Two Suggested Probabilistic and Kinetic Models for Astrocytic Network in Spiking Neural Networks

Abstract

Astrocytes, the predominant glial cell type in the brain, were traditionallyconsidered as merely passive supportive cells without any important roles in synaptic information processing. In contrast, the contemporary view was given rise to show that astrocytes play active roles in synaptic neurotransmissionand information processing. Hence, recently two terms have been emerged, tripartite synapse, to describe the communication between an astrocyte and two neurons, and the term astrocytic syncytium or astrocytic network to describe the communication among the astrocytesby gap junction. Therefore, we propose mathematical models for tripartite synapseand astrocytic syncytium basedontwo-state kinetics models, several probabilistic methods and Spiking Neural Network (SNN) to introducenew Artificial Astrocytic Syncytium (AAS) model. The simulation results have shown that proposed model could represent the cellular intrinsic properties of astrocyte based on the spatial and temporal aspects to emulate the astrocytic network functions related to cognitive, learning and memory.