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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2505.07988 |
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| _version_ | 1866916734899847168 |
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| author | Dutta, Subhasanket Jalan, Sarika Vakilna, Yash Shashank Pati, Sandipan |
| author_facet | Dutta, Subhasanket Jalan, Sarika Vakilna, Yash Shashank Pati, Sandipan |
| contents | Postictal generalized EEG suppression (PGES) is a neurological condition that occurs in patients with generalized tonic-clonic seizures. It is marked by suppressed signals just after the seizure before the brain gradually recovers. Recovery from PGES involves a mixed state of amplitude suppression and high-amplitude oscillations, exhibiting a bimodal exponential distribution in power, unlike the unimodal exponential distribution of PGES. In this study, using the subcritical Hopf model, we explain the nature of phase transitions that underlie PGES. Our results reveal that recovery from PGES involves a change from a fixed point state to a bistable state (mixed phase), effectively captured by the noisy fixed-point and bistable regimes of the model. Consistent patterns across patients suggest a universal dynamical signature in PGES recovery. Our findings offer a mechanistic understanding of seizure termination and postictal brain state transitions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_07988 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Dynamical phase transitions in postictal generalized EEG suppression Dutta, Subhasanket Jalan, Sarika Vakilna, Yash Shashank Pati, Sandipan Adaptation and Self-Organizing Systems Postictal generalized EEG suppression (PGES) is a neurological condition that occurs in patients with generalized tonic-clonic seizures. It is marked by suppressed signals just after the seizure before the brain gradually recovers. Recovery from PGES involves a mixed state of amplitude suppression and high-amplitude oscillations, exhibiting a bimodal exponential distribution in power, unlike the unimodal exponential distribution of PGES. In this study, using the subcritical Hopf model, we explain the nature of phase transitions that underlie PGES. Our results reveal that recovery from PGES involves a change from a fixed point state to a bistable state (mixed phase), effectively captured by the noisy fixed-point and bistable regimes of the model. Consistent patterns across patients suggest a universal dynamical signature in PGES recovery. Our findings offer a mechanistic understanding of seizure termination and postictal brain state transitions. |
| title | Dynamical phase transitions in postictal generalized EEG suppression |
| topic | Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2505.07988 |