ArticlePloS one2025
EEG difference in the Higuchi fractal dimension of wakefulness and sleep from birth to adolescence.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Topographic Reorganization of EEG Complexity During Visual Mental Imagery: Insights from Lempel-Ziv Complexity in High-Density EEG.Brain topography · 2026Article
- Normative Modeling of EEG Complexity Reveals Cortical Rigidity Associated with Pain Severity in Chronic Pain.Journal of pain research · 2026Article
- Complexity of fractal dimension patterns and machine learning-based classification of altered motor cortical oscillatory activity in rodent models of Parkinson disease.Frontiers in neurologyArticle
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13 authors.
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Abstract
Brain maturation from birth to adolescence involves profound transformations in neural dynamics, which can be studied in a minimally invasive manner using quantitative EEG. Most of the results published in the literature are based on spectral analysis approaches, which are extremely effective in detecting and assessing EEG rhythms. However, some aspects of EEG dynamics can only be investigated using nonlinear approaches, the use of which is still relatively unexplored in the pediatric population. The aim of the present paper is to assess the EEG differentiation of wakefulness from deep sleep (quiet sleep in neonates, stage N3 in older children) and its maturation across a wide developmental window (0-17 years) using the fractal dimension. Specifically, Higuchi fractal dimension (HFD) algorithm is used to analyse both wakefulness and sleep EEG recordings collected from 63 infants (aged 0-1 year) and 160 children (aged 2-17 years). To ensure methodological consistency, a data-driven criterion for the selection of HFD user parameters is implemented to enhance reproducibility. Our results show that HFD during wakefulness increases during the first year of life, followed by a stabilization or slight decrease in later years. In contrast, HFD during sleep exhibits a more stable profile, with only a mild increase over development. These findings are consistent with known neurodevelopmental processes-including synaptogenesis, pruning, and white matter maturation-and support the interpretation of HFD as a sensitive marker of large-scale integrative brain dynamics. These physiological trajectories of HFD both in wakefulness and sleep could be used as reference for future clinical applications in pediatric neurology and developmental monitoring.
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