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Critical states in sleep EEG: developmental evolution across 3192 clinical children aged 0-18 years

Huimin Sun1, Wang Wan1, Xingran Cui1,2

  • 1Key Laboratory of Child Development and Learning Science, Ministry of Education, School of Biological Science and Medical Engineering, Southeast University, No. 2 Southeast University Road, Jiangning District, Nanjing, Jiangsu Province 211189, China.

Sleep
|October 13, 2025
PubMed

Insights

As children age, their sleep brain activity evolves towards network criticality. This developmental shift in sleep EEG dynamics indicates brain maturation and improved adaptability.

Area of Science:

  • Neuroscience
  • Developmental Biology
  • Sleep Science

Background:

  • Sleep is vital for brain function, restoring optimal information processing capacity.
  • Understanding how sleep's restorative capabilities develop with age is crucial.
  • Neural criticality, a state of optimal information processing, is theorized to be restored by sleep.

Purpose of the Study:

  • To analyze sleep electroencephalogram (EEG) dynamics in children aged 0-18 years.
  • To investigate the developmental trajectory of brain system criticality during sleep.
  • To examine long-range temporal correlations in sleep EEG to understand brain maturation.

Main Methods:

  • Screened sleep EEG data from 3192 children (0-18 years) from the Nationwide Children's Hospital Sleep Databank.
  • Analyzed developmental evolution of long-range temporal correlation in sleep stages (wake, N1, N2, N3, REM).
  • Utilized detrended fluctuation analysis (DFA) to quantify EEG dynamics.

Main Results:

  • In N3 sleep, the DFA exponent remained stable (~1.5) across all ages, indicating regular activity far from criticality.
  • In light sleep (N1/N2) and REM sleep, the DFA exponent decreased from ~1.5 in neonates to ~1.0 in late adolescence.
  • This progressive decrease signifies the emergence of scale-free, network-critical dynamics with age.

Conclusions:

  • Provides population-scale evidence linking sleep architecture to the developmental emergence of neural criticality.
  • Stage-specific sleep EEG trajectories correlate with synaptic pruning and network refinement during cortical maturation.
  • Sleep dynamics during development may serve as a biomarker for cortical maturation and brain adaptability.
Abstract

Keywords:
EEG analysischild/childrencritical statesdetrended fluctuation analysisdevelopmentsleep and the brain

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