چکیده:
Introduction: Investigating an effective controller to shift hippocampal epileptic periodicity to normal chaotic behavior will be new hope for epilepsy treatment. Astrocytes nourish and protect neurons and maintain synaptic transmission and network activity. Therefore, this study explored the ameliorating effect of the astrocyte computational model on epileptic periodicity.
Methods: Modified Morris-Lecar equations were used to model the hippocampal CA3 network. Network inhibitory parameters were employed to generate oscillation-induced epileptiform periodicity. The astrocyte controller was based on a functional dynamic mathematical model of brain astrocytic cells.
Results: Results demonstrated that the synchronization of two neural networks shifted the brain’s chaotic state to periodicity. Applying an astrocytic controller to the synchronized networks returned the system to the desynchronized chaotic state.
Conclusion: It is concluded that astrocytes are probably a good model for controlling epileptic periodicity. However, more research is needed to delineate this effect.
نوع مطالعه:
Original |
موضوع مقاله:
Computational Neuroscience دریافت: 1398/12/19 | پذیرش: 1400/3/2 | انتشار: 1402/4/10