Periodic and aperiodic neural activity displays age-dependent changes across early-to-middle childhood

By A. Hill, Gillian M. Clark, F. Bigelow, J. Lum, Peter Enticott. 2021

Subfields: Cognitive Neuroscience, Developmental Neuroscience

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Ángela Hoyo
2. Josué Rico-Picó
3. N. Langer
4. M. R. Rueda
5. D. Melcher
6. Julie Sato
7. J. Trajković
8. Marius Tröndle

In Developmental Neuroscience

1. C. Wilkinson

Citations in the corpus

• Scale-Free Neurodynamics as Functional Fingerprint of Brain Regions (2026, unknown): “Voytek et al. [17] further demonstrated that age-related changes in the spectral slope reflect meaningful alterations in cortical circuitry, while distinct developmental changes in aperiodic dynamics during infancy have also been reported [18,19].”
• The development of aperiodic neural activity in the human brain (2024, unknown): “Based on reports of age-related variability in global scalp EEG-derived aperiodic activity 5,6,32,57,58 and in brain structure demonstrating that sensorimotor regions mature earlier than association regions 2,3,59,60 , we hypothesized the following: (a) in association cortices, the aperiodic slope…”
• Brain Activity of Young Children in Bangladesh Is Associated With Biopsychosocial Conditions at the Individual‐, Family‐, and Household‐Level (2026, unknown): “Research has shown that, as typically developing children age, EEG activity increases in the alpha and beta power bands and decreases in the delta and theta power bands (Cellier et al. 2021; Hill et al. 2022; Matousek and Petersen 1973).”
• Characterization of aperiodic and theta activity in preterm infants using EEG: Insights into cerebral maturation and inter-individual variability (2026, unknown): “Aperiodic exponent decreases from childhood into adolescence/adulthood (Favaro et al., 2023; Hill et al., 2022), but findings in infancy are scarce and indicate a less clear picture, as noted in the systematic review of Stanyard et al., (2024).”
• Non-Neural Sources Systematically Impact Aperiodic EEG Activity (2026, unknown): “Furthermore, this range was commonly used in subsequent studies examining the relationship between aperiodic activity and age 12 – 14,50, Across all analytic subsamples, the specparam algorithm achieved consistently high model fits across (R² = 0.96-0.99), regardless of differences in EEG data…”
• Resting-state periodic and aperiodic brain oscillations from birth to preschool years: Aperiodic maturity predicts developmental course (2026, unknown): “…measures have been obtained from power spectra via an average of EEG channels (Karalunas, 2022; Tr ¨ ondle, 2022) or via two or more regional clusters of EEG sensors (Cellier, 2021; Carter Leno, 2021; Schawor-onkow and Voytek, 2021; Favaro, 2023; Hill, 2022; Tr ¨ ondle, 2022; Rico-Pic ´ o, 2023).”
• Aperiodic parameters of the fMRI power spectrum associate with preterm birth and neonatal age (2026, unknown): “The parameters change as a function of age, with the exponent decreasing in infants 28 , and both exponent and offset decreasing during the early-childhood 29,30 and early-adulthood 31 .”
• Resting state aperiodic and periodic EEG activity in preschool-aged autistic children: differences from neurotypical peers and links to language skills (2026, unknown): “Although increased aperiodic offset during the first year of life may be related to increases in gray matter volume, neuronal density, and synaptic number [51], aperiodic offset typically stabilizes after 1 year of age and then later decreases with age [51, 58, 59].”
• Developmental relationships between the human alpha rhythm and intrinsic neural timescales are dependent on neural hierarchy (2025, unknown): “The peak alpha rhythm frequency (PAF), for example, increases from approximately 6 to 8 Hz in infancy and early childhood (2–4) to 8 to 12 Hz in later childhood and adolescence (5–13).”
• Neuronal oscillatory imbalances in GNAO1‐related disorders associated with disease severity (2025, unknown): “20 We used the FOOOF algorithm 21 to extract the aperiodic exponent within the frequency range of 1 to 45 Hz.”
• Heterochronous laminar maturation in the human prefrontal cortex (2025, unknown): “Replicating prior findings 60,63,64 , the aperiodic exponent significantly declined with age across the frontal cortex (indicative of a flattening of the aperiodic slope; F = 16.7; p < 0.001; Fig.”