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Objective: The symptom-related neurobiology characteristic of schizophrenia in the brain from a network perspective is still poorly understood, leading to a lack of potential biologically-based markers and difficulty identifying therapeutic targets. We aim to test the dysregulated cross-network interactions among the Salience Network (SN), Central Executive Network (CEN) and Default Mode Network (DMN) and how they contributed to different symptoms in schizophrenia patients.Methods: We examined network interactions among the SN, CEN and DMN in 76 patients with schizophrenia vs. 80 well-matched controls using dynamic causal modeling (DCM). We further analyzed the relation between network dynamics and Positive and Negative Syndrome Scale (PANSS).Results: We observed that the DMN, CEN and SN across healthy controls and schizophrenia patients showed several similarities within or between-network pattern in the resting state. Comparing schizophrenia to controls, SN-centered cross-network interactions were most significantly reduced. Crucially, the strength of connections from CEN subnetwork 1 to DMN subnetwork 1 was positively correlated with the Positive Score of PANSS. The connection from the DMN subnetwork 2 to CEN subnetwork 2 was negatively correlated with the Negative Score of PANSS.Conclusions: Our study provides strong evidence for the dysregulation among SN, CEN and DMN in a triple-network perspective in schizophrenia. The connection between DMN and CEN could be clinically-relevant neurobiological signature of schizophrenia symptoms. Our study indicated that the description of brain triple network hypothesis could be a novel and possible bio-marker for schizophrenia. [ABSTRACT FROM AUTHOR]

Objective: We aimed to evaluate the functional network properties in first-episode schizophrenia (SZ) patients at baseline and after 4-months treatment with second-generation antipsychotic drugs.Methods: Resting-state functional magnetic resonance imaging and graph theory approaches were utilized to evaluate the functional integration and segregation of brain networks in 36 first-episode patients (20 male/16 female) with SZ and 36 age and sex matched healthy controls (20 male/16 female).Results: Compared with healthy controls, SZ at baseline showed lower clustering coefficient (Cp) and local network efficiency (Eloc), and this abnormal pattern was modulated with treatment of antipsychotic drugs at follow-up. Longitudinally, the increase of Cp was associated with the improvement of negative symptom. We found that the strength of functional connectivity between brain regions were significantly increased in three connections after treatment, mainly involving the frontal, parietal and occipital lobes.Conclusion: The current study suggested that antipsychotic drugs could modulate the faulty local clustering of the functional connectome in SZ. Furthermore, Cp, the parameter that reflects local clustering of topological organization, demonstrated the potential to be a connectome-based biomarker of treatment response to second-generation antipsychotics in patients with SZ. [ABSTRACT FROM AUTHOR]

Background: Recent progress in neuroscience research has provided evidence that schizophrenia is a disease that involves dysconnectivity of brain networks. Widespread gray matter loss was commonly observed but how these gray matter abnormalities are characterized at the large-scale network-level in schizophrenia, especially patients with first-episode (FE-SCZ) remains unclear.Methods: In this study, gray matter structural network aberrations were investigated by applying structural covariance network analysis to 193 first episode schizophrenia patients and 178 age and gender-matched healthy controls (HCs). The mean gray matter volume in seed regions relating to eight specific networks (visual, auditory, sensorimotor, speech, semantic, default-mode, executive control, and salience) were extracted, and voxel-wise analyses of covariance were conducted to compare the association between whole-brain gray matter volume and each seed region for FE-SCZ and HCs.Results: The auditory network was less extended in FE-SCZ compared with HCs, with a significant decrease in the structural association between the Hesch's gyrus and the middle frontal gyrus and the superior frontal gyrus. Hyperconnectivity was observed in executive control network with a significant increase in the structural association between the dorsal lateral prefrontal cortex and the superior frontal gyrus and supplementary motor area.Conclusion: Our research shows that seed based structural covariance analysis can well characterize multiple large-scale networks, the observed changes might underly the hallucinations and cognitive impairments observed in FE-SCZ. Given that these patients were experiencing their first episode of schizophrenia, our findings suggest that such structural network deficits are present at an early stage in this disorder. [ABSTRACT FROM AUTHOR]

Objective: Auditory verbal hallucinations (AVHs) are one of the cardinal symptoms of schizophrenia (SZ). Cerebral dysfunction may represent pathophysiological underpinnings behind AVHs in SZ. However, regional and network functional deficits for AVHs in SZ remain to be identified. Methods: Seventeen medication-naïve first-episode SZ patients with AVHs, 15 without AVHs, and 19 healthy controls (HCs) were studied using resting-state functional magnetic resonance imaging. We compared the amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) among these subjects. Areas with both ALFF and ReHo alterations were used as seeds in functional connectivity (FC) analysis. Then we performed correlation analysis between image measures and symptoms and receiver operating characteristic analysis. Results: One-way analysis of variance showed significant differences of ALFF and ReHo in the bilateral putamen, thereby being used as seeds. SZ patients with AVHs showed decreased ALFF in the left putamen, increased ReHo in the right dorsolateral prefrontal cortex (DLPFC), and increased right putamen-seeded FC with the left DLPFC and Broca's area relative to those without AVHs. Furthermore, the increased strength of the connectivity between the right putamen and left Broca's area correlated with the severity of SZ symptoms. Both patient groups demonstrated hypoconnectivity within frontal/parietal/temporal cortico-striatal-cerebellar networks compared with HCs. Conclusion: AVHs in SZ may be caused by abnormal regional function in the putamen and prefrontal cortex, as well as hyperconnectivity between them. The putamen-related regional and network functional deficits may reflect imbalance in neuromodulation of AVHs in SZ. Furthermore, dysconnectivity within cortico-striatal-cerebellar networks might subserve the pathogenesis of SZ. [ABSTRACT FROM AUTHOR]