Modeling of the complementary learning systems between hippocampus and neocortex

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In this research, we have examined the mechanism of the complementary learning between the hippocampus and the neocortex of the brain by using an artificial neural network model which is based on physiological, anatomical and neuropsychological findings. As the results, we have revealed that the structure of the hippocampus itself can decrease the similarity of patterns to be stored and makes easy to store them. This function can be exaggerated by the neuronal turnover in dentate gyrus. Moreover, we have shown that the chaotic recall in the hippocampal network can reduce catastrophic forgetting in the neocortical network.