Evidence map›Paper›PMID 41578132›Full record

ArticleNature communications2026

Spatial heterogeneity and subtypes of functional connectivity development in youth.

Hongming Li, Zaixu Cui, Matthew Cieslak, Taylor Salo, Tyler M Moore, Raquel E Gur, Ruben C Gur, Russell T Shinohara, Desmond J Oathes, Christos Davatzikos and 2 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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Hongming LiCenter for AI and Data Science for Integrated Diagnostics (AI2D), University of Pennsylvania, Philadelphia, PA, USA. Hongming.Li@pennmedicine.upenn.edu.ORCID 0000-0001-6934-1928
Zaixu CuiChinese Institute for Brain Research, Beijing, China.ORCID 0000-0003-4385-8106
Matthew CieslakDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-1931-4734
Taylor SaloDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Tyler M MooreDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-1384-0151
Raquel E GurDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Ruben C GurDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-4082-8502
Russell T ShinoharaCenter for AI and Data Science for Integrated Diagnostics (AI2D), University of Pennsylvania, Philadelphia, PA, USA.
Desmond J OathesDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0001-7346-2669
Christos DavatzikosCenter for AI and Data Science for Integrated Diagnostics (AI2D), University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-1025-8561
Theodore D SatterthwaiteCenter for AI and Data Science for Integrated Diagnostics (AI2D), University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0001-7072-9399
Yong FanCenter for AI and Data Science for Integrated Diagnostics (AI2D), University of Pennsylvania, Philadelphia, PA, USA. Yong.Fan@pennmedicine.upenn.edu.ORCID 0000-0001-9869-4685

Funding

Personalized Functional Network Modeling to Characterize and Predict Psychopathology in YouthR01EB022573 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI Yong Fan, Theodore Satterthwaite · 2016 to 2026
$6.0M
The Neuroimaging Brain Chart Software SuiteU24NS130411 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Christos Davatzikos, Yong Fan · 2023 to 2026
$3.7M
Fast and robust deep learning tools for analysis of neuroimaging data of Alzheimer's diseaseR01AG066650 · NIA · UNIVERSITY OF PENNSYLVANIA · PI FAN, YONG · 2021 to 2025
$3.4M
NIA NIH HHS R01 AG066650NIBIB NIH HHS R01 EB022573U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering (NIBIB) R01EB022573U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS) U24NS130411U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) R01AG066650
6 · The paper itself

Abstract

Brain age prediction has been widely utilized to assess functional connectivity (FC) development, but conventional global brain age indices are limited in capturing spatial heterogeneity across the cortex. This study introduces a regional brain development index to characterize fine-grained FC maturation across cortical regions. We examined its spatial variability and stratified individuals into subtypes with distinct region-wise FC developmental patterns. Using data from the Philadelphia Neurodevelopmental Cohort (ages 8-23 years), we identified three distinct subtypes and found that individuals with advanced FC developmental pattern aligning with the sensorimotor-association axis exhibited superior cognitive performance. Robustness was confirmed through replication in the Human Connectome Project Development cohort. Further analyses revealed associations between FC development and gene expression linked to neural differentiation, synaptogenesis, and myelination. These findings suggest that spatial heterogeneity in FC development reflects cortical microstructure and hierarchical organization, underscoring its critical role in neurocognitive maturation during youth.

Indexed as

BrainConnectomeAdolescentChildCognitionFemaleHumansMagnetic Resonance ImagingMaleNerve NetNeurodevelopmentYoung Adult

Identifiers

PMID41578132
PMCPMC12929791

What Socratic holds

Textmetadata
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 Socratic graph.