Research progresses of brain complex network in schizophrenia based on multimodal MRI
10.13929/j.issn.1003-3289.2020.10.030
- VernacularTitle: 基于多模态MRI精神分裂症脑复杂网络研究进展
- Author:
Lingyin KONG
1
Author Information
1. Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology
- Publication Type:Journal Article
- Keywords:
Magnetic resonance imaging;
Neural networks, computer;
Schizophrenia
- From:
Chinese Journal of Medical Imaging Technology
2020;36(10):1550-1554
- CountryChina
- Language:Chinese
-
Abstract:
Schizophrenia (SZ) is a group of chronic mental disorders, which is often accompanied by perception, thinking, emotion, behavior and other impairments. MRI techniques can be used to investigate brain structural and functional alterations in SZ, so as to provide significant support for the recognition of biomarkers for mental disorders. Structural and functional brain networks in SZ constructed with multimodal MRI have been analyzed by the human brain connectome using graph theory in numerous studies, which highlighted the abnormality of brain complex networks, such as increased shortest path length, decreased clustering coefficient and global efficiency, as well as deficits of global hub, providing further support for the hypothesis of dysconnection in SZ. The recent advancements of structural networks, functional networks and multimodal networks were reviewed, and the characteristics of brain complex networks in SZ were explored, the existing problems of analysis methods and future direction were discussed in this paper.
