Evidence map›Paper›PMID 41894329›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Correspondence of large-scale functional brain network decline across aging mice and humans.

Ezra Winter-Nelson, Eyal Bergmann, Micaela Y Chan, Gabriella Vill, Liang Han, Ziwei Zhang, Alexandra Kavushansky, Irit Dolgopyat, Jad Asleh, Jennifer D Whitesell and 2 more

Abstract readComparative Study
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Heterogeneous brain alterations in treatment-resistant depression converge on common control networks.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026
    Pooled it
  2. Correspondence of large-scale functional brain network decline across aging mice and humans.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. 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

12 authors.

Ezra Winter-NelsonCenter for Vital Longevity, The University of Texas at Dallas, Dallas, TX 75235.ORCID 0000-0003-2241-5277
Eyal BergmannDepartment of Neuroscience, Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel 3525433.
Micaela Y ChanCenter for Vital Longevity, The University of Texas at Dallas, Dallas, TX 75235.
Gabriella VillZuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY.ORCID 0009-0007-5362-9741
Liang HanCenter for Vital Longevity, The University of Texas at Dallas, Dallas, TX 75235.
Ziwei ZhangCenter for Vital Longevity, The University of Texas at Dallas, Dallas, TX 75235.ORCID 0009-0006-0591-8314
Alexandra KavushanskyDepartment of Neuroscience, Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel 3525433.ORCID 0000-0002-8511-3068
Irit DolgopyatDepartment of Neuroscience, Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel 3525433.
Jad AslehDepartment of Neuroscience, Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel 3525433.ORCID 0000-0003-3498-0003
Jennifer D WhitesellAllen Institute for Brain Science, Seattle, WA 98109.
Itamar Kahn *Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY.ORCID 0000-0002-1895-8677
Gagan S Wig *Center for Vital Longevity, The University of Texas at Dallas, Dallas, TX 75235.ORCID 0000-0002-6432-5192

Funding

Research Network on Animal Models to Understand Social Dimensions of AgingR24AG065172 · NIA · UNIVERSITY OF MINNESOTA · PI Susan C. Alberts, Alessandro Bartolomucci · 2020 to 2026
$2.6M
CRCNS: Assessing long-term impacts of disruption to large-scale brain networksR01AG092219 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Itamar Kahn, Gagan S Wig · 2024 to 2026
$1.7M
HHS | NIH | National Institute on Aging (NIA) AG063930HHS | NIH | National Institute on Aging (NIA) AG092219HHS | NIH | National Institute on Aging (NIA) R24AG065172James S. McDonnell Foundation (JSMF) Understanding Human Cognition Scholar AwardNIA NIH HHS R01 AG092219
6 · The paper itself

Abstract

Human aging is marked by progressive reorganization of large-scale functional brain networks; these brain network changes have been linked to cognitive decline and disease vulnerability. Conversely, while mice have served as powerful models for understanding the molecular and cellular changes that occur over the lifespan, an absence of precise characterization of age-related changes in large-scale functional brain network organization has limited cross-species translational insights. Here, using densely sampled resting-state functional MRI data acquired cross-sectionally and longitudinally in awake mice over a broad range of adulthood (n = 82; 3 to 20 mo), we describe organizational features and age-related alterations of the mouse's functional connectome. Mouse resting-state functional connectivity recapitulates known functional circuits, demonstrating the organizational validity of these signals. Graph theoretic analysis applied to functional connectivity reveals that mice exhibit modular architectures of functional brain network organization and that increasing age is associated with decreasing system segregation, indicative of network dedifferentiation analogous to observations in humans. Notably, mouse resting-state brain networks are more segregated than those of humans [determined using data from the Human Connectome Project and its developmental- and aging-counterparts (n = 1,179; 18 to 90 y)], attributable to mice exhibiting a diminished contribution of long-range functional relationships that integrate distributed systems. Mice also exhibit slower rates of age-related decline in brain network organization relative to humans, highlighting important species differences in functional brain network organization and trajectories of brain network aging. These findings establish a model of large-scale functional brain network aging in mice and provide a translational bridge across species and spatial scales of analysis.

Indexed as

AgingBrainConnectomeMagnetic Resonance ImagingAdolescentAdultAgedAged, 80 and overAnimalsFemaleHumansMaleMiceMiddle AgedYoung Adultagingbrain networksmouseresting-state correlationssystem segregation

Identifiers

PMID41894329
PMCPMC13037878

What OpenQuestion holds

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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.