Abnormal network homogeneity of default-mode network and its relationships with clinical symptoms in antipsychotic-naïve first-diagnosis schizophrenia

Abstract

Schizophrenia is a severe mental disorder affecting around 0.5-1% of the global population. A few studies have shown the functional disconnection in the default-mode network (DMN) of schizophrenia patients. However, the findings remain discrepant. In the current study, we compared the intrinsic network organization of DMN of 57 first-diagnosis drug-naïve schizophrenia patients with 50 healthy controls (HCs) using a homogeneity network (NH) and explored the relationships of DMN with clinical characteristics of schizophrenia patients. Receiver operating characteristic (ROC) curves analysis and support vector machine (SVM) analysis were applied to calculate the accuracy of distinguishing schizophrenia patients from HCs. Our results showed that the NH values of patients were significantly higher in the left superior medial frontal gyrus (SMFG) and right cerebellum Crus I/Crus II and significantly lower in the right inferior temporal gyrus (ITG) and bilateral posterior cingulate cortex (PCC) compared to those of HCs. Additionally, negative correlations were shown between aberrant NH values in the right cerebellum Crus I/Crus II and general psychopathology scores, between NH values in the left SMFG and negative symptom scores, and between the NH values in the right ITG and speed of processing. Also, patients' age and the NH values in the right cerebellum Crus I/Crus II and the right ITG were the predictors of performance in the social cognition test. ROC curves analysis and SVM analysis showed that a combination of NH values in the left SMFG, right ITG, and right cerebellum Crus I/Crus II could distinguish schizophrenia patients from HCs with high accuracy. The results emphasized the vital role of DMN in the neuropathological mechanisms underlying schizophrenia.

Keywords: cognitive dysfunction; default-mode network; network homogeneity; resting-state functional magnetic resonance imaging; schizophrenia.

FIGURE 1

The DMN mask was determined using ICA. R and L denote the right and left sides, respectively; DMN, default-mode network; ICA, independent component analysis.

FIGURE 2

Differences in the NH values in the brain regions between patients and HCs. The color of the bars denotes the t-values (two-sample t-tests). Blue and red represent lower and higher NH, respectively. R and L denote the right and left sides, respectively; HCs, healthy controls; NH, network homogeneity.

FIGURE 3

Scatterplots of significant associations between NH values in the SMFG and negative symptom scores (A), NH values in the right cerebellum Crus I/Crus II and general psychopathology scores (B), NH values in the right ITG and speed of processing scores (C), age and social cognition scores (D), NH values in the right cerebellum Crus I/Crus II and social cognition scores (E), NH values in the right ITG and social cognition scores (F), age and attention/vigilance scores (G), and education and reasoning and problem-solving scores (H) in the patient group. SMFG, superior medial frontal gyrus; ITG, inferior temporal gyrus; PANSS, Positive and Negative Syndrome Scale; NH, network homogeneity.

FIGURE 4

Results of the ROC analyses used to differentiate between patients and HCs using the NH values in the different brain regions. NH, network homogeneity; HCs, healthy controls; PCC, posterior cingulate cortex; SMFG, superior medial frontal gyrus; ITG, inferior temporal gyrus; ROC, receiver operating characteristic.

FIGURE 5

Visualization of classification using SVM analysis with the NH values in the combined brain regions, comprising the left SMFG, right cerebellum Crus I/Crus II, and right ITG; (A) confusion matrix; (B) SVM parameter results of 3D view. Target Class and Output Class represent actual and predicted results of classification, respectively; SMFG, superior medial frontal gyrus; ITG, inferior temporal gyrus; NH, network homogeneity; SVM, support vector machine.