ArticleFrontiers in computational neuroscience2022
Multi-Granularity Analysis of Brain Networks Assembled With Intra-Frequency and Cross-Frequency Phase Coupling for Human EEG After Stroke.
Article in Frontiers in computational neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Microstate-Specific Cross-Frequency Coupling Networks: A Spatiotemporal Framework for MCI Identification.CNS neuroscience & therapeutics · 2026Article
- Neural oscillation mechanisms of repetitive subconcussive impacts: a network study of microstate-specific cross-frequency coupling.The journal of headache and pain · 2025Article
- Time-frequency-space transformer EEG decoding for spinal cord injury.Cognitive neurodynamics · 2024Article
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7 authors.
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Abstract
Evaluating the impact of stroke on the human brain based on electroencephalogram (EEG) remains a challenging problem. Previous studies are mainly analyzed within frequency bands. This article proposes a multi-granularity analysis framework, which uses multiple brain networks assembled with intra-frequency and cross-frequency phase-phase coupling to evaluate the stroke impact in temporal and spatial granularity. Through our experiments on the EEG data of 11 patients with left ischemic stroke and 11 healthy controls during the mental rotation task, we find that the brain information interaction is highly affected after stroke, especially in delta-related cross-frequency bands, such as delta-alpha, delta-low beta, and delta-high beta. Besides, the average phase synchronization index (PSI) of the right hemisphere between patients with stroke and controls has a significant difference, especially in delta-alpha (
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