Evidence map›Paper›PMID 39314355›Full record

ArticlebioRxiv : the preprint server for biology2025

The Generalizability of Cortical Area Parcellations Across Early Childhood.

Jiaxin Cindy Tu, Michael Myers, Wei Li, Jiaqi Li, Xintian Wang, Donna Dierker, Trevor K M Day, Abraham Z Snyder, Aidan Latham, Jeanette K Kenley and 18 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

28 authors.

Jiaxin Cindy TuDepartment of Radiology, Washington University in St. Louis.ORCID 0000-0003-1982-9890
Michael MyersDepartment of Psychiatry, Washington University in St. Louis.
Wei LiDepartment of Mathematics and Statistics, Washington University in St. Louis.
Jiaqi LiDepartment of Mathematics and Statistics, Washington University in St. Louis.
Xintian WangDepartment of Radiology, Washington University in St. Louis.
Donna DierkerDepartment of Radiology, Washington University in St. Louis.
Trevor K M DayMasonic Institute for the Developing Brain, University of Minnesota.
Abraham Z SnyderDepartment of Radiology, Washington University in St. Louis.
Aidan LathamDepartment of Neurology, Washington University in St. Louis.
Jeanette K KenleyDepartment of Neurology, Washington University in St. Louis.
Chloe M SobolewskiDepartment of Radiology, Washington University in St. Louis.
Yu WangDepartment of Mathematics and Statistics, Washington University in St. Louis.
Alyssa K LabonteDepartment of Psychiatry, Washington University in St. Louis.
Eric FeczkoMasonic Institute for the Developing Brain, University of Minnesota.ORCID 0000-0003-1337-5517
Omid KardanDepartment of Psychiatry, University of Michigan.
Lucille A MooreMasonic Institute for the Developing Brain, University of Minnesota.
Chad M SylvesterDepartment of Psychiatry, Washington University in St. Louis.
Damien A FairMasonic Institute for the Developing Brain, University of Minnesota.
Jed T ElisonMasonic Institute for the Developing Brain, University of Minnesota.
Barbara B WarnerDepartment of Pediatrics, Washington University in St. Louis.ORCID 0000-0002-9910-4461
Deanna M BarchDepartment of Psychological and Brain Sciences, Washington University in St Louis.
Cynthia E RogersDepartment of Psychiatry, Washington University in St. Louis.
Joan L LubyDepartment of Psychiatry, Washington University in St. Louis.
Christopher D SmyserDepartment of Radiology, Washington University in St. Louis.
Evan M GordonDepartment of Radiology, Washington University in St. Louis.
Timothy O LaumannDepartment of Radiology, Washington University in St. Louis.
Adam T EggebrechtDepartment of Radiology, Washington University in St. Louis.
Muriah D WheelockDepartment of Radiology, Washington University in St. Louis.

Funding

Early Life Adversity, Biological Embedding, and Risk for Developmental Precursors of Mental DisordersR01MH113883 · NIMH · WASHINGTON UNIVERSITY · PI JOAN L. LUBY, Christopher Daniel Smyser · 2018 to 2026
$20.6M
UNC/UMN Baby Connectome ProjectU01MH110274 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ELISON, JED THOMAS, GILMORE, JOHN HORACE · 2016 to 2019
$4.5M
Individualized Mechanisms of Neural Plasticity and Response to Interventions in NeonatesR01MH134966 · NIMH · WASHINGTON UNIVERSITY · PI Chad Michael Sylvester · 2024 to 2026
$4.2M
Neonatal Brain Activity and Risk for Anxiety Disorders in Early ChildhoodR01MH122389 · NIMH · WASHINGTON UNIVERSITY · PI Chad Michael Sylvester · 2020 to 2026
$3.9M
Infant Brain and Behavioral Signatures of Later Emerging Risk for PsychopathologyR01MH104324 · NIMH · UNIVERSITY OF MINNESOTA · PI ELISON, JED THOMAS · 2014 to 2018
$2.6M
Leveraging pediatric state-specific functional brain network dynamics to predict developmental outcomesR01HD115540 · NICHD · WASHINGTON UNIVERSITY · PI Muriah D Wheelock · 2024 to 2026
$1.9M
Innovative biostatistical approaches to network level analyses of connectome-behavior relationshipsR00EB029343 · NIBIB · WASHINGTON UNIVERSITY · PI WHEELOCK, MURIAH D · 2022 to 2024
$955k
Network level analysis of progressive brain degeneration in autosomal dominant Alzheimer diseaseK99EB029343 · NIBIB · WASHINGTON UNIVERSITY · PI WHEELOCK, MURIAH D · 2020 to 2021
$484k
NIBIB NIH HHS K99 EB029343NIBIB NIH HHS R00 EB029343NICHD NIH HHS R01 HD115540NIMH NIH HHS R01 MH104324NIMH NIH HHS R01 MH113883NIMH NIH HHS R01 MH122389NIMH NIH HHS R01 MH134966NIMH NIH HHS U01 MH110274
6 · The paper itself

Abstract

The cerebral cortex consists of distinct areas that develop through intrinsic embryonic patterning and postnatal experiences. Accurate parcellation of these areas in neuroimaging studies improves statistical power and cross-study comparability. Given significant brain changes in volume, microstructure, and connectivity during early life, we hypothesized that cortical areas in 1- to 3-year-olds would differ markedly from neonates and increasingly resemble adult patterns as development progresses. Here, we parcellated the cerebral cortex into putative areas using local functional connectivity gradients in 92 toddlers at 2 years old. We demonstrate high reproducibility of these cortical regions across 1- to 3-year-olds in two independent datasets. The area boundaries in 1- to 3-year-olds were more similar to those in adults than those in neonates. While the age-specific group area parcellation better fit the underlying functional connectivity in individuals during the first 3 years, adult area parcellations might still have some utility in developmental studies, especially in children older than 6 years. Additionally, we provide connectivity-based community assignments of the parcels, showing fragmented anterior and posterior components based on the strongest connectivity, yet alignment with adult systems when weaker connectivity was included.

Indexed as

areadevelopmentfMRIfunctional connectivitylifespanparcellation

Identifiers

PMID39314355
PMCPMC11419084

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.