Evidence map›Paper›PMID 42365014›Full record

ArticleNature communications2026

In-scanner thoughts contribute to resting-state functional connectivity.

Javier Gonzalez-Castillo, Megan A Spurney, Ka Chun Lam, Isabel S Gephart, Francisco Pereira, Daniel A Handwerker, Julia W Y Kam, Peter A Bandettini

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Javier Gonzalez-CastilloSection on Functional Imaging Methods, NIMH, NIH, Bethesda, MA, USA. javier.gonzalez-castillo@nih.gov.ORCID http://orcid.org/0000-0002-6520-5125
Megan A SpurneySection on Functional Imaging Methods, NIMH, NIH, Bethesda, MA, USA.
Ka Chun LamMachine Learning Team, NIMH, NIH, Bethesda, MA, USA.ORCID http://orcid.org/0000-0003-2131-4386
Isabel S GephartSection on Functional Imaging Methods, NIMH, NIH, Bethesda, MA, USA.
Francisco PereiraMachine Learning Team, NIMH, NIH, Bethesda, MA, USA.
Daniel A HandwerkerSection on Functional Imaging Methods, NIMH, NIH, Bethesda, MA, USA.ORCID http://orcid.org/0000-0001-7261-4042
Julia W Y KamDepartment of Psychology, University of Calgary, Calgary, AL, Canada.ORCID http://orcid.org/0000-0002-2369-2148
Peter A BandettiniSection on Functional Imaging Methods, NIMH, NIH, Bethesda, MA, USA.ORCID http://orcid.org/0000-0001-9038-4746

Funding

Functional MRI Core FacilityZICMH002884 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI BANDETTINI, PETER · 2009 to 2025
$85.5M
Functional MRI Method DevelopmentZIAMH002783 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI BANDETTINI, PETER · 2009 to 2025
$38.4M
Machine Learning TeamZICMH002968 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI PEREIRA, FRANCISCO · 2018 to 2025
$13.9M
Intramural NIH HHS ZIA MH002783Intramural NIH HHS ZIC MH002884Intramural NIH HHS ZIC MH002968U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) ZIAMH002783U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) ZICMH002884U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) ZICMH002968
6 · The paper itself

Abstract

Resting-state fMRI (rsfMRI) scans-acquired in the absence of experimentally controlled stimuli or task demands-are widely used to identify aberrant patterns of functional connectivity (FC) in clinical populations. To minimize interpretational uncertainty, researchers routinely control for across-cohort disparities in age, gender, comorbidities, and head motion. Yet, studies rarely consider the possibility that systematic differences in inner experience (i.e., how subjects think and feel during the scan) directly affect FC measures. Here, using an rsfMRI dataset comprising 469 scans with retrospective experiential annotations, we show that summary descriptors of in-scanner experience are reproducible across visits and subject-specific, consistent with trait-like characteristics. We further show that widespread significant differences in FC are observed between scans that are associated with different reported experiential profiles, and that FC can predict specific experiential dimensions with performance comparable to that reported for demographic, cognitive, and clinical variables. Together, these findings highlight the key role that in-scanner experience should play when interpreting FC in the context of rsfMRI. Given that the available experiential measures are retrospective summaries, these results speak to stable experiential tendencies rather than potential moment-to-moment, state-dependent relationships between ongoing experience and concurrent brain activity.

Indexed as

BrainMagnetic Resonance ImagingRestThinkingAdultBrain MappingFemaleHumansMaleRetrospective Studies

Identifiers

PMID42365014
PMCPMC13454257

What OpenQuestion 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 OpenQuestion graph.