Evidence map›Paper›PMID 39975397›Full record

ArticlebioRxiv : the preprint server for biology2025

Developmental Variations in Recurrent Spatiotemporal Brain Propagations from Childhood to Adulthood.

Kyoungseob Byeon, Hyunjin Park, Shinwon Park, Jon Cluce, Kahini Mehta, Matthew Cieslak, Zaixu Cui, Seok-Jun Hong, Catie Chang, Jonathan Smallwood and 3 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

13 authors.

Kyoungseob ByeonChild Mind Institute, New York, NY, United States.
Hyunjin ParkSchool of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, South Korea.
Shinwon ParkChild Mind Institute, New York, NY, United States.
Jon CluceChild Mind Institute, New York, NY, United States.
Kahini MehtaPenn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Matthew CieslakPenn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Zaixu CuiBeijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Seok-Jun HongChild Mind Institute, New York, NY, United States.
Catie ChangDepartments of Electrical and Computer Engineering, Computer Science, and Biomedical Engineering, Vanderbilt University, Nashville, TN, United States.
Jonathan SmallwoodDepartment of Psychology, Queens University, Kingston, ON, Canada.
Theodore D SatterthwaitePenn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Michael P MilhamChild Mind Institute, New York, NY, United States.
Ting XuChild Mind Institute, New York, NY, United States.

Funding

Project 5: ComputationalP50MH109429 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI Michael Peter Milham · 2017 to 2026
$25.3M
Longitudinal Mapping of Network Development Underlying Executive Dysfunction in AdolescenceR01MH113550 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Danielle Smith Bassett, Theodore Satterthwaite · 2018 to 2026
$6.9M
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
Inter-modal Coupling Image AnalyticsR01MH112847 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Theodore Satterthwaite, Russell Takeshi Shinohara · 2017 to 2026
$5.9M
Precision mapping of individualized executive networks in youthR37MH125829 · NIMH · UNIVERSITY OF MINNESOTA · PI Damien A Fair, Theodore Satterthwaite · 2021 to 2026
$4.7M
Reproducible imaging-based brain growth charts for psychiatryR01MH120482 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI MILHAM, MICHAEL PETER, SATTERTHWAITE, THEODORE · 2019 to 2023
$3.5M
C-PAC: A configurable, compute-optimized, cloud-enabled neuroimaging analysis software for reproducible translational and comparativeR24MH114806 · NIMH · CHILD MIND INSTITUTE, INC. · PI CRADDOCK, RICHARD CAMERON, MILHAM, MICHAEL PETER · 2018 to 2020
$1.6M
An Alignment Framework For Mapping Brain Dynamics and Substrates of Human Cognition Across SpeciesRF1MH128696 · NIMH · CHILD MIND INSTITUTE, INC. · PI XU, TING · 2021 to 2021
$1.2M
CRCNS: Linking receptorarchitecture and functional brain networks across speciesR01MH139349 · NIMH · CHILD MIND INSTITUTE, INC. · PI Thomas Funck · 2024 to 2026
$516k
NIBIB NIH HHS R01 EB022573NIMH NIH HHS P50 MH109429NIMH NIH HHS R01 MH112847NIMH NIH HHS R01 MH113550NIMH NIH HHS R01 MH120482NIMH NIH HHS R01 MH139349NIMH NIH HHS R24 MH114806NIMH NIH HHS R37 MH125829NIMH NIH HHS RF1 MH128696
6 · The paper itself

Abstract

The brain undergoes profound structural and functional transformations from childhood to adolescence. Convergent evidence suggests that neurodevelopment proceeds in a hierarchical manner, characterized by heterogeneous maturation patterns across brain regions and networks. However, the maturation of the intrinsic spatiotemporal propagations of brain activity remains largely unexplored. This study aims to bridge this gap by delineating spatiotemporal propagations from childhood to early adulthood. By leveraging a recently developed approach that captures time-lag dynamic propagations, we characterized intrinsic dynamic propagations along three axes: sensory-association (S-A), 'task-positive' to default networks (TP-D), and somatomotor-visual (SM-V) networks, which progress towards adult-like brain dynamics from childhood to early adulthood. Importantly, we demonstrated that as participants mature, there is a prolonged occurrence of the S-A and TP-D propagation states, indicating that they spend more time in these states. Conversely, the prevalence of SM-V propagation states declines during development. Notably, top-down propagations along the S-A axis exhibited an age-dependent increase in occurrence, serving as a superior predictor of cognitive scores compared to bottom-up S-A propagation. These findings were replicated across two independent cohorts (N = 677 in total), emphasizing the robustness and generalizability of these findings. Our results provide new insights into the emergence of adult-like functional dynamics during youth and their role in supporting cognition.

Indexed as

adolescencecortical developmentdynamic brain activityfMRINeurodevelopmenttop-down processing

Identifiers

PMID39975397
PMCPMC11838599

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.