The Internal Structure of Seizures Reflects Animal-Specific Trajectories of Disease Progression and Circadian Modulation in Epileptic Mice

Abstract

Epileptic seizures arise from the abnormal, sustained recruitment of neuronal populations, yet the temporal organisation of activity within individual seizures remains poorly understood. We hypothesised that seizures follow structured trajectories through a restricted state space rather than random patterns of activity. To test this idea, we analysed continuous long-term EEG recordings from six mice with pilocarpine-induced temporal lobe epilepsy and developed a symbolic framework that transforms seizure activity into sequences of discrete burst states. Across more than one thousand spontaneous seizures, we found that seizures are organised by sparse, animal-specific transition rules linking a small repertoire of recurrent burst motifs. These rules evolve over the course of epilepsy: early seizures display substantial variability in burst composition, and, to a smaller but statistically significant degree, in transition structure, whereas later seizures become more stereotyped in which burst types they use, a pattern suggestive of consolidation of the epileptic network into a stable dynamical regime. Seizure microstructure was further modulated by circadian phase, indicating that biological rhythms influence not only when seizures occur but also how they unfold. Moreover, burst sequences exhibited higher-order temporal dependencies that could not be explained by first-order Markov statistics alone. Together, these results reveal an evolving seizure grammar that links ictal dynamics to disease progression and circadian regulation, establishing symbolic dynamics as a powerful framework for quantifying the internal organisation of seizures. significance statement Why seizures differ from one another, and how those differences relate to the evolution of epilepsy in each subject, remain poorly understood. We demonstrate that seizures are structured dynamical trajectories rather than uniform episodes of abnormal activity. Using symbolic and information-theoretic analyses of long-term recordings in epileptic mice, we identify a limited repertoire of recurrent activity patterns whose organisation evolves during chronic epilepsy and is modulated by circadian phase. These findings suggest that the internal structure of seizures encodes information about network reorganisation over time, providing a class of biomarkers for tracking disease progression.