Evidence map›Paper›PMID 26057595›Full record

ArticleNeuroImage2015

Developmental changes in spontaneous electrocortical activity and network organization from early to late childhood.

Vladimir Miskovic, Xinpei Ma, Chun-An Chou, Miaolin Fan, Max Owens, Hiroki Sayama, Brandon E Gibb

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NeuroImage, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
90citing papers in PubMed, 1 pooled it
–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

90 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  5. Article
  6. Review
  7. Contrastive Latent Functional Model.Statistics in biosciences · 2026
    Article
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  10. Developmental patterns of mother-child similarity in executive function and electroencephalogram coherence.Journal of family psychology : JFP : journal of the Division of Family Psychology of the American Psychological Association (Division 43) · 2026
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  19. Temporal autocorrelation is predictive of age-An extensive MEG time-series analysis.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  20. Article

30 more citing papers are in PubMed but not listed here.

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

7 authors.

Vladimir MiskovicCenter for Affective Science, State University of New York at Binghamton, USA; Department of Psychology, State University of New York at Binghamton, USA. Electronic address: miskovic@binghamton.edu.
Xinpei MaDepartment of Systems Science and Industrial Engineering, State University of New York at Binghamton, USA.
Chun-An ChouCenter for Affective Science, State University of New York at Binghamton, USA; Department of Systems Science and Industrial Engineering, State University of New York at Binghamton, USA.
Miaolin FanDepartment of Systems Science and Industrial Engineering, State University of New York at Binghamton, USA.
Max OwensCenter for Affective Science, State University of New York at Binghamton, USA; Department of Psychology, State University of New York at Binghamton, USA.
Hiroki SayamaCenter for Affective Science, State University of New York at Binghamton, USA; Department of Systems Science and Industrial Engineering, State University of New York at Binghamton, USA.
Brandon E GibbCenter for Affective Science, State University of New York at Binghamton, USA; Department of Psychology, State University of New York at Binghamton, USA.

Funding

Supplement to MH098060, “Children’s Attentional Biases: A Key Component of Negative Valence Systems.”R01MH098060 · NIMH · STATE UNIVERSITY OF NY,BINGHAMTON · PI GIBB, BRANDON E · 2012 to 2015
$3.1M
NIMH NIH HHS MH098060NIMH NIH HHS R01 MH098060
6 · The paper itself

Abstract

We investigated the development of spontaneous (resting state) cerebral electric fields and their network organization from early to late childhood in a large community sample of children. Critically, we examined electrocortical maturation across one-year windows rather than creating aggregate averages that can miss subtle maturational trends. We implemented several novel methodological approaches including a more fine grained examination of spectral features across multiple electrodes, the use of phase-lagged functional connectivity to control for the confounding effects of volume conduction and applying topological network analyses to weighted cortical adjacency matrices. Overall, there were major decreases in absolute EEG spectral density (particularly in the slow wave range) across cortical lobes as a function of age. Moreover, the peak of the alpha frequency increased with chronological age and there was a redistribution of relative spectral density toward the higher frequency ranges, consistent with much of the previous literature. There were age differences in long range functional brain connectivity, particularly in the alpha frequency band, culminating in the most dense and spatially variable networks in the oldest children. We discovered age-related reductions in characteristic path lengths, modularity and homogeneity of alpha-band cortical networks from early to late childhood. In summary, there is evidence of large scale reorganization in endogenous brain electric fields from early to late childhood, suggesting reduced signal amplitudes in the presence of more functionally integrated and band limited coordination of neuronal activity across the cerebral cortex.

Indexed as

Alpha RhythmBrain WavesCerebral CortexChildChild DevelopmentCross-Sectional StudiesElectroencephalographyFemaleHumansMaleNerve NetNeural Pathways

Identifiers

PMID26057595
PMCPMC4554821

What OpenQuestion holds

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Registered trials

None linked

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.