u201320 Hz range. Multi-condition partial least squares decomposition analysis revealed two independent lifespan trajectories. First, slow-frequency power, variance,\u00a0and complexity at longer timescales declined monotonically with age, indicating a progressive dampening of low-frequency fluctuations and large-scale coherence. Second, the temporal organization of phase-synchrony reconfigurations followed an inverted U-shaped trend: young adults exhibited the slowest yet most diverse switching\u2014characterized by low mean but high variance and low kurtosis of jump lengths at 2\u20136 Hz,\u00a0and the opposite pattern at 8\u201320 Hz\u2014whereas children and older adults showed faster, more stereotyped dynamics. To mechanistically account for these patterns, we fitted a ten-node phase-oscillator model constrained by the human structural connectome. Only an intermediate, metastable coupling regime qualitatively\u00a0reproduced the empirical finding of maximally heterogeneous synchrony dynamics observed in young adults, whereas deviations toward weaker or stronger coupling mimicked the children\u2019s and older adults\u2019 profiles. Our results demonstrate that development and aging entail changes in the switching dynamics of EEG phase synchronization by differentially sculpting stationary and transient aspects of neural variability. This establishes time-resolved phase-synchrony metrics as sensitive, mechanistically grounded markers of neurocognitive status across the lifespan.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1013290","type":"journal-article","created":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T17:45:14Z","timestamp":1776361514000},"page":"e1013290","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Developmental and aging changes in brain network switching dynamics revealed by EEG phase synchronization"],"prefix":"10.1371","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0103-7094","authenticated-orcid":true,"given":"Dionysios","family":"Perdikis","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3508-3403","authenticated-orcid":true,"given":"Rita","family":"Sleimen-Malkoun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Viktor","family":"M\u00fcller","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Viktor","family":"Jirsa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2026,4,16]]},"reference":[{"issue":"1","key":"pcbi.1013290.ref001","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1038\/s41386-024-01946-8","article-title":"Revisiting the role of computational neuroimaging in the era of integrative neuroscience","volume":"50","author":"AM Loosen","year":"2024","journal-title":"Neuropsychopharmacology"},{"key":"pcbi.1013290.ref002","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.conb.2018.01.009","article-title":"Challenges and opportunities for large-scale electrophysiology with Neuropixels probes","volume":"50","author":"NA Steinmetz","year":"2018","journal-title":"Curr Opin Neurobiol"},{"issue":"4","key":"pcbi.1013290.ref003","doi-asserted-by":"crossref","first-page":"891","DOI":"10.1038\/s41593-025-01907-4","volume":"28","author":"L Sun","year":"2025","journal-title":"Nature Neuroscience"},{"issue":"10","key":"pcbi.1013290.ref004","doi-asserted-by":"crossref","first-page":"2974","DOI":"10.1073\/pnas.70.10.2974","article-title":"A theory of the epigenesis of neuronal networks by selective stabilization of synapses","volume":"70","author":"JP Changeux","year":"1973","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"24","key":"pcbi.1013290.ref005","doi-asserted-by":"crossref","first-page":"13763","DOI":"10.1073\/pnas.231499798","article-title":"Degeneracy and complexity in biological systems","volume":"98","author":"GM Edelman","year":"2001","journal-title":"Proc Natl Acad Sci U S A"},{"key":"pcbi.1013290.ref006","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/978-3-540-71512-2_1","article-title":"Neuronal Dynamics and Brain Connectivity","author":"M Breakspear","year":"2007","journal-title":"Understanding Complex Systems. 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