Transition behavior of the seizure dynamics modulated by the astrocyte inositol triphosphate noise

TL;DR

This study models how astrocyte IP3 noise influences seizure transitions, revealing that increased noise can induce bistability and alter seizure patterns, thus offering insights into epileptic randomness.

Contribution

It introduces a neuron-astrocyte network model incorporating astrocytic IP3 noise, demonstrating its role in seizure dynamics and transition behaviors.

Findings

Increased IP3 noise induces epileptic seizures and neuronal firing changes.

Bistable states emerge with certain noise levels, switching between spiking and seizures.

Higher noise levels prolong depolarization block and alter seizure patterns.

Abstract

Epilepsy is a neurological disorder with recurrent seizures of complexity and randomness. Until now, the mechanism of epileptic randomness has not been fully elucidated. Inspired by the recent finding that astrocyte GTPase-activating protein (G-protein)-coupled receptors could be involved in stochastic epileptic seizures, we proposed a neuron-astrocyte network model, incorporating the noise of the astrocytic second messager, inositol triphosphate (IP3) which is modulated by the G-protein)-coupled receptor activation. Based on this model, we have statistically analysed the transitions of epileptic seizures by performing tens of simulation trials. Our simulation results show that the increase of the IP3 noise intensity induces the depolarization-block epileptic seizures together with an increase in neuronal firing frequency. Meanwhile, a bistable state of neuronal firing emerges under certain noise intensity, during which the neuronal firing pattern switches between regular sparse spiking and epileptic seizure states. This random presence of epileptic seizures is absent when the noise intensity continues to increase, accompanying with an increase in the epileptic depolarization block duration. The simulation results also shed light on the fact that calcium signals in astrocytes play significant roles in the pattern formations of the epileptic seizure. Our results provide a potential pathway for understanding the epileptic randomness.