Evaluation of Module Dynamics in Functional Brain Networks After Stroke

Kaichao Wu, Qiang Fang, Katrina Neville, Beth Jelfs

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publication2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
PublisherIEEE
Number of pages4
ISBN (Electronic)9798350324471
ISBN (Print)9798350324488 (PoD)
DOIs
Publication statusPublished - 11 Dec 2023

Bibliographical note

Acknowledgments:
This work was supported by Li Ka Shing Foundation Cross-Disciplinary Research Grant (2020LKSFG01C).

Keywords

  • Magnetic resonance imaging
  • Stroke (medical condition)
  • Nonhomogeneous media
  • Biology

ASJC Scopus subject areas

  • General Medicine

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