Plasticity of neuronal networks is widely investigated as the basis of learning and stimulus-induced plasticity is one of the remarkable topics. For inducing plasticity and leading a network to a desired state, effective stimuli have to be applied to the network. However, the effect of stimuli on living neuronal networks is difficult to evaluate because of the unsteadiness of the network property. In this paper, we produce a simulated neuronal network and compare the effects of tetanic stimulus at various sites of networks in silico. Using simulation, the tetanic effects can be evaluated irrespective of network transition. We confirmed that the direction of the network plasticity is determined by the tetanized site in the network, and this can be observed only when the proper test-stimulus site is selected. We conclude that this simulation-based approach effectively evaluates the stimulus effect on neuronal networks.
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