2-DIMENSIONAL NEURAL-NETWORK MODEL OF THE PRIMATE SACCADIC SYSTEM

The objective of this paper is to present a distributed model of the s patiotemporal neural processing that underlies the control of two-dime nsional saccadic eye movements in the monkey. In this new model the su perior colliculus (SC) is represented by two layers of cells. Simulate d visual inputs activate the upper layer that is connected lo the lowe r (motor) layer with feed forward projections. Extensive lateral inter connections exist in the motor layer The weights assigned to these int erconnections are established with a recurrent back propagation algori thm and by training on a set of activity patterns obtained from neuron s recorded in the monkey SC. A distributed set of connections to horiz ontal and vertical brainstem saccadic burst generators is trained to a llow the model to make accurate saccades to randomly selected target p ositions. Finally, the model is able to produce accurate eye movements and realistic neural discharge for saccades evoked with a variety of experimental conditions not included in the training set (for example, averaging and express saccades).