Volume 14, Issue 3 (May & Jun- In Press 2023)                   BCN 2023, 14(3): 0-0 | Back to browse issues page

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1- Post-Doctoral Research Fellow, School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
2- M.Sc. Student of Neurosciences, Department of Health Sciences and Technology (D-HEST), ETH Zürich, Zürich, Switzerland.
3- Associate Professor, Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran.
Schizophrenia (SZ) is a chronic brain disorder characterized by diverse cognitive dysfunctions due to abnormal brain connectivity. Evaluating these connectivity alterations between and within such networks (intra- and inter connectivity) may improve the understanding of disrupted information processing patterns in SZ patients. For this reason, resting-state fMRI analysis was performed on 24 SZ patients and 27 matched healthy controls. A functional connectivity matrix was constructed for each participant based on 129 gray matter regions. All regions were classified into eight distinct functional networks. Afterwards, all functional connections were segregated into inter- and intra-network connections considering the eight networks. The mean values of connectivity weights and nodal strength were examined for within-and between-network connections in SZ patients and healthy controls. This analysis revealed that the within-network connections in the somatomotor network were significantly reduced (p-value<0.001) in SZ patients. Additionally, intra-network connections within the visual and the ventral attention networks were proven to be significantly lower (p-value<0.01) in the SZ group. Moreover, disrupted intra-network connectivity was detected between the following network pairs: the visual-limbic, the somatomotor-limbic, the dorsal attention-limbic, and the ventral attention-dorsal attention system. Overall, an extensive reduction in functional connectivity strength for SZ patients was illustrated, with a particularly significant decrease in intra-network connections when compared to the inter-networks. These findings can impact the understanding of the important dysregulated connections that are implicated in the incidence of Schizophrenia.
Type of Study: Original | Subject: Clinical Neuroscience
Received: 2022/01/10 | Accepted: 2022/02/27 | Published: 2023/05/8

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