ArticleCognitive neurodynamics2020
Variation of functional brain connectivity in epileptic seizures: an EEG analysis with cross-frequency phase synchronization.
Article in Cognitive neurodynamics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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21 citing papers in PubMed, 53 citations in OpenAlex.
- Seizure type classification algorithm based on multi-dimensional brain network feature selection.Fundamental research · 2026Article
- Decoding preparatory movement state-based motor imagery with multi layer energy decoder.Journal of neuroengineering and rehabilitation · 2025Article
- Transition to synchronization in functional brain networks of children suffering from ADHD.Brain structure & function · 2025Article
- Elucidating the Pivotal Neuroprotective Mechanisms and Therapeutic Variants of Erythropoietin in Neonatal Brain Injury.Current topics in medicinal chemistry · 2025Review
- Resting state EEG microstate profiling and a machine-learning based classifier model in epilepsy.Cognitive neurodynamics · 2024Article
- The high frequency oscillations in the amygdala, hippocampus, and temporal cortex during mesial temporal lobe epilepsy.Cognitive neurodynamics · 2024Article
- Classification of the Epileptic Seizure Onset Zone Based on Partial Annotation.Cognitive neurodynamics · 2023Article
- Study on brain damage patterns of COVID-19 patients based on EEG signals.Frontiers in human neuroscience · 2023Article
- A deep learning framework for identifying Alzheimer's disease using fMRI-based brain network.Frontiers in neuroscience · 2023Article
- Epileptic Seizure Detection Using Geometric Features Extracted from SODP Shape of EEG Signals and AsyLnCPSO-GA.Entropy (Basel, Switzerland) · 2022Article
- EEG based functional brain networks analysis in dyslexic children during arithmetic task.Cognitive neurodynamics · 2022Article
- An Explainable Statistical Method for Seizure Prediction Using Brain Functional Connectivity from EEG.Computational intelligence and neuroscience · 2022Article
- Automatic Detection of Epilepsy Based on Entropy Feature Fusion and Convolutional Neural Network.Oxidative medicine and cellular longevity · 2022Article
- Multi-Granularity Analysis of Brain Networks Assembled With Intra-Frequency and Cross-Frequency Phase Coupling for Human EEG After Stroke.Frontiers in computational neuroscience · 2022Article
- Prediction of Epilepsy Based on Tensor Decomposition and Functional Brain Network.Brain sciences · 2021Article
- A novel index of functional connectivity: phase lag based on Wilcoxon signed rank test.Cognitive neurodynamics · 2021Article
- Cross-frequency and iso-frequency estimation of functional corticomuscular coupling after stroke.Cognitive neurodynamics · 2021Article
- Role of joint language control during cross-language communication: evidence from cross-frequency coupling.Cognitive neurodynamics · 2021Article
- Path Planning of Unmanned Autonomous Helicopter Based on Human-Computer Hybrid Augmented Intelligence.Neural plasticity · 2021Article
- Research on Differential Brain Networks before and after WM Training under Different Frequency Band Oscillations.Neural plasticity · 2021Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Frequency coupling in nervous system is believed to be associated with normal and impaired brain functions. However, most of the existing experiments have been concentrated on the coupling strength within frequency bands, while the coupling strength between different bands is ignored. In this work, we apply phase synchronization index (PSI) to investigate the cross-frequency coupling (CFC) of Electroencephalogram (EEG) signals. The PSI matrixes for the multi-channel EEG signals are calculated from interictal to ictal period in each sliding time window. The results show that CFC changes obviously once seizure occurs between the different bands, and such alteration is earlier than the appearance of clinical symptoms in seizure. Considering the similar role of the within-frequency coupling (WFC), we further reconstruct multi-layered brain networks, including CFC networks and WFC networks. The graph metrics are applied to investigate the variation of network structure of the epileptic brain. Significant decreases/increases of the local/global efficiency are found in δ-β, δ-α, θ-α and δ-θ bands from the CFC network, while WFC network shows a significant decline in the local efficiency in θ and α bands. These findings suggest that CFC may provide a new perspective to observe the alteration of brain structure when seizure occurs, and the investigation of functional connectivity across the full frequency spectrum can give us a deeper understanding of epileptic brains.
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