Evidence map›Paper›PMID 42039092›Full record

ArticleNetwork neuroscience (Cambridge, Mass.)2026

Metastability of resting-state bold fMRI as a reliable biomarker of individual brain dynamics: An interrogation of within-subject variability as a function of total acquisition time.

Hiba Sheheitli, Robert Hermosillo, Gracie Grimsrud, Thomas Madison, Oscar Miranda Dominguez, Steven Nelson, Damien Fair, Ziad Nahas

Abstract read
In one paragraph

Article in Network neuroscience (Cambridge, Mass.), 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

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

8 authors.

Hiba SheheitliDepartment of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, USA.ORCID https://orcid.org/0000-0003-3849-7692
Robert HermosilloDepartment of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, USA.
Gracie GrimsrudMasonic Institute for the Developing Brain, University of Minnesota, Minneapolis, USA.
Thomas MadisonMasonic Institute for the Developing Brain, University of Minnesota, Minneapolis, USA.
Oscar Miranda DominguezDepartment of Pediatrics, University of Minnesota, Minneapolis, USA.ORCID https://orcid.org/0000-0002-3622-0166
Steven NelsonDepartment of Pediatrics, University of Minnesota, Minneapolis, USA.
Damien FairDepartment of Pediatrics, University of Minnesota, Minneapolis, USA.ORCID https://orcid.org/0000-0001-8602-393X
Ziad NahasDepartment of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, USA.ORCID https://orcid.org/0000-0002-8391-5673

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metastability of BOLD fMRI signals is a commonly used proxy of brain dynamics in behavioral and clinical studies. To date, little has been done to assess the confidence with which we can use estimates of metastability as reliable biomarkers of individual brain state. We analyze whole-brain and network-specific metastability for a highly sampled individual brain (84 sessions taken over 18 months) and quantify the within-subject reliability for the metrics as a function of the amount of data used, which we find to be comparable to that seen for static functional connectivity. As considerable variability is observed across networks in the required amount of data, we combine the networks' metrics in one novel feature vector that exhibits an order of magnitude improvement in reliability. We then test reproducibility by analyzing the Midnight Scan Club dataset (10 subjects imaged over 10 consecutive days). Finally, we examine the susceptibility to change of the proposed metastability measure in another dataset examining brain dynamics under the effect of psilocybin. We conclude that the networks' metastability feature vector exhibits strong within-subject reliability that renders it a promising candidate for the study of individual-specific biomarkers of brain dynamics and potential targets for precision neuromodulation.

Indexed as

BOLD fMRI resting-state networksBrain dynamics biomarkerDynamic functional connectivityMetastabilityPhase synchronyPrecision functional mapping

Identifiers

PMID42039092
PMCPMC13108507

What Socratic holds

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LicenceCC BY
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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 Socratic graph.