Evidence map›Paper›PMID 41571660›Full record

ArticleNature communications2026

Hierarchical maturation of structural brain connectomes from birth to childhood.

Tengda Zhao, Minhui Ouyang, Xiao-Jing Shou, Shanbin Zhang, Jiatong Ju, Xuhong Liao, Meizhen Han, Lianglong Sun, Xiaoyue Wang, Yunman Xia and 11 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
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

21 authors.

Tengda Zhao *State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.ORCID 0000-0002-5160-8417
Minhui Ouyang *Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.ORCID 0000-0001-8013-2553
Xiao-Jing Shou *State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Shanbin ZhangState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Jiatong JuState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Xuhong LiaoSchool of Systems Science, Beijing Normal University, Beijing, China.ORCID 0009-0000-0170-2520
Meizhen HanState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Lianglong SunState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.ORCID 0009-0007-0164-0893
Xiaoyue WangSchool of Medical Technology, Beijing Institute of Technology, Beijing, China.
Yunman XiaState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.ORCID 0000-0003-2593-9252
Di HuDepartment of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Huiying KangDepartment of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Jianlin GuoDepartment of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Qian WangState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Maolin LiState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Ran HuoDepartment of Radiology, Peking University Third Hospital, Beijing, China.
Ying LiuDepartment of Radiology, Peking University Third Hospital, Beijing, China.
Huishu YuanDepartment of Radiology, Peking University Third Hospital, Beijing, China.
Yun PengDepartment of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China. ppengyun@hotmail.com.
Hao HuangDepartment of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA. huangh6@chop.edu.ORCID 0000-0002-9103-4382
Yong HeState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China. yong.he@bnu.edu.cn.ORCID 0000-0002-7039-2850

Funding

The Intellectual and Developmental Disabilities Research Center (IDDRC) at CHOP/PennP50HD105354 · NICHD · CHILDREN'S HOSP OF PHILADELPHIA · PI ERIC D MARSH, ROBERT Thomas SCHULTZ · 2021 to 2026
$9.2M
Structural Development of Human Fetal BrainR01MH092535 · NIMH · UT SOUTHWESTERN MEDICAL CENTER · PI HUANG, HAO · 2011 to 2020
$4.6M
Infant Atlas of Brain PerfusionR01EB031284 · NIBIB · CHILDREN'S HOSP OF PHILADELPHIA · PI HUANG, HAO · 2021 to 2025
$2.4M
Association of gene expression and brain connectivity in human cerebral cortex development and adulthoodR01MH129981 · NIMH · CHILDREN'S HOSP OF PHILADELPHIA · PI HUANG, HAO · 2022 to 2025
$1.8M
Next-generation human connectome atlas across the timespan of brain developmentR01MH125333 · NIMH · CHILDREN'S HOSP OF PHILADELPHIA · PI HUANG, HAO · 2021 to 2022
$456k
Reliable prediction of high-risk infants of autism with cortical microstructural biomarkerR21MH123930 · NIMH · CHILDREN'S HOSP OF PHILADELPHIA · PI OUYANG, MINHUI · 2021 to 2022
$415k
National Natural Science Foundation of China (National Science Foundation of China) Nos. 82021004NIBIB NIH HHS R01 EB031284NICHD NIH HHS P50 HD105354NIMH NIH HHS R01 MH092535NIMH NIH HHS R01 MH125333NIMH NIH HHS R01 MH129981NIMH NIH HHS R21 MH123930
6 · The paper itself

Abstract

The postnatal white matter connectome undergoes profound reorganization, yet the topological principles governing its spatiotemporal maturation remain largely unknown. Using connectome mapping, machine learning, and neurobiological annotation, we show hierarchical network development from birth to childhood and its association with neurobiological signatures. We identify two cardinal topological transformations that change rapidly during infancy and continue to refine into childhood, as characterized by nonlinear global increases in network efficiency and robustness to nodal attack, and regional reorganization with accelerated hub consolidation and prolonged modular reconfiguration, predominantly involving the prefrontal and insular cortices. Early developmental trajectories of these association cortices predict late childhood network architecture through local microstructural maturation of connected white matter tracts. These patterns align with well-established multiscale cortical hierarchies, including anatomical, evolutionary, and energy metabolism axes. Our findings reveal critical neurotopological milestones after postnatal development and establish a unified multiscale framework linking macroscale network dynamics to biologically constrained rules.

Indexed as

BrainConnectomeNerve NetWhite MatterChild, PreschoolFemaleHumansInfantInfant, NewbornMachine LearningMagnetic Resonance ImagingMaleNeural PathwaysNeurodevelopment

Identifiers

PMID41571660
PMCPMC12929715

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.