Evidence map›Paper›PMID 34647268›Full record

ArticleBrain imaging and behavior2022

Modular-level alterations of single-subject gray matter networks in schizophrenia.

Yuxiang Guo, Yunxiao Ma, GongShu Wang, Ting Li, Tong Wang, Dandan Li, Jie Xiang, Tianyi Yan, Bin Wang, Miaomiao Liu

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Article in Brain imaging and behavior, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

10 authors.

Yuxiang Guo *College of Information and Computer, Taiyuan University of Technology, Taiyuan, China.
Yunxiao Ma *School of Life Science, Beijing Institute of Technology, Beijing, China.
GongShu WangSchool of Life Science, Beijing Institute of Technology, Beijing, China.
Ting LiSchool of Life Science, Beijing Institute of Technology, Beijing, China.
Tong WangCollege of Information and Computer, Taiyuan University of Technology, Taiyuan, China.
Dandan LiCollege of Information and Computer, Taiyuan University of Technology, Taiyuan, China.
Jie XiangCollege of Information and Computer, Taiyuan University of Technology, Taiyuan, China.
Tianyi YanSchool of Life Science, Beijing Institute of Technology, Beijing, China.
Bin WangCollege of Information and Computer, Taiyuan University of Technology, Taiyuan, China. wangbin01@tyut.edu.cn.ORCID http://orcid.org/0000-0001-7771-5360
Miaomiao LiuGraduate School of Natural Science and Technology, Okayama University, Okayama, Japan. byo_byo@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Schizophrenia is often regarded as a psychiatric disorder caused by disrupted connections in the brain. Evidence suggests that the gray matter of schizophrenia patients is damaged in a modular pattern. Recently, abnormal topological organization was observed in the gray matter networks of patients with schizophrenia. However, the modular-level alteration of gray matter networks in schizophrenia remains unclear. In this study, single-subject gray matter networks were constructed for a total of 217 subjects (116 patients with schizophrenia and 101 controls). We analyzed the topological characteristics of the brain network and the strengths of connections between and within modules. Compared with the outcomes in the control group, the global efficiency and participation coefficient values of the single-subject gray matter networks in schizophrenic patients were significantly reduced. The nodal participation coefficient of the regions involving the frontoparietal attention network, default mode network and subcortical network were significantly decreased in subjects with schizophrenia. The intermodule connections between the frontoparietal attention network and visual network and between the default mode network and subcortical network, in the frontoparietal attention network were significantly reduced in the patient group. In the frontoparietal attention network, the intramodule nodal connection strength of the left orbital inferior frontal gyrus and right inferior parietal gyrus was significantly decreased in schizophrenia patients. Reduced intermodule nodal connection strength between the frontoparietal attention network and visual network was associated with the severity of schizophrenia symptoms. These findings suggest that abnormal intramodule and intermodule connections in the structural brain network may a biomarker of schizophrenia symptoms.

Indexed as

Gray MatterSchizophreniaBrainCerebral CortexHumansMagnetic Resonance ImagingConnectionModularitySchizophreniaStrengthStructural network

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.