Evidence map›Paper›PMID 41261142›Full record

ArticleMolecular psychiatry2026

Spatiotemporal complexity in the psychotic brain.

Qiang Li, Jingyu Liu, Godfrey D Pearlson, Jiayu Chen, Yu-Ping Wang, Jessica A Turner, Vince D Calhoun

Abstract read
In one paragraph

Article in Molecular psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Qiang LiTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA. qli27@gsu.edu.ORCID http://orcid.org/0000-0002-5337-0676
Jingyu LiuTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA.ORCID http://orcid.org/0000-0002-1724-7523
Godfrey D PearlsonDepartments of Psychiatry and Neurobiology, Yale University, New Haven, CT 06511, USA.
Jiayu ChenTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA.ORCID http://orcid.org/0000-0001-5059-372X
Yu-Ping WangDepartment of Biomedical Engineering, Tulane University, New Orleans, LA 70118, USA.ORCID http://orcid.org/0000-0001-9340-5864
Jessica A TurnerWexner Medical Center, Department of Psychiatry and Behavioral Health, Ohio State University, Columbus, OH 43210, USA.ORCID http://orcid.org/0000-0003-0076-8434
Vince D CalhounTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA. vcalhoun@gsu.edu.

Funding

Data-driven solutions for temporal, spatial, and spatiotemporal dynamic functional connectivityR01MH123610 · NIMH · GEORGIA STATE UNIVERSITY · PI ADALI, TULAY, CALHOUN, VINCE D · 2021 to 2025
$3.1M
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
National Science Foundation (NSF) 2112455U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01MH119251U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01MH123610
6 · The paper itself

Abstract

Psychotic disorders, such as schizophrenia and bipolar disorder, pose significant diagnostic challenges with major implications on mental health. The measures of resting-state fMRI spatiotemporal complexity offer a powerful tool for identifying irregularities in brain activity. To capture global brain connectivity, we employed information-theoretic metrics, overcoming the limitations of pairwise correlation analysis approaches. This enables a more comprehensive exploration of higher-order interactions and multiscale intrinsic connectivity networks (ICNs) in the psychotic brain. In this study, we provide converging evidence suggesting that the psychotic brain exhibits states of randomness across both spatial and temporal dimensions. To further investigate these disruptions, we estimated brain network connectivity using redundancy and synergy measures, aiming to assess the integration and segregation of topological information in the psychotic brain. Our findings reveal a disruption in the balance between redundant and synergistic information, a phenomenon we term brainquake in this study, which highlights the instability and disorganization of brain networks in psychosis. Moreover, our exploration of higher-order topological functional connectivity reveals profound disruptions in brain information integration. Aberrant information interactions were observed across both cortical and subcortical ICNs. We specifically identified the most easily affected irregularities in the sensorimotor, visual, temporal, default mode, and fronto-parietal networks, as well as in the hippocampal and amygdalar regions, all of which showed disruptions. These findings underscore the severe impact of psychotic states on multiscale critical brain networks, suggesting a profound alteration in the brain's complexity and organizational states.

Indexed as

BrainPsychotic DisordersAdultBipolar DisorderBrain MappingConnectomeFemaleHumansMagnetic Resonance ImagingMaleNerve NetNeural PathwaysSchizophreniaYoung Adult

Identifiers

PMID41261142
PMCPMC12999491

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.