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Simple model for the prediction of seizure durations.

Tyler SalnersKarin A DahmenJohn Beggs
Published in: Physical review. E (2024)
A simple model is used to simulate seizures in a population of spiking excitatory neurons experiencing a uniform effect from inhibitory neurons. A key feature is introduced into the model, i.e., a mechanism that weakens the firing thresholds. This weakening mechanism adds memory to the dynamics. We find a seizure-prone state in a "mode-switching" phase. In this phase, the system can suddenly switch from a "healthy" state with small scale-free avalanches to a "seizure" state with almost periodic large avalanches ("seizures"). Simulations of the model predict statistics for the average time spent in the seizure state (the seizure "duration") that agree with experiments and theoretical examples of similar behavior in neuronal systems. Our study points to. different connections between seizures and fracture and also offers an alternative view on the type of critical point controlling neuronal avalanches.
Keyphrases
  • temporal lobe epilepsy
  • spinal cord
  • machine learning
  • spinal cord injury
  • molecular dynamics
  • cerebral ischemia
  • monte carlo