Evidence map›Paper›PMID 38278807›Full record

ArticleNature communications2024

Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence.

Xinyuan Liang, Lianglong Sun, Xuhong Liao, Tianyuan Lei, Mingrui Xia, Dingna Duan, Zilong Zeng, Qiongling Li, Zhilei Xu, Weiwei Men and 8 more

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

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

  1. Pooled it
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  11. The Brain Age Gap as a Predictor of Alcohol Initiation in Adolescence.bioRxiv : the preprint server for biology · 2026
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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

18 authors.

Xinyuan LiangState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.ORCID 0009-0007-2141-405X
Lianglong SunState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
Xuhong LiaoSchool of Systems Science, Beijing Normal University, Beijing, 100875, China.ORCID 0009-0000-0170-2520
Tianyuan LeiState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.ORCID 0000-0002-5921-5853
Mingrui XiaState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.ORCID 0000-0003-4615-9132
Dingna DuanState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
Zilong ZengState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
Qiongling LiState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.ORCID 0000-0001-6989-2981
Zhilei XuState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
Weiwei MenCenter for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
Yanpei WangState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
Shuping TanBeijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, 100096, China.
Jia-Hong GaoCenter for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.ORCID 0000-0002-9311-0297
Shaozheng QinState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.ORCID 0000-0002-1859-2150
Sha TaoState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.ORCID 0000-0002-0928-0681
Qi DongState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
Tengda ZhaoState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China. tengdazhao@bnu.edu.cn.ORCID 0000-0002-5160-8417
Yong HeState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China. yong.he@bnu.edu.cn.ORCID 0000-0002-7039-2850

Funding

Mapping the Human Connectome During Typical DevelopmentU01MH109589 · NIMH · WASHINGTON UNIVERSITY · PI BARCH, DEANNA, BOOKHEIMER, SUSAN Y · 2016 to 2019
$17.1M
NIMH NIH HHS U01 MH109589
6 · The paper itself

Abstract

Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.

Indexed as

ConnectomeWhite MatterAdolescentBrainCerebral Cortical ThinningHumansMagnetic Resonance Imaging

Identifiers

PMID38278807
PMCPMC10817914

What OpenQuestion holds

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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.