Evidence map›Paper›PMID 41082537›Full record

ArticlePloS one2025

EEG difference in the Higuchi fractal dimension of wakefulness and sleep from birth to adolescence.

Francesco Colussi, Jacopo Favaro, Claudio Ancona, Edoardo Passarotto, Maria Federica Pelizza, Eleonora Lorenzon, Simone Ruzzante, Stefano Masiero, Giorgio Perilongo, Giovanni Sparacino and 3 more

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Francesco ColussiDepartment of Information Engineering, University of Padova, Padova, Italy.ORCID https://orcid.org/0009-0007-4801-5796
Jacopo FavaroWomen's and Children's Health Department, University of Padova, Padova, Italy.ORCID https://orcid.org/0000-0002-4340-2398
Claudio AnconaWomen's and Children's Health Department, University of Padova, Padova, Italy.ORCID https://orcid.org/0009-0000-5721-5270
Edoardo PassarottoDepartment of Neuroscience, University of Padova, Padova, Italy.
Maria Federica PelizzaWomen's and Children's Health Department, University of Padova, Padova, Italy.
Eleonora LorenzonWomen's and Children's Health Department, University of Padova, Padova, Italy.
Simone RuzzanteWomen's and Children's Health Department, University of Padova, Padova, Italy.
Stefano MasieroDepartment of Neuroscience, University of Padova, Padova, Italy.
Giorgio PerilongoWomen's and Children's Health Department, University of Padova, Padova, Italy.
Giovanni SparacinoDepartment of Information Engineering, University of Padova, Padova, Italy.ORCID https://orcid.org/0000-0002-3248-1393
Irene ToldoWomen's and Children's Health Department, University of Padova, Padova, Italy.
Stefano SartoriWomen's and Children's Health Department, University of Padova, Padova, Italy.
Maria RubegaDepartment of Neuroscience, University of Padova, Padova, Italy.ORCID https://orcid.org/0000-0002-0744-3109

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

BrainElectroencephalographyFractalsSleepWakefulnessAdolescentAlgorithmsChildChild, PreschoolFemaleHumansInfantInfant, NewbornMale

Identifiers

PMID41082537
PMCPMC12517535

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.