Evidence map›Paper›PMID 40078534›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2025

Analysis of functional connectivity changes from childhood to old age: A study using HCP-D, HCP-YA, and HCP-A datasets.

Yaotian Wang, Shuoran Li, Jie He, Lingyi Peng, Qiaochu Wang, Xu Zou, Dana L Tudorascu, David J Schaeffer, Lauren Schaeffer, Diego Szczupak and 5 more

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

15 authors.

Yaotian WangDepartment of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States.
Shuoran LiDepartment of Statistics, University of Pittsburgh, Pittsburgh, PA, United States.
Jie HeDepartment of Statistics, University of Pittsburgh, Pittsburgh, PA, United States.
Lingyi PengDepartment of Biostatistics, University of Pittsburgh, Pittsburgh, PA, United States.
Qiaochu WangDepartment of Statistics, University of Pittsburgh, Pittsburgh, PA, United States.
Xu ZouDepartment of Statistics, University of Pittsburgh, Pittsburgh, PA, United States.
Dana L TudorascuDepartment of Biostatistics, University of Pittsburgh, Pittsburgh, PA, United States.
David J SchaefferDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, PA, United States.
Lauren SchaefferDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, PA, United States.
Diego SzczupakDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, PA, United States.
Jung Eun ParkDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, PA, United States.
Stacey J Sukoff RizzoDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, PA, United States.
Gregory W CarterThe Jackson Laboratory, Bar Harbor, ME, United States.
Afonso C SilvaDepartment of Neurobiology, University of Pittsburgh, Pittsburgh, PA, United States.
Tingting ZhangDepartment of Statistics, University of Pittsburgh, Pittsburgh, PA, United States.ORCID https://orcid.org/0000-0002-7895-8070

Funding

Vascular Moderators of the Impact of Alzheimer's Pathology in the Young-OldP01AG025204 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HOWARD J AIZENSTEIN, Ann D. Cohen · 2005 to 2026
$56.5M
Veterinary and Colony Management CoreU19AG074866 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Afonso C Silva · 2022 to 2026
$44.9M
Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
MAPPING THE HUMAN CONNECTOME DURING TYPICAL AGINGU01AG052564 · NIA · WASHINGTON UNIVERSITY · PI SALAT, DAVID H, TERPSTRA, MELISSA J · 2016 to 2020
$18.9M
Mapping the Human Connectome During Typical DevelopmentU01MH109589 · NIMH · WASHINGTON UNIVERSITY · PI BARCH, DEANNA, BOOKHEIMER, SUSAN Y · 2016 to 2019
$17.1M
Development and Validation of a Marmoset Model of Late-Onset Alzheimer Disease Based on Tau SeedingR24AG073190 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI SILVA, AFONSO C · 2021 to 2024
$4.5M
Statistical methods to improve reproducibility and reduce technical variability in heterogeneous multimodal neuroimaging studies of Alzheimer’s DiseaseR01AG063752 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI TUDORASCU, DANA L · 2019 to 2023
$3.0M
High-Throughput Computing for Genomics and Bioinformatics ResearchS10OD028483 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LEE, ADRIAN V · 2021 to 2021
$574k
NIA NIH HHS P01 AG025204NIA NIH HHS R01 AG063752NIA NIH HHS R24 AG073190NIA NIH HHS U01 AG052564NIA NIH HHS U19 AG074866NIH HHS S10 OD028483NIMH NIH HHS U01 MH109589NIMH NIH HHS U54 MH091657
6 · The paper itself

Abstract

We present a new clustering-enabled regression approach to investigate how functional connectivity (FC) of the entire brain changes from childhood to old age. By applying this method to resting-state functional magnetic resonance imaging data aggregated from three Human Connectome Project studies, we cluster brain regions that undergo identical age-related changes in FC and reveal diverse patterns of these changes for different region clusters. While most brain connections between pairs of regions show minimal yet statistically significant FC changes with age, only a tiny proportion of connections exhibit practically significant age-related changes in FC. Among these connections, FC between region clusters from the same functional network tends to decrease over time, whereas FC between region clusters from different networks demonstrates various patterns of age-related changes. Moreover, our research uncovers sex-specific trends in FC changes. Females show much higher FC mainly within the default mode network, whereas males display higher FC across several more brain networks. These findings underscore the complexity and heterogeneity of FC changes in the brain throughout the lifespan.

Indexed as

clusteringfunctional connectivitylifespan changesresting-state brain network

Identifiers

PMID40078534
PMCPMC11894817

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.