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Multi-channel hierarchy functional integration analysis between large-scale brain networks for migraine: An fMRI
Yuhu Shi1, Weiming Zeng1, Weifang Nie1
1College of Information Engineering, Shanghai Maritime University, Shanghai, China.
Neuroimage. Clinical
|January 5, 2021
Summary
Migraine patients exhibit distinct dynamic functional connectivity patterns in brain networks compared to healthy individuals. These dynamic changes in brain network structure may offer new insights for migraine diagnosis.
Area of Science:
- Neuroscience
- Medical Imaging
- Computational Biology
Background:
- Migraine is a chronic neurological disorder with unclear pathogenesis.
- Functional magnetic resonance imaging (fMRI) is crucial for studying migraine's neural mechanisms.
Purpose of the Study:
- To systematically investigate fMRI functional connectivities (FCs) in migraine patients.
- To compare static and dynamic FCs and network topology between migraineurs and healthy controls.
Main Methods:
- Utilized group independent component analysis to obtain large-scale brain networks.
- Analyzed static and dynamic FCs at group and individual levels.
- Applied graph metrics to identify dynamic FC states and their topological properties.
Main Results:
- Significant differences in dynamic FCs and global topology were found between migraine patients and controls.
- Dynamic functional connectivity patterns in migraineurs showed specificity and consistency across different analysis window-widths.
- Local topological properties and dynamic fluctuations were sensitive to window-width selection.
Conclusions:
- Dynamic changes in brain network FCs and topology are key to migraine's brain functional activity.
- Identified specific dynamic functional connectivity states in migraine patients.
- Findings suggest a new perspective for the clinical diagnosis of migraine.
