Affiliation:
1. School of Biological Science and Medical Engineering Beihang University Beijing China
2. Beijing Advanced Innovation Centre for Big Data‐Based Precision Medicine Beihang University Beijing China
3. Beijing Advanced Innovation Centre for Biomedical Engineering Beihang University Beijing China
4. Department of Neurology, Xuanwu Hospital Capital Medical University Beijing China
5. Brain Functional Disease and Neuromodulation of Beijing Key Laboratory Beijing China
6. Hefei Innovation Research Institute, Beihang University Hefei Anhui China
Abstract
AbstractObjectiveTo explore the association between high‐frequency oscillations (HFOs) and epilepsy types and to improve the accuracy of source localization.MethodsMagnetoencephalography (MEG) ripples of 63 drug‐resistant epilepsy patients were detected. Ripple rates, distribution, spatial complexity, and the clustering coefficient of ripple channels were used for the preliminary classification of lateral temporal lobe epilepsy (LTLE), mesial temporal lobe epilepsy (MTLE), and nontemporal lobe epilepsy (NTLE), mainly frontal lobe epilepsy (FLE). Furthermore, the seizure site identification was improved using the Tucker LCMV method and source‐level betweenness centrality.ResultsRipple rates were significantly higher in MTLE than in LTLE and NTLE (p < 0.05). The LTLE and MTLE were mainly distributed in the temporal lobe, followed by the parietal lobe, occipital lobe, and frontal lobe, whereas MTLE ripples were mainly distributed in the frontal lobe, then parietal lobe and occipital lobe. Nevertheless, the NTLE ripples were primarily in the frontal lobe and partially in the occipital lobe (p < 0.05). Meanwhile, the spatial complexity of NTLE was significantly higher than that of LTLE and MTLE and was lowest in MTLE (p < 0.01). However, an opposite trend was observed for the standardized clustering coefficient compared with spatial complexity (p < 0.01). Finally, the tucker algorithm showed a higher percentage of ripples at the surgical site when the betweenness centrality was added (p < 0.01).ConclusionThis study demonstrated that HFO rates, distribution, spatial complexity, and clustering coefficient of ripple channels varied considerably among the three epilepsy types. Additionally, tucker MEG estimation combined with ripple rates based on the source‐level functional connectivity is a promising approach for presurgical epilepsy evaluation.
Subject
Pharmacology (medical),Physiology (medical),Psychiatry and Mental health,Pharmacology
Cited by
3 articles.
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