Evidence map›Paper›PMID 41554647›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2026

Distributed fMRI Patterns Coupled to Low-Frequency Cardiorespiratory Dynamics Provide Markers of Aging.

Shiyu Wang, Richard Song, Laurent M Lochard, Jiawen Fan, Yamin Li, Kimberly Kundert-Obando, Caroline Martin, Sarah E Goodale, Haatef Pourmotabbed, J Mason Harding and 10 more

Abstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2026. 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

20 authors.

Shiyu WangDepartments of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37240 shiyu.wang.1@vanderbilt.edu catie.chang@vanderbilt.edu.ORCID 0009-0000-3518-4231
Richard SongComputer Science, Vanderbilt University, Nashville, Tennessee 37240.ORCID 0009-0009-5850-2058
Laurent M LochardDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee 37240.
Jiawen FanAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts 02129.
Yamin LiComputer Science, Vanderbilt University, Nashville, Tennessee 37240.
Kimberly Kundert-ObandoNeuroscience Graduate Program, Vanderbilt University, Nashville, Tennessee 37240.
Caroline MartinDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee 37240.
Sarah E GoodaleDepartments of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37240.
Haatef PourmotabbedDepartments of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37240.
J Mason HardingDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee 37240.
Terra LeeProgram in Neuroscience, Vanderbilt University, Nashville, Tennessee 37240.
Chang LiComputer Science, Vanderbilt University, Nashville, Tennessee 37240.
Shengchao ZhangDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee 37240.
Roza G BayrakDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee 37240.
Taylor BoltDepartments of Psychiatry and Biobehavioral Sciences and.
Jason S NomiDepartments of Psychiatry and Biobehavioral Sciences and.
Lucina Q UddinDepartments of Psychiatry and Biobehavioral Sciences and.
Jingyuan E ChenAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts 02129.
Mara MatherLeonard Davis School of Gerontology, Departments of Psychology and Biomedical Engineering, University of Southern California, Los Angeles, California 90089.ORCID 0000-0003-4331-6112
Catie ChangDepartments of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37240 shiyu.wang.1@vanderbilt.edu catie.chang@vanderbilt.edu.

Funding

ABCD-USA Consortium: Coordinating CenterU24DA041147 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SANDRA A BROWN, TERRY L. JERNIGAN · 2015 to 2026
$54.7M
Project 5: ComputationalP50MH109429 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI Michael Peter Milham · 2017 to 2026
$25.3M
17/21 ABCD-USA CONSORTIUM: RESEARCH PROJECT SITE AT UCLAU01DA050987 · NIDA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SUSAN Y BOOKHEIMER, Mirella Dapretto · 2020 to 2026
$9.0M
Training in Fundamental NeuroscienceT32MH064913 · NIMH · VANDERBILT UNIVERSITY · PI IHRIE, REBECCA A, WINDER, DANNY G. · 2001 to 2022
$7.6M
Training Program for Innovative Engineering Research in Surgery and InterventionT32EB021937 · NIBIB · VANDERBILT UNIVERSITY · PI Dario J Englot, Michael Ian Miga · 2016 to 2026
$2.3M
Longitudinal investigation of bilingualism, executive function, and brain organization in autismR01HD116691 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Lucina Qazi Uddin · 2025 to 2026
$1.4M
fMRI physiological signatures of aging and Alzheimer's DiseaseRF1MH125931 · NIMH · VANDERBILT UNIVERSITY · PI CHANG, CATHERINE ELIZABETH · 2021 to 2021
$1.1M
Exploratory investigation of bilingualism, executive function, and brain organization in children with autismR21HD111805 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI UDDIN, LUCINA QAZI · 2023 to 2023
$432k
Longitudinal effects of aging and neurodegeneration on structure-function and brain-behavior relationshipsK00AG079810 · NIA · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Sarah E Goodale · 2025 to 2026
$161k
Characterizing vigilance in fMRI data and its relation to age-related cognitive impairment.F99AG079810 · NIA · VANDERBILT UNIVERSITY · PI GOODALE, SARAH E · 2022 to 2024
$65k
NIA NIH HHS F99 AG079810NIA NIH HHS K00 AG079810NIBIB NIH HHS T32 EB021937NICHD NIH HHS R01 HD116691NICHD NIH HHS R21 HD111805NIDA NIH HHS U01 DA050987NIDA NIH HHS U24 DA041147NIMH NIH HHS P50 MH109429NIMH NIH HHS RF1 MH125931NIMH NIH HHS T32 MH064913
6 · The paper itself

Abstract

How aging affects brain-body connections can be investigated through changes in the coupling between functional magnetic resonance imaging (fMRI) signals and bodily autonomic processes across the adult lifespan. Recent studies using univariate approaches have identified age-related changes in the association between fMRI signals from multiple individual brain regions and low-frequency respiratory and cardiac activity. Here, we investigate if whole-brain spatial fMRI patterns associated with low-frequency physiological processes (heart rate and respiratory volume fluctuations) present generalizable changes with age. Data from human participants of both sexes are included in the analysis. We find that chronological age can be predicted statistically beyond chance from patterns of low-frequency fMRI-physiological coupling, even after accounting for individual differences in physiological signal characteristics and brain anatomy. Notably, brain areas implicated in central autonomic regulation, including nodes within salience and ventral attention networks (e.g., insula and middle cingulate cortex), are among the strongest contributors to age prediction. Furthermore, we observe that after removing physiological effects from fMRI data, the residual blood oxygen level-dependent signal variability is still a reliable indicator of age. Together, these findings underscore the close integration between brain and body physiology and highlight this interaction as a potential biomarker of the aging process.

Indexed as

AgingBrainHeart RateMagnetic Resonance ImagingAdultAgedBrain MappingFemaleHumansMaleMiddle AgedYoung Adultagingbrain–body interactionsfMRI variabilityheart raterespiratory variationsystemic physiology

Identifiers

PMID41554647
PMCPMC12896689

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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.