A NETWORK MODEL OF MOTION PROCESSING IN AREA MT OF PRIMATES

A simple and biologically plausible model is proposed to simulate the visual motion processing taking place in the middle temporal (MT) area of the visual cortex in the primate brain. The model is a hierarchica l neural network composed of multiple competitive learning layers. The input layer of the network simulates the neurons in the primary visua l cortex (V1), which are sensitive to the orientation and motion veloc ity of the visual stimuli, and the middle and output layers of the net work simulate the component MT and pattern MT neurons, which are selec tively responsive to local and global motions, respectively. The netwo rk model was tested with various simulated motion patterns (random dot s of different direction correlations, transparent motion, grating and plaid patterns, and so on). The response properties of the model clos ely resemble many of the known features of the MT neurons found neurop hysiologically. These results show that the sophisticated response beh aviors of the MT neurons can emerge naturally from some very simple mo dels, such as a competitive learning network.