Neural networks are information processing models based on the human brain, and they have been activity studied. However, in order to realize the hardware of the neural network, it is necessary to achieve high integration. In this study, we fabricated synapses for neural networks using the Ga-Sn-O (GTO) thin films, which is rare-metal-free amorphous oxide semiconductor. The synapses are planar type, and it is assumed that they are stacked on the LSI surface in the future. It was found that the synapses have a degradation characteristic that can be applied to modify Hebb's leaning rule. The deterioration characteristics obtained were modeled to simulate letter correction, and we succeeded the character correction.