FAPEX: Fractional Amplitude-Phase Expressor for Robust Cross-Subject Seizure Prediction
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866917061489328128 |
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| author | Zheng, Ruizhe Mao, Lingyan Han, Dingding Luo, Tian Wang, Yi Ding, Jing Yu, Yuguo |
| author_facet | Zheng, Ruizhe Mao, Lingyan Han, Dingding Luo, Tian Wang, Yi Ding, Jing Yu, Yuguo |
| contents | Precise, generalizable subject-agnostic seizure prediction (SASP) remains a fundamental challenge due to the intrinsic complexity and significant spectral variability of electrophysiological signals across individuals and recording modalities. We propose FAPEX, a novel architecture that introduces a learnable fractional neural frame operator (FrNFO) for adaptive time-frequency decomposition. Unlike conventional models that exhibit spectral bias toward low frequencies, our FrNFO employs fractional-order convolutions to capture both high and low-frequency dynamics, achieving approximately 10% improvement in F1-score and sensitivity over state-of-the-art baselines. The FrNFO enables the extraction of instantaneous phase and amplitude representations that are particularly informative for preictal biomarker discovery and enhance out-of-distribution generalization. FAPEX further integrates structural state-space modeling and channelwise attention, allowing it to handle heterogeneous electrode montages. Evaluated across 12 benchmarks spanning species (human, rat, dog, macaque) and modalities (Scalp-EEG, SEEG, ECoG, LFP), FAPEX consistently outperforms 23 supervised and 10 self-supervised baselines under nested cross-validation, with gains of up to 15% in sensitivity on complex cross-domain scenarios. It further demonstrates superior performance in several external validation cohorts. To our knowledge, these establish FAPEX as the first epilepsy model to show consistent superiority in SASP, offering a promising solution for discovering epileptic biomarker evidence supporting the existence of a distinct and identifiable preictal state and clinical translation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_03263 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | FAPEX: Fractional Amplitude-Phase Expressor for Robust Cross-Subject Seizure Prediction Zheng, Ruizhe Mao, Lingyan Han, Dingding Luo, Tian Wang, Yi Ding, Jing Yu, Yuguo Neurons and Cognition Signal Processing Precise, generalizable subject-agnostic seizure prediction (SASP) remains a fundamental challenge due to the intrinsic complexity and significant spectral variability of electrophysiological signals across individuals and recording modalities. We propose FAPEX, a novel architecture that introduces a learnable fractional neural frame operator (FrNFO) for adaptive time-frequency decomposition. Unlike conventional models that exhibit spectral bias toward low frequencies, our FrNFO employs fractional-order convolutions to capture both high and low-frequency dynamics, achieving approximately 10% improvement in F1-score and sensitivity over state-of-the-art baselines. The FrNFO enables the extraction of instantaneous phase and amplitude representations that are particularly informative for preictal biomarker discovery and enhance out-of-distribution generalization. FAPEX further integrates structural state-space modeling and channelwise attention, allowing it to handle heterogeneous electrode montages. Evaluated across 12 benchmarks spanning species (human, rat, dog, macaque) and modalities (Scalp-EEG, SEEG, ECoG, LFP), FAPEX consistently outperforms 23 supervised and 10 self-supervised baselines under nested cross-validation, with gains of up to 15% in sensitivity on complex cross-domain scenarios. It further demonstrates superior performance in several external validation cohorts. To our knowledge, these establish FAPEX as the first epilepsy model to show consistent superiority in SASP, offering a promising solution for discovering epileptic biomarker evidence supporting the existence of a distinct and identifiable preictal state and clinical translation. |
| title | FAPEX: Fractional Amplitude-Phase Expressor for Robust Cross-Subject Seizure Prediction |
| topic | Neurons and Cognition Signal Processing |
| url | https://arxiv.org/abs/2511.03263 |