ArticleCerebral cortex (New York, N.Y. : 1991)2025
The fractal dimension of resting state EEG increases over age in children.
Article in Cerebral cortex (New York, N.Y. : 1991), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Neural integrator and orchestrator communities shape spontaneous signaling in the human brain.PNAS nexus · 2026Article
- Developmental and aging changes in brain network switching dynamics revealed by EEG phase synchronization.PLoS computational biology · 2026Article
- Neural integrator and orchestrator communities shape spontaneous signaling in the human brain.bioRxiv : the preprint server for biology · 2026Article
- Normative Modeling of EEG Complexity Reveals Cortical Rigidity Associated with Pain Severity in Chronic Pain.Journal of pain research · 2026Article
- Neural transmission in the wired brain, new insights into an encoding-decoding-based neuronal communication model.Translational psychiatry · 2025Article
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Abstract
Resting-state electroencephalography (rs-EEG) represents spontaneous neural activity and is increasingly analyzed using nonlinear measures to assess brain complexity. The Higuchi Fractal Dimension (HFD) is a widely used metric for quantifying the fractal properties of EEG signals, yet its developmental trajectory remains largely unexplored. In this study, we examined age-related changes in HFD across childhood, adolescence, and early adulthood. We analyzed eyes-closed rs-EEG from 128 channels in 83 neurotypical participants (8 to 30 yr) from the MIPDB database. To assess developmental patterns, we applied a Gaussian Linear Mixed Model with age, electrode location, and their interaction as predictors, alongside non-parametric cluster-based permutation analysis to evaluate topographical differences. We observed a significant increase in HFD with age (P = 0.001), most pronounced between childhood and adolescence, followed by stabilization in early adulthood. HFD also varied across electrode locations, with higher values in frontal, central, and temporal regions and lower values in parietal and occipital areas. These findings provide new insights into the maturation of neural complexity in rs-EEG, aligning with known structural and functional changes in brain development. This study contributes to the growing body of research on nonlinear EEG dynamics and their relevance to neurodevelopment.
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