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

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

doi:10.3389/fnins.2021.682110

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.

Highlights

Ranked as the third most disabling condition after quadriplegia and dementia, psychosis is characterized as severer disruptions to the information processing in the brain that affect people’s thoughts and perceptions (Amador and David, 1999; Arciniegas, 2015)
We examined the topologic measures in early psychosis transiently within each dynamic functional network connectivity (dFNC) state and found significantly disrupted functional integration in brain networks
A similar dFNC state with median connectivity strength and network efficiency was identified with reduced local efficiency in schizophrenia (Fu et al, 2021). Our results extend this finding by showing that the loss of transiently local efficiency in both affective and non-affective psychosis, during the initial onset of psychotic symptoms

Summary

Introduction

Ranked as the third most disabling condition after quadriplegia and dementia, psychosis is characterized as severer disruptions to the information processing in the brain that affect people’s thoughts and perceptions (Amador and David, 1999; Arciniegas, 2015). Over the past decade, growing evidence has shown that psychosis is associated with disruptions of the coordinated functioning of distributed brain regions (Friston, 1998, 1999; Canuet et al, 2011; Khadka et al, 2013). Such functional disconnections are typically investigated by measuring functional connectivity (i.e., temporal coherence) between fluctuations in low-frequency blood oxygen leveldependent (BOLD) signal in resting-state functional magnetic imaging (rs-fMRI) data (Dandash et al, 2014; Palaniyappan and Liddle, 2014; Satterthwaite and Baker, 2015). Functional abnormalities have been identified in multiple brain systems involving default mode, subcortical, cerebellar, and sensorimotor networks (Mamah et al, 2013; Baker et al, 2014; Palaniyappan and Liddle, 2014; Wang et al, 2020)

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