: The brain is a complex organ of the body that performs many tasks, such as processing, regulation, controlling the other body organs, and performs the mind action like memory, Imagination, thinking and creativity. The most important part in each brain area is a neuron that transmits signals by chemical and electrical synapses.Today, neuroscientists provide the different approaches of brain modeling, in order to achieve more processing speed and accuracy.In this research, that the neuron is considered an agent is based on Hebbian theory, Theta model, Synaptic plasticity, and Metaplasticity. Consequently, the agent makes a decision to communicate with other agents according to environmental conditions. Moreover, the chemical synapse has been analyzed. In the chemical synapse, presynaptic neuron leads to stimulate postsynaptic neuron with diffusing neurotransmitters. It is possible that the postsynaptic neuron receives a signal according to receiving neurotransmitters. In this thesis, we proposed four models to analyze the neurons behavior based on game theoretical approaches, Morris-Lecar model, and Li-Rinzel model. In the first model, we propose a dynamic game to analyze the functionality of neurons in the chemical synapse. The active neuron is first agent and neuron at resting state is the second agent. In the second model, we investigate the functionality of neurons and astrocyte in the tripartite synapse by a Bayesian game that role of the astrocyte is a chance move. In the third model, we define nature for determining the uncertainty of neurons about the state of other neurons. The chemical synapse is modeled with two types uncertainty according to the Bayesian game. In the fourth model, we model the functionality of neurons in the chemical synapse according to the functionality of neuroglia. Nash equilibrium is a strategy profile that no player can increase its payoff by deviating unilaterally. If the environmental conditions are safe and neurons are healthy, all equilibria in four models will indicate communication for transmitting signal. If each neuron becomes ill, different equilibria will be calculated which indicate no communication for transmitting signal. The model simulation is based on the biological information of CA1 area in the hippocampus. We verify analytical simulations by theoretical results. As a matter of fact, when the environmental conditions and state of neurons are Acceptable, a synapse is formed for transmitting the signal that leads to increase synchronization in the network, otherwise, a synapse won't be formed. Keywords: Neuron, Astrocyte, Morris-Lecar model, Dynamic game, Bayesian game, Chemical synapse, Neural network