» Articles » PMID: 34220438

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

Overview
Journal Front Neurosci
Date 2021 Jul 5
PMID 34220438
Citations 13
Authors
Affiliations
Soon will be listed here.
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.

Citing Articles

Building Multivariate Molecular Imaging Brain Atlases Using the NeuroMark PET Independent Component Analysis Framework.

Eierud C, Norgaard M, Bilgel M, Petropoulos H, Fu Z, Iraji A bioRxiv. 2025; .

PMID: 40027837 PMC: 11870563. DOI: 10.1101/2025.02.18.638362.


Connectome-based predictive modeling of early and chronic psychosis symptoms.

Foster M, Ye J, Powers A, Dvornek N, Scheinost D Neuropsychopharmacology. 2025; .

PMID: 40016363 DOI: 10.1038/s41386-025-02064-9.


Time-Varying Spatial Propagation of Brain Networks in fMRI Data.

Bostami B, Lewis N, Agcaoglu O, Turner J, van Erp T, Ford J Hum Brain Mapp. 2025; 46(2):e70131.

PMID: 39835629 PMC: 11747993. DOI: 10.1002/hbm.70131.


Functional dysconnectivity of visual and somatomotor networks yields a simple and robust biomarker for psychosis.

Keane B, Abrham Y, Cole M, Johnson B, Hu B, Cocuzza C Mol Psychiatry. 2024; .

PMID: 39367056 DOI: 10.1038/s41380-024-02767-3.


Addressing Inconsistency in Functional Neuroimaging: A Replicable Data-Driven Multi-Scale Functional Atlas for Canonical Brain Networks.

Jensen K, Turner J, Uddin L, Calhoun V, Iraji A bioRxiv. 2024; .

PMID: 39314443 PMC: 11419112. DOI: 10.1101/2024.09.09.612129.


References
1.
Yu R, Hsieh M, Wang H, Liu C, Liu C, Hwang T . Frequency dependent alterations in regional homogeneity of baseline brain activity in schizophrenia. PLoS One. 2013; 8(3):e57516. PMC: 3590274. DOI: 10.1371/journal.pone.0057516. View

2.
Allen E, Damaraju E, Eichele T, Wu L, Calhoun V . EEG Signatures of Dynamic Functional Network Connectivity States. Brain Topogr. 2017; 31(1):101-116. PMC: 5568463. DOI: 10.1007/s10548-017-0546-2. View

3.
Mamah D, Barch D, Repovs G . Resting state functional connectivity of five neural networks in bipolar disorder and schizophrenia. J Affect Disord. 2013; 150(2):601-9. PMC: 3749249. DOI: 10.1016/j.jad.2013.01.051. View

4.
Dandash O, Fornito A, Lee J, Keefe R, Chee M, Adcock R . Altered striatal functional connectivity in subjects with an at-risk mental state for psychosis. Schizophr Bull. 2013; 40(4):904-13. PMC: 4059431. DOI: 10.1093/schbul/sbt093. View

5.
Pavuluri M, Passarotti A . Neural bases of emotional processing in pediatric bipolar disorder. Expert Rev Neurother. 2008; 8(9):1381-7. DOI: 10.1586/14737175.8.9.1381. View