Evidence map›Paper›PMID 36255322›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2023

Brainnetome atlas of preadolescent children based on anatomical connectivity profiles.

Wen Li, Lingzhong Fan, Weiyang Shi, Yuheng Lu, Jin Li, Na Luo, Haiyan Wang, Congying Chu, Liang Ma, Ming Song and 4 more

Erratum issuedAbstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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. Learning Explainable Imaging-Genetics Associations Related to a Neurological Disorder.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2026
    Article
  2. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Wen LiBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.
Lingzhong FanBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.
Weiyang ShiBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.
Yuheng LuBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.
Jin LiBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.
Na LuoBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.
Haiyan WangBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.
Congying ChuBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.
Liang MaBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.
Ming SongBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.
Kaixin LiBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.
Luqi ChengSchool of Life and Environmental Sciences, Guilin University of Electronic Technology, No.1 Jinji Road, Qixing District, Guilin 541004, China.
Long CaoKey Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, China.
Tianzi JiangBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing 100190, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the preadolescent period, when the cerebral thickness, curvature, and myelin are constantly changing, the brain's regionalization patterns underwent persistent development, contributing to the continuous improvements of various higher cognitive functions. Using a brain atlas to study the development of these functions has attracted much attention. However, the brains of children do not always have the same topological patterns as those of adults. Therefore, age-specific brain mapping is particularly important, serving as a basic and indispensable tool to study the normal development of children. In this study, we took advantage of longitudinal data to create the brain atlas specifically for preadolescent children. The resulting human Child Brainnetome Atlas, with 188 cortical and 36 subcortical subregions, provides a precise period-specific and cross-validated version of the brain atlas that is more appropriate for adoption in the preadolescent period. In addition, we compared and illustrated for regions with different topological patterns in the child and adult atlases, providing a topologically consistent reference for subsequent research studying child and adolescent development.

Indexed as

BrainMagnetic Resonance ImagingAdolescentAdolescent DevelopmentAdultBrain MappingChildCognitionHumansanatomical connectivityBrainnetome atlasdevelopmentdiffusion magnetic resonance imagingpreadolescent child

Identifiers

PMID36255322
PMCPMC10151881

What OpenQuestion holds

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LicenceCC BY-NC
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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.