Increased Excursions to Functional Networks in Schizophrenia in the Absence of Task.

Miguel Farinha,Conceição Amado,Joana Cabral,Pedro Morgado

doi:10.3389/fnins.2022.821179

Miguel Farinha, Conceição Amado + Show 2 more

Open Access

https://doi.org/10.3389/fnins.2022.821179

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Abstract

Schizophrenia is a chronic psychotic disorder characterized by the disruption of thought processes, perception, cognition, and behaviors, for which there is still a lack of objective and quantitative biomarkers in brain activity. Using functional magnetic resonance imaging (fMRI) data from an open-source database, this study investigated differences between the dynamic exploration of resting-state networks in 71 schizophrenia patients and 74 healthy controls. Focusing on recurrent states of phase coherence in fMRI signals, brain activity was examined for intergroup differences through the lens of dynamical systems theory. Results showed reduced fractional occupancy and dwell time of a globally synchronized state in schizophrenia. Conversely, patients exhibited increased fractional occupancy, dwell time and limiting probability of being in states during which canonical functional networks—i.e., Limbic, Dorsal Attention and Somatomotor—synchronized in anti-phase with respect to the rest of the brain. In terms of state-to-state transitions, patients exhibited increased probability of switching to Limbic, Somatomotor and Visual networks, and reduced probability of remaining in states related to the Default Mode network, the Orbitofrontal network and the globally synchronized state. All results revealed medium to large effect sizes. Combined, these findings expose pronounced differences in the temporal expression of resting-state networks in schizophrenia patients, which may relate to the pathophysiology of this disorder. Overall, these results reinforce the utility of dynamical systems theory to extend current knowledge regarding disrupted brain dynamics in psychiatric disorders.

Highlights

Brain activity at “rest” captured using functional magnetic resonance imaging reveals the recurrent emergence and dissolution of connectivity patterns that overlap with functional networks typically activated during task (Beckmann et al, 2005; Fox and Raichle, 2007; Smith et al, 2009; Deco and Jirsa, 2012)
Neuroimaging studies suggest that SZ patients have aberrant functional connectivity in brain networks and these abnormalities are related to disease symptoms (Wang et al, 2014)
The collection of clustering solutions was investigated to search for FC states whose fractional occupancy and dwell time most significantly and consistently differed between SZ patients and

Summary

Introduction

Brain activity at “rest” captured using functional magnetic resonance imaging (fMRI) reveals the recurrent emergence and dissolution of connectivity patterns that overlap with functional networks typically activated during task (Beckmann et al, 2005; Fox and Raichle, 2007; Smith et al, 2009; Deco and Jirsa, 2012). These resting-state networks (RSNs) have been consistently detected and extensively analyzed across neuroimaging studies (Damoiseaux et al, 2006; van den Heuvel and Hulshoff Pol, 2010) and their characterization in the temporal domain—referred to as dynamic. As such, neuroimaging data-sharing initiatives have been developed to potentiate the discovery of biomarkers of schizophrenia in fMRI signals, allowing to test novel analysis methods which may provide further insights into the pathophysiology of this disease and, potentially, lead to the discovery of new treatments for the diseased brain (Aine et al, 2017)

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