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Autores principales: Dutta, Subhasanket, Jalan, Sarika, Vakilna, Yash Shashank, Pati, Sandipan
Formato: Preprint
Publicado: 2025
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Acceso en línea:https://arxiv.org/abs/2505.07988
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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.
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institution arXiv
publishDate 2025
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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