Evidence map›Paper›PMID 35939665›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Mapping developmental regionalization and patterns of cortical surface area from 29 post-menstrual weeks to 2 years of age.

Ying Huang, Zhengwang Wu, Fan Wang, Dan Hu, Tengfei Li, Lei Guo, Li Wang, Weili Lin, Gang Li

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

22 citing papers in PubMed, 29 citations in OpenAlex.

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  19. Longitudinal mapping of the development of cortical thickness and surface area in rhesus macaques during the first three years.Proceedings of the National Academy of Sciences of the United States of America · 2023
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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

9 authors at 2 institutions in 2 countries.

Ying HuangSchool of Automation, Northwestern Polytechnical University, Xi'an 710071, China.ORCID 0000-0003-2127-5751
Zhengwang WuDepartment of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599.
Fan WangDepartment of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599.
Dan HuDepartment of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599.
Tengfei LiDepartment of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599.ORCID 0000-0001-6142-3865
Lei GuoSchool of Automation, Northwestern Polytechnical University, Xi'an 710071, China.
Li WangDepartment of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599.
Weili LinDepartment of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599.ORCID 0000-0002-2900-8204
Gang LiDepartment of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599.
University of North Carolina at Chapel Hill · USNorthwestern Polytechnical University · CN

Funding

UNC/UMN Baby Connectome ProjectU01MH110274 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ELISON, JED THOMAS, GILMORE, JOHN HORACE · 2016 to 2019
$4.5M
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
Harmonizing and Archiving of Large-scale Infant Neuroimaging DataRF1MH123202 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI LI, GANG · 2021 to 2021
$627k
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
NIMH NIH HHS K01 MH109773NIMH NIH HHS R01 MH116225NIMH NIH HHS R01 MH117943NIMH NIH HHS RF1 MH123202NIMH NIH HHS U01 MH110274
6 · The paper itself

Abstract

Surface area of the human cerebral cortex expands extremely dynamically and regionally heterogeneously from the third trimester of pregnancy to 2 y of age, reflecting the spatial heterogeneity of the underlying microstructural and functional development of the cerebral cortex. However, little is known about the developmental patterns and regionalization of cortical surface area during this critical stage, due to the lack of high-quality imaging data and accurate computational tools for pediatric brain MRI data. To fill this critical knowledge gap, by leveraging 1,037 high-quality MRI scans with the age between 29 post-menstrual weeks and 24 mo from 735 pediatric subjects in two complementary datasets, i.e., the Baby Connectome Project (BCP) and the developing Human Connectome Project (dHCP), and state-of-the-art dedicated image-processing tools, we unprecedentedly parcellate the cerebral cortex into a set of distinct subdivisions purely according to the developmental patterns of the cortical surface. Our discovered developmentally distinct subdivisions correspond well to structurally and functionally meaningful regions and reveal spatially contiguous, hierarchical, and bilaterally symmetric patterns of early cortical surface expansion. We also show that high-order association subdivisions, where cortical folds emerge later during prenatal stages, undergo more dramatic cortical surface expansion during infancy, compared with the central regions, especially the sensorimotor and insula cortices, thus forming a distinct central-pole division in early cortical surface expansion. These results provide an important reference for exploring and understanding dynamic early brain development in health and disease.

Indexed as

Cerebral CortexConnectomeHumansImage Processing, Computer-AssistedInfantInfant, NewbornMagnetic Resonance Imagingcortical surface areadevelopmental regionalizationearly brain development

Identifiers

PMID35939665
PMCPMC9388141
OpenAlexW4290725088

What OpenQuestion holds

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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.