Evidence map›Paper›PMID 34091033›Full record

ArticleNeuroImage2021

The maturation and cognitive relevance of structural brain network organization from early infancy to childhood.

Mackenzie Woodburn, Cheyenne L Bricken, Zhengwang Wu, Gang Li, Li Wang, Weili Lin, Margaret A Sheridan, Jessica R Cohen

Open access · goldAbstract read
In one paragraph

Article in NeuroImage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 14% of its field
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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Pooled it
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  7. Longitudinal associations between birth-to-six cortical growth and childhood neurocognitive function.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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

8 authors at 2 institutions in 1 country.

Mackenzie WoodburnDepartment of Psychology & Neuroscience, University of North Carolina, Chapel Hill, United States. Electronic address: mawoodbu@live.unc.edu.
Cheyenne L BrickenDepartment of Psychology & Neuroscience, University of North Carolina, Chapel Hill, United States.
Zhengwang WuBiomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Department of Radiology, University of North Carolina, Chapel Hill, United States.
Gang LiBiomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Department of Radiology, University of North Carolina, Chapel Hill, United States.
Li WangBiomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Department of Radiology, University of North Carolina, Chapel Hill, United States.
Weili LinBiomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Department of Radiology, University of North Carolina, Chapel Hill, United States.
Margaret A SheridanDepartment of Psychology & Neuroscience, University of North Carolina, Chapel Hill, United States; Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Carolina Institute of Developmental Disabilities, University of North Carolina, Chapel Hill, United States.
Jessica R CohenDepartment of Psychology & Neuroscience, University of North Carolina, Chapel Hill, United States; Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, United States; Carolina Institute of Developmental Disabilities, University of North Carolina, Chapel Hill, United States.
University of North Carolina at Chapel Hill · USImaging Center · US

Funding

Continued Development of Infant Brain Analysis ToolsR01MH117943 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LI, GANG, WANG, LI · 2018 to 2022
$2.3M
Parcellating Infant Cerebral Cortex based on Developmental Patterns of Multimodal MRIR01MH116225 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LI, GANG · 2018 to 2022
$1.9M
Volume-based Analysis of 6-month Infant Brain MRI for Autism Biomarker Identification and Early DiagnosisK01MH109773 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WANG, LI · 2017 to 2020
$571k
Using growth models to identify how trajectories of infant brain development predict childhood behavior and neural functionR21HD096232 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SHERIDAN, MARGARET ANN · 2018 to 2019
$414k
NICHD NIH HHS R21 HD096232NIMH NIH HHS K01 MH109773NIMH NIH HHS R01 MH116225NIMH NIH HHS R01 MH117943
6 · The paper itself

Abstract

The interactions of brain regions with other regions at the network level likely provide the infrastructure necessary for cognitive processes to develop. Specifically, it has been theorized that in infancy brain networks become more modular, or segregated, to support early cognitive specialization, before integration across networks increases to support the emergence of higher-order cognition. The present study examined the maturation of structural covariance networks (SCNs) derived from longitudinal cortical thickness data collected between infancy and childhood (0-6 years). We assessed modularity as a measure of network segregation and global efficiency as a measure of network integration. At the group level, we observed trajectories of increasing modularity and decreasing global efficiency between early infancy and six years. We further examined subject-based maturational coupling networks (sbMCNs) in a subset of this cohort with cognitive outcome data at 8-10 years, which allowed us to relate the network organization of longitudinal cortical thickness maturation to cognitive outcomes in middle childhood. We found that lower global efficiency of sbMCNs throughout early development (across the first year) related to greater motor learning at 8-10 years. Together, these results provide novel evidence characterizing the maturation of brain network segregation and integration across the first six years of life, and suggest that specific trajectories of brain network maturation contribute to later cognitive outcomes.

Indexed as

Brain Cortical ThicknessBrainChildChild, PreschoolCognitionFemaleFollow-Up StudiesHumansImage Processing, Computer-AssistedInfantInfant, NewbornLearningMagnetic Resonance ImagingMaleMotor ActivityMotor CortexCognitionEarly brain developmentLongitudinal MRIMaturational couplingStructural covariance networks

Identifiers

PMID34091033
PMCPMC8372198
OpenAlexW3207816499

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.