Abstract
Astrocyte cells form the largest cell population in the brain and can influence neuron behavior. These cells provide appropriate feedback control in regulating neuronal activities in the Central Nervous System (CNS). This paper presents a set of equations as a model to describe the interactions between neurons and astrocyte. A VHDL–AMS-based tripartite synapse model that includes a pre-synaptic neuron, the synaptic terminal, a post-synaptic neuron, and an astrocyte cell is presented. In this model, the astrocyte acts as a controller module for neurons and can regulates the spiking activity of them. Simulation results show that by regulating the coupling coefficients of astrocytes, spiking frequency of neurons can be reduced and the activity of neuronal cells is modulated.
Highlights
This paper presents a set of equations as a model to describe the interactions between neurons and astrocyte
The results of neuron–astrocyte interaction simulation with VHDL–AMS are given in this part
We assume that z0 = 0 and the excitation of the post-neuronal cell is given as IPostsynaptic = KModi f iedKs Z + γGm
Summary
Several different computational approaches, such as Runge–Kutta methods, finite element, numerical linear algebra, statistics, numerical analysis, tensor analysis, and the most important one, Neural Networks (NNs), have been used in various fields of researches such as chemical engineering [1,2,3,4,5,6,7,8,9], electrical engineering [10,11,12,13,14,15,16,17,18,19], health and biology [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34], fluid mechanic engineering [35,36,37,38,39,40,41,42,43,44,45,46], civil engineering [47,48,49,50], computer sciences [51,52,53], petroleum engineering [54,55,56,57,58,59,60,61,62], and mathematics [63,64,65,66,67,68,69,70,71,72,73,74] etc. Neural–glial modeling and different aspects of their interaction can help to detect various biological states of the CNS [77] These astrocyte cells can have several functional roles, such as extracellular environment regulation, synaptic information regulation, neuronal synchronization, and feedback to neural activity [75,77,81]. The VHDL–AMS method is very suitable choice for evaluating the systems Since this approach is capable of behavioral modeling, linear and nonlinear systems are close together in the case of operation [89,90]. In this way, to achieve a useful and simple modeling of neuron–astrocyte interaction, VHDL–AMS stands out due to its convenience as a suitable option [89,90].
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