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A positive-feedback (PF) neuron device capable of threshold tuning and simultaneously processing excitatory (G±) and inhibitory (G-) signals is experimentally demonstrated to replace conventional neuron circuits, for the first time. Thanks to the PF operation, the PF neuron device with steep switching characteristics can implement integrate-and-fire (IF) function of neurons with low-energy consumption. The structure of the PF neuron device efficiently merges a gated PNPN diode and a single MOSFET. Integrateand-fire (IF) operation with steep subthreshold swing (SS <; 1 mV/dec) is experimentally implemented by carriers accumulated in an n floating body of the PF neuron device. The carriers accumulated in the n floating body are discharged by an inhibitory signal applied to the merged FET. Moreover, the threshold voltage (V_th) of the proposed PF neuron is controlled by using a charge storage layer. The low-energy consuming PF neuron circuit (~0.62 pJ/spike) consists of one PF device and only five MOSFETs for the IF and reset operation. In a high-level system simulation, a deep-spiking neural network (D-SNN) based on PF neurons with four hidden layers (1024 neurons in each layer) shows high-accuracy (98.55%) during a MNIST classification task. The PF neuron device provides a viable solution for high-density and low-energy neuromorphic systems.