Evidence map›Paper›PMID 39975042›Full record

ArticlebioRxiv : the preprint server for biology2025

Deciphering Multiway Multiscale Brain Network Connectivity: Insights from Birth to 6 Months.

Qiang Li, Zening Fu, Hasse Walum, Masoud Seraji, Prerana Bajracharya, Vince Calhoun, Sarah Shultz, Armin Iraji

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

8 authors.

Qiang LiTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA, USA.ORCID 0000-0002-5337-0676
Zening FuTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA, USA.
Hasse WalumDivision of Autism & Related Disabilities, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.
Masoud SerajiTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA, USA.ORCID 0000-0002-3179-4275
Prerana BajracharyaTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA, USA.
Vince CalhounTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA, USA.ORCID 0000-0001-9058-0747
Sarah ShultzDivision of Autism & Related Disabilities, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.
Armin IrajiTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA, USA.

Funding

Measuring gene-environment transactions to identify sensitive periods for infant social behavior & brain growthR01MH118285 · NIMH · EMORY UNIVERSITY · PI JONES, WARREN, SHULTZ, SARAH · 2019 to 2024
$3.7M
Mapping the developing infant connectomeR01EB027147 · NIBIB · EMORY UNIVERSITY · PI CALHOUN, VINCE D, DAI, XIONGTAO · 2019 to 2022
$1.9M
Mapping the Infant Brain Developmental Connectome: Temporally Precise Growth Trajectories of Changing Infant Brain TopologyR01MH119251 · NIMH · EMORY UNIVERSITY · PI IRAJI, ARMIN, SHULTZ, SARAH · 2020 to 2023
$1.0M
NIBIB NIH HHS R01 EB027147NIMH NIH HHS R01 MH118285NIMH NIH HHS R01 MH119251
6 · The paper itself

Abstract

Converging evidence suggests that understanding the human brain requires more than just examining pairwise functional brain interactions. The human brain is a complex, nonlinear system, and focusing solely on linear pairwise functional connectivity often overlooks important nonlinear and higher-order relationships. Infancy is a critical period marked by significant brain development that could contribute to future learning, health, and life success. Exploring higher-order functional relationships in the brain can provide insight into brain function and development. To the best of our knowledge, there is no existing research on multiway, multiscale brain network interactions in infants. In this study, we comprehensively investigate the interactions among brain intrinsic connectivity networks (ICNs), including both pairwise (pair-FNC) and triple relationships (tri-FNC). We focused on an infant dataset collected between birth and six months, a critical period for brain maturation. Our results revealed significant hierarchical, multiway, multiscale brain functional network interactions in the infant brain. These findings suggest that tri-FNC provide additional insights beyond what pairwise interactions reveal during early brain development. The tri-FNC predominantly involve the default mode, sensorimotor, visual, limbic, language, salience, and central executive domains. Notably, these triplet networks align with the classical triple network model of the human brain, which includes the default mode network, the salience network, and the central executive network. This suggests that the brain network system might already be initially established during the first six months of infancy. Interestingly, tri-FNC in the default mode and salience domains showed significantly stronger nonlinear interactions with age compared to pair-FNC. We also found that pair-FNC were less effective at detecting these networks. The present study suggests that exploring tri-FNC can offer additional insights beyond pair-FNC by capturing higher-order nonlinear interactions, potentially yielding more reliable biomarkers to characterize developmental trajectories.

Indexed as

Brain DevelopmentHigher-order Nonlinear InteractionsInfantMultiscale Brain Networkspair-FNCtri-FNC

Identifiers

PMID39975042
PMCPMC11838216

What OpenQuestion holds

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LicenceCC BY-NC
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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.