Evidence map›Paper›PMID 39896611›Full record

ArticlebioRxiv : the preprint server for biology2025

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 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

12 authors.

Hongming LiCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA.
Zaixu CuiChinese Institute for Brain Research, Beijing, 102206, China.
Matthew CieslakDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
Taylor SaloDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
Tyler M MooreDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
Raquel E GurDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
Ruben C GurDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
Russell T ShinoharaCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA.
Desmond J OathesDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
Christos DavatzikosCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA.
Theodore D SatterthwaiteCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA.
Yong FanCenter for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA.

Funding

Penn Mental Health AIDS Research CenterP30MH097488 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Karine Dube, Kelly L Jordan-Sciutto · 2013 to 2026
$23.5M
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 EB022573NIMH NIH HHS P30 MH097488NINDS NIH HHS U24 NS130411
6 · The paper itself

Abstract

The brain functional connectome development is fundamental to neurocognitive growth in youth. While brain age prediction has been widely used to assess connectome development at the individual level, traditional approaches providing a global index overlook the spatial variability and inter-individual heterogeneity of functional connectivity (FC) development across the cortex. In this study, we introduced a regional brain development index to assess spatially fine-grained FC development. We examined the spatial variability of FC development and stratified individuals into subtypes with distinct patterns of spatial heterogeneity in region-wise FC development across the cortex through clustering. An evaluation conducted on a sample of youths aged 8-23 years using fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) revealed three distinct FC development subtypes. Individuals with advanced FC development aligned with the hierarchical brain organization along the sensorimotor-association (S-A) axis demonstrated superior cognitive performance compared to those with other patterns. These patterns were replicated in the Human Connectome Project Development (HCP-D) cohort, confirming their robustness. Further analysis revealed associations between FC development and gene expression, with enriched genes linked to neural differentiation, synaptogenesis, and myelination. These findings suggest that spatial heterogeneity in FC development reflects underlying cortical microstructure and hierarchical cortical organization, underscoring its critical role in understanding neurocognitive maturation and individual variability during youth.

Identifiers

PMID39896611
PMCPMC11785253

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.