Evaluation of Module Dynamics in Functional Brain Networks After Stroke

被引:5
作者
Wu, Kaichao [1 ,2 ]
Fang, Qiang [1 ]
Neville, Katrina [2 ]
Jelfs, Beth [3 ]
机构
[1] Shantou Univ, Dept Biomed Engn, Coll Engn, Shantou, Peoples R China
[2] RMIT Univ, Sch Engn, Melbourne, Vic, Australia
[3] Univ Birmingham, Dept Elect Elect & Syst Engn, Birmingham, W Midlands, England
来源
2023 45TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY, EMBC | 2023年
关键词
COMMUNITY STRUCTURE; CONNECTIVITY; MODULARITY;
D O I
10.1109/EMBC40787.2023.10340633
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The brain's functional network can be analyzed as a set of distributed functional modules. Previous studies using the static method suggested the modularity of the brain function network decreased due to stroke; however, how the modular network changes after stroke, particularly over time, is far from understood. This study collected resting-state functional MRI data from 15 stroke patients and 15 age-matched healthy controls. The patients exhibit distinct clinical symptoms, presenting in mild (n = 6) and severe (n = 9) subgroups. By using a multilayer network model, a dynamic modular structure was detected and corresponding interaction measurements were calculated. The results demonstrated that the module structure and interaction had changed following the stroke. Importantly, the significant differences in dynamic interaction measures demonstrated that the module interaction alterations were not independent of the initial degree of clinical severity. Mild patients were observed to have a significantly lower between-module interaction than severe patients as well as healthy controls. In contrast, severe patients showed remarkably lower within-module interaction and had a reduced overall interaction compared to healthy controls. These findings contributed to the development of post-stroke dynamics analysis and shed new light on brain network interaction for stroke patients. Clinical relevance- Dynamic module interaction analysis underpins the post-stroke functional plasticity and reorganization, and may enable new insight into rehabilitation strategies to promote recovery of function.
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页数:4
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