NEURAL NETWORK ARCHITECTURES FOR MOTION PERCEPTION AND ELEMENTARY MOTION DETECTION IN THE FLY VISUAL-SYSTEM

Two distinct but complementary neural architectures for motion perception are presented. Part I of the paper describes a directionally selective, local motion detector based on the fly visual system. Model predictions are compared with experimental data and the relationship of the neural model with the Reichardt functional model is discussed. Part II of the paper introduces a motion-sensitive network, insensitive to the direction of motion. First, local temporal discrimination problem is addressed in shunting networks and the limitations of the local scheme are used to motivate spatial interactions. Then, asynchronous interactions are studied in center-surround antagonistic shunting networks. Some properties of resulting asynchronous shunting networks are established. Finally, extensions of the work and integration of these architectures into a global model are discussed. © 1990.