Focused on the issue of decoding visual input from neuron response signal, a method to reconstruct visual input using neurons action potential (Spike) signal was proposed. Firstly, the Spike signal from the pigeon Optic Tectum (OT) neurons was recorded and the firing rate characteristics of Spike were extracted. Then, a linear inverse filter reconstruction model and a convolution neural network reconstruction model were constructed to realize the reconstruction of the visual input. Finally, the number of channels, time bin, data time length and delay time were optimized. Under the same parameter condition, the cross correlation coefficient of image reconstruction using linear inverse filter reconstruction model reached 0.910 7±0.021 9, and the cross correlation coefficient of image reconstruction using convolution neural network reconstruction model reached 0.927 1±0.017 6. The results show that the visual input can be reconstructed effectively by extracting firing rate characteristics of neuron Spike and using linear inverse filter reconstruction model and convolution neural network reconstruction model.