Functional Integration and Segregation in a Multilayer Network Model of Patients with Schizophrenia.

Jing Wei,Arezo Osmani,Jie Xiang,Qianshan Wang,Bin Wang,Xiaoyue Wang,Xiaohong Cui,Yan Niu,Jiayue Xue

doi:10.3390/brainsci12030368

Jing Wei, Arezo Osmani + Show 7 more

Open Access

https://doi.org/10.3390/brainsci12030368

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Abstract

Research has shown that abnormal brain networks in patients with schizophrenia appear at different frequencies, but the relationship between these different frequencies is unclear. Therefore, it is necessary to use a multilayer network model to evaluate the integration of information from different frequency bands. To explore the mechanism of integration and separation in the multilayer network of schizophrenia, we constructed multilayer frequency brain network models in 50 patients with schizophrenia and 69 healthy subjects, and the entropy of the multiplex degree (EMD) and multilayer clustering coefficient (MCC) were calculated. The results showed that the ability to integrate and separate information in the multilayer network of patients was significantly higher than that of normal people. This difference was mainly reflected in the default mode network, sensorimotor network, subcortical network, and visual network. Among them, the subcortical network was different in both MCC and EMD outcomes. Furthermore, differences were found in the posterior cingulate gyrus, hippocampus, amygdala, putamen, pallidum, and thalamus. The thalamus and posterior cingulate gyrus were associated with the patient’s symptom scores. Our results showed that the cross-frequency interaction ability of patients with schizophrenia was significantly enhanced, among which the subcortical network was the most active. This interaction may serve as a compensation mechanism for intralayer dysfunction.

Highlights

Schizophrenia is a common chronic and disabling mental disorder, its neural basis remains unclear
By comparing the average entropy of the multiplex degree (EMD) and multilayer clustering coefficient (MCC), we found that the EMD was significantly different in the default mode network (DMN) (t(90) = −9.002, p(FDR) = 0.000), sensorimotor network (t(90) = −14.451, p(FDR) = 0.000), visual network (t(90) = −3.989, p(FDR) = 0.000), and subcortical network (t(90) = −25.364, p(FDR) = 0.000)
The results showed that the trends of information interaction and cross-layer formation of local triangles in the multilayer frequency brain network of patients with schizophrenia were significantly enhanced compared with those of healthy controls

Summary

Introduction

Schizophrenia is a common chronic and disabling mental disorder, its neural basis remains unclear. Relevant studies have shown that schizophrenia is a typical complex mental disorder with abnormal connections in the whole brain, and its underlying neuropathology is related to the abnormal functional coordination of multiple brain regions in patients [1]. Brain activity is frequency-specific, and different physiological activities produce frequency-specific signals [2,3]. Recent research has found that brain network differences in schizophrenia occur at different frequencies [4]. Researchers found that schizophrenia patients showed a wide range of frequency band-specific differences in low-frequency amplitude and regional consistency [5]. Moran et al pointed out that the study of intraband or interband interactions at specific frequencies plays an important role in the study of schizophrenia [8]

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