Evidence map›Paper›PMID 34220438›Full record

ArticleFrontiers in neuroscience2021

Whole-Brain Functional Network Connectivity Abnormalities in Affective and Non-Affective Early Phase Psychosis.

Zening Fu, Armin Iraji, Jing Sui, Vince D Calhoun

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
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  6. Connectome-based predictive modeling of early and chronic psychosis symptoms.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2025
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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

4 authors.

Zening FuTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.
Armin IrajiTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.
Jing SuiTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.
Vince D CalhounTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.

Funding

Multivariate methods for identifying multitask/multimodal brain imaging biomarkersR01EB006841 · NIBIB · THE MIND RESEARCH NETWORK · PI VINCE D CALHOUN, Sergey Plis · 2007 to 2026
$9.8M
Male/Female differences in psychosis and mood disorders:Dynamic imaging-genomic models for characterizing and predicting psychosis and mood dR01MH118695 · NIMH · GEORGIA STATE UNIVERSITY · PI ADALI, TULAY, CALHOUN, VINCE D · 2019 to 2023
$3.8M
Unified multivariate data-driven solutions for static and dynamic brain connectivityR01EB020407 · NIBIB · THE MIND RESEARCH NETWORK · PI ADALI, TULAY, CALHOUN, VINCE D · 2015 to 2018
$2.7M
Data-driven approaches to identify biomarkers from multimodal imaging big dataR01MH117107 · NIMH · GEORGIA STATE UNIVERSITY · PI CALHOUN, VINCE D · 2019 to 2022
$1.6M
NIBIB NIH HHS R01 EB006841NIBIB NIH HHS R01 EB020407NIMH NIH HHS R01 MH117107NIMH NIH HHS R01 MH118695
6 · The paper itself

Abstract

Psychosis disorders share overlapping symptoms and are characterized by a wide-spread breakdown in functional brain integration. Although neuroimaging studies have identified numerous connectivity abnormalities in affective and non-affective psychoses, whether they have specific or unique connectivity abnormalities, especially within the early stage is still poorly understood. The early phase of psychosis is a critical period with fewer chronic confounds and when treatment intervention may be most effective. In this work, we examined whole-brain functional network connectivity (FNC) from both static and dynamic perspectives in patients with affective psychosis (PAP) or with non-affective psychosis (PnAP) and healthy controls (HCs). A fully automated independent component analysis (ICA) pipeline called "Neuromark" was applied to high-quality functional magnetic resonance imaging (fMRI) data with 113 early-phase psychosis patients (32 PAP and 81 PnAP) and 52 HCs. Relative to the HCs, both psychosis groups showed common abnormalities in static FNC (sFNC) between the thalamus and sensorimotor domain, and between subcortical regions and the cerebellum. PAP had specifically decreased sFNC between the superior temporal gyrus and the paracentral lobule, and between the cerebellum and the middle temporal gyrus/inferior parietal lobule. On the other hand, PnAP showed increased sFNC between the fusiform gyrus and the superior medial frontal gyrus. Dynamic FNC (dFNC) was investigated using a combination of a sliding window approach, clustering analysis, and graph analysis. Three reoccurring brain states were identified, among which both psychosis groups had fewer occurrences in one antagonism state (state 2) and showed decreased network efficiency within an intermediate state (state 1). Compared with HCs and PnAP, PAP also showed a significantly increased number of state transitions, indicating more unstable brain connections in affective psychosis. We further found that the identified connectivity features were associated with the overall positive and negative syndrome scale, an assessment instrument for general psychopathology and positive symptoms. Our findings support the view that subcortical-cortical information processing is disrupted within five years of the initial onset of psychosis and provide new evidence that abnormalities in both static and dynamic connectivity consist of shared and unique features for the early affective and non-affective psychoses.

Indexed as

affective psychosisdynamic functional network connectivity (dFNC)early phase psychosisfunctional network connectivity (FNC)graphic measurenon-affective psychosis

Identifiers

PMID34220438
PMCPMC8250435

What OpenQuestion holds

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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.