Evidence map›Paper›PMID 39789112›Full record

ArticleScientific reports2025

The level of cognitive functioning in school-aged children is predicted by resting EEG Directed Phase Lag Index.

Audrey-Rose Charlebois-Poirier, Saeideh Davoudi, Ève Lalancette, Inga Sophia Knoth, Sarah Lippé

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Behavioral Phenotype Associations With Resting State EEG Signal Complexity and Power Spectral Density in Fragile X Syndrome.Autism research : official journal of the International Society for Autism Research · 2026
    Article
4 · The record

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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

5 authors.

Audrey-Rose Charlebois-PoirierResearch Center of the Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada.
Saeideh DavoudiResearch Center of the Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada.
Ève LalancetteResearch Center of the Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada.
Inga Sophia KnothResearch Center of the Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada.
Sarah LippéResearch Center of the Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada. sarah.lippe@umontreal.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantifying cognitive potential relies on psychometric measures that do not directly reflect cortical activity. While the relationship between cognitive ability and resting state EEG signal dynamics has been extensively studied in children with below-average cognitive performances, there remains a paucity of research focusing on individuals with normal to above-average cognitive functioning. This study aimed to elucidate the resting EEG dynamics in children aged four to 12 years across normal to above-average cognitive potential. Our findings indicate that signal complexity, as measured by Multiscale Entropy (MSE), was not significantly predictive of the level of cognitive functioning. However, utilizing Directed Phase Lag Index (DPLI) as an effective connectivity measure, we observed consistent patterns of information flow between anterior and posterior regions. Fronto-parietal as well as local connectivity patterns were seen across most of the cognitive functions. Moreover, specific connectivity patterns were obtained for each intellectual quotient index (namely verbal comprehension, visuospatial, fluid reasoning, and processing speed indexes as well as full-scale intellectual quotient). These results underscore the presence of long-range connections and support fronto-parietal theories of cognitive abilities within the resting state brain dynamics of children.

Indexed as

CognitionElectroencephalographyBrainChildChild, PreschoolFemaleHumansMaleRestBrain developmentCognitive functioningDirected Phase Lag IndexElectroencephalographyMultiscale entropy

Identifiers

PMID39789112
PMCPMC11718128

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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.