Multi-timescale interactions underlying the emergence and evolution of seizure dynamics

Abstract Epileptic electroencephalographic (EEG) activity exhibits recurrent seizures, evolving fast and slow wave-forms, state-dependent responses to perturbations, and delayed recruitment between brain regions. How these phenomena emerge from interactions across distinct timescales remains unclear. In this study, we propose a multi-timescale Dual-Component Epileptic EEG (DCE) model that reciprocally couples square-wave bursting and spike-wave subsystems, and we investigate its dynamics using slow-fast and bifurcation analyses, pulse perturbations, and coupled-node simulations. The model generates recurrent seizure-like events that evolve from fast ictal-like activity through spike-wave complexes to slow waves, with spectral evolution qualitatively resembling clinical EEG. Phase-space analysis shows that the epileptogenicity parameter regulates recurrence by shifting an ultraslow nullcline, primarily altering interictal duration. Pulse-induced transitions depend jointly on stimulus amplitude and the ultraslow recovery state. Within individual events, the two coupling directions modulate the fast-burst envelope and drive transitions among oscillatory regimes, respectively. At the coupled-node level, local epileptogenicity and coupling strength organize five dynamical modes. The stimulated node responds on a fast timescale, whereas recruitment of a second node is delayed by ultraslow coupling dynamics, with stronger coupling shortening this delay. The DCE model therefore provides a unified dynamical framework that relates these seizure-related phenomena to mechanisms operating across multiple timescales.

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Publication Details

Journal
Chinese Physics B
Published
2026-11-11
DOI
https://doi.org/10.1088/1674-1056/aec08c
Primary Topic
Neural dynamics and brain function
Type
article
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article

Multi-timescale interactions underlying the emergence and evolution of seizure dynamics

Xile Wei, Feng Zhang, Meili Lu
Chinese Physics B
Neural dynamics and brain function
article

Multi-timescale interactions underlying the emergence and evolution of seizure dynamics

Xile Wei, Feng Zhang, Meili Lu
article en

Abstract

Abstract Epileptic electroencephalographic (EEG) activity exhibits recurrent seizures, evolving fast and slow wave-forms, state-dependent responses to perturbations, and delayed recruitment between brain regions. How these phenomena emerge from interactions across distinct timescales remains unclear. In this study, we propose a multi-timescale Dual-Component Epileptic EEG (DCE) model that reciprocally couples square-wave bursting and spike-wave subsystems, and we investigate its dynamics using slow-fast and bifurcation analyses, pulse perturbations, and coupled-node simulations. The model generates recurrent seizure-like events that evolve from fast ictal-like activity through spike-wave complexes to slow waves, with spectral evolution qualitatively resembling clinical EEG. Phase-space analysis shows that the epileptogenicity parameter regulates recurrence by shifting an ultraslow nullcline, primarily altering interictal duration. Pulse-induced transitions depend jointly on stimulus amplitude and the ultraslow recovery state. Within individual events, the two coupling directions modulate the fast-burst envelope and drive transitions among oscillatory regimes, respectively. At the coupled-node level, local epileptogenicity and coupling strength organize five dynamical modes. The stimulated node responds on a fast timescale, whereas recruitment of a second node is delayed by ultraslow coupling dynamics, with stronger coupling shortening this delay. The DCE model therefore provides a unified dynamical framework that relates these seizure-related phenomena to mechanisms operating across multiple timescales.

Chinese Physics B
Tianjin University of Technology and Education (CN), Tianjin University (CN)
Neural dynamics and brain function
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