Epileptogenic Zone Location of Temporal Lobe Epilepsy by Cross-Frequency Coupling Analysis

Liu, Xiaotong; Han, Fang; Fu, Rui; Wang, Qingyun; Luan, Guoming

doi:10.3389/fneur.2021.764821

Cited by 11 publications

(12 citation statements)

References 35 publications

(44 reference statements)

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“…The PAC is commonly used to localize the epileptic tissue ( Weiss et al, 2015 ; Liu et al, 2021 ), but the coupled phase of LFO in PAC is seldom used due to the complexity of the pattern. The proposed CV-PAC contains both the coupling strengths and the coupled phases.…”

Section: Discussionmentioning

confidence: 99%

“…Some studies focused on the PAC in either LFO-gamma (30–80 Hz) or LFO-HFO (

80) ( Amiri et al, 2016 ; Liu et al, 2021 ). Our result shows that the AUC values scored only .80 and .84 when using CV-PAC of LFO-gamma (30–80 Hz) and LFO-HFO (80–160 Hz), respectively.…”

Section: Discussionmentioning

confidence: 99%

“…Stereo-electroencephalography (SEEG) is one kind of iEEG and is widely used to study the spatiotemporal oscillatory dynamics of brain networks engaged in epileptogenic processes ( Bartolomei et al, 2017 ). Some EEG features provide promise biomarkers for EZ, such as phase-amplitude coupling (PAC) ( Weiss et al, 2015 ; Amiri et al, 2016 ; Jiang et al, 2019 ; Liu et al, 2021 ), and high-frequency oscillations ( Worrell and Gotman, 2011 ). Currently, there is still a gap between those studies and their applications in the clinical setting.…”

Section: Introductionmentioning

confidence: 99%

“…The PAC in the inter- and pre-seizure periods was weak and paroxysmal, and strong PAC channels were confined more to the SOZ and resection region ( Ma et al, 2021 ). The theta—gamma PAC within the electrodes in the seizure region increased during the ictal period ( Liu et al, 2021 ). In Parkinson’s disease, the HFO (100–300 Hz) was found modulated by beta (13–30 Hz), and beta and gamma amplitudes were further modulated by their low-frequency components ( Jin et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Classifying epileptic phase-amplitude coupling in SEEG using complex-valued convolutional neural network

Liu²,

Wang³

et al. 2023

Front. Physiol.

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EEG phase-amplitude coupling (PAC), the amplitude of high-frequency oscillations modulated by the phase of low-frequency oscillations (LFOs), is a useful biomarker to localize epileptogenic tissue. It is commonly represented in a comodulogram of coupling strength but without coupled phase information. The phase-amplitude coupling is also found in the normal brain, and it is difficult to discriminate pathological phase-amplitude couplings from normal ones. This study proposes a novel approach based on complex-valued phase-amplitude coupling (CV-PAC) for classifying epileptic phase-amplitude coupling. The CV-PAC combines both the coupling strengths and the coupled phases of low-frequency oscillations. The complex-valued convolutional neural network (CV-CNN) is then used to classify epileptic CV-PAC. Stereo-electroencephalography (SEEG) recordings from nine intractable epilepsy patients were analyzed. The leave-one-out cross-validation is performed, and the area-under-curve (AUC) value is used as the indicator of the performance of different measures. Our result shows that the area-under-curve value is .92 for classifying epileptic CV-PAC using CV-CNN. The area-under-curve value decreases to .89, .80, and .88 while using traditional convolutional neural networks, support vector machine, and random forest, respectively. The phases of delta (1–4 Hz) and alpha (8–10 Hz) bands are different between epileptic and normal CV-PAC. The phase information of CV-PAC is important for improving classification performance. The proposed approach of CV-PAC/CV-CNN promises to identify more accurate epileptic brain activities for potential surgical intervention.

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Section: Discussionmentioning

confidence: 99%

“…Some studies focused on the PAC in either LFO-gamma (30–80 Hz) or LFO-HFO (

80) ( Amiri et al, 2016 ; Liu et al, 2021 ). Our result shows that the AUC values scored only .80 and .84 when using CV-PAC of LFO-gamma (30–80 Hz) and LFO-HFO (80–160 Hz), respectively.…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Classifying epileptic phase-amplitude coupling in SEEG using complex-valued convolutional neural network

Liu²,

Wang³

et al. 2023

Front. Physiol.

View full text Add to dashboard Cite

show abstract

“…In another study, Ca ´mpora et al (2019) found that higher PAC exists in the SOZ than in the brain region far from Besides, Ma et al (2021) illustrated that PAC of intracranial EEG during the inter-and pre-seizure stage can provide an accurate reference for epileptogenic zone localization. Liu et al (2021) found increased theta-gamma PAC in the seizure region at the ictal state. Nevertheless, there is a lack of comprehensive consideration for the PAC of interictal ECoG among wider frequency bands, especially in the fast ripple band, which is one emphasis of our research.…”

Section: Introductionmentioning

confidence: 87%

Seizure onset zone identification using phase-amplitude coupling and multiple machine learning approaches for interictal electrocorticogram

et al. 2022

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Automatic seizure onset zone (SOZ) localization using interictal electrocorticogram (ECoG) improves the diagnosis and treatment of patients with medically refractory epilepsy. This study aimed to investigate the characteristics of phase-amplitude coupling (PAC) extracted from interictal ECoG and the feasibility of PAC serving as a promising biomarker for SOZ identification. We employed the mean vector length modulation index approach on the 20-s ECoG window to calculate PAC features between low-frequency rhythms (0.5–24 Hz) and high frequency oscillations (HFOs) (80–560 Hz). We used statistical measures to test the significant difference in PAC between the SOZ and non-seizure onset zone (NSOZ). To overcome the drawback of handcraft feature engineering, we established novel machine learning models to learn automatically the characteristics of the obtained PAC features and classify them to identify the SOZ. Besides, to handle imbalanced dataset classification, we introduced novel feature-wise/class-wise re-weighting strategies in conjunction with classifiers. In addition, we proposed a time-series nest cross-validation to provide more accurate and unbiased evaluations for this model. Seven patients with focal cortical dysplasia were included in this study. The experiment results not only showed that a significant coupling at band pairs of slow waves and HFOs exists in the SOZ when compared with the NSOZ, but also indicated the effectiveness of the PAC features and the proposed models in achieving better classification performance .

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Deep-learning-optimized microstate network analysis for early Parkinson’s disease with mild cognitive impairment

Zhang,

Shen,

Chu

et al. 2024

Cogn Neurodyn

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Epileptogenic Zone Location of Temporal Lobe Epilepsy by Cross-Frequency Coupling Analysis

Cited by 11 publications

References 35 publications

Classifying epileptic phase-amplitude coupling in SEEG using complex-valued convolutional neural network

Classifying epileptic phase-amplitude coupling in SEEG using complex-valued convolutional neural network

Seizure onset zone identification using phase-amplitude coupling and multiple machine learning approaches for interictal electrocorticogram

Deep-learning-optimized microstate network analysis for early Parkinson’s disease with mild cognitive impairment

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