Evidence map›Paper›PMID 39868241›Full record

ArticlebioRxiv : the preprint server for biology2025

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 readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

7 authors.

Qiang LiTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA 30303, United States.ORCID 0000-0002-5337-0676
Jingyu LiuTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA 30303, United States.
Godfrey D PearlsonDepartments of Psychiatry and Neurobiology, Yale University, New Haven, CT 06511, United States.
Jiayu ChenTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA 30303, United States.
Yu-Ping WangDepartment of Biomedical Engineering, Tulane University, New Orleans, LA 70118, United States.
Jessica A TurnerWexnar Medical Center, Department of Psychiatry and Behavioral Health, Ohio State University, Columbus, OH 43210, United States.
Vince D CalhounTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, and Emory University, Atlanta, GA 30303, United States.ORCID 0000-0001-9058-0747

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
NIMH NIH HHS R01 MH119251NIMH NIH HHS R01 MH123610
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

Indexed as

High-Order InteractionsPsychotic BrainRandomnessRedundant and Synergistic InformationSpatiotemporal Complexity Measures

Identifiers

PMID39868241
PMCPMC11761638

What OpenQuestion holds

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LicenceCC BY-NC
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.