Movement and memory function in biological neural networks

Asymmetrical neural networks are shown in a biological neural network, the catfish retina. Several mechanisms have been proposed for the detection of motion in biological system. Hassenstein and Reichardt network (1956) and Barlow and Levick network (1965) of movements are similar to the asymmetrical network developed here. To make clear the difference among these asymmetrical networks, we applied nonlinear analysis developed by N. Wiener. Then, we can derive the α-equation of movement, which shows the direction of movement. During the movement, we also can derive the movement equation, which implies that the movement holds regardless of the parameter α. By analyzing the biological asymmetric neural networks, it is shown that the asymmetric networks are excellent in the ability of spatial information processing on the retinal level. The symmetric network was discussed by applying nonlinear analysis. In the symmetric neural network, it was suggested that memory function is needed to perceive the movement