A neural network model of saccade generation using distributed dynamic feedback to superior colliculus

In this paper we present a new spatio-temporal neural network model of saccade generation using distributed dynamic feedback to the superior colliculus. Although the saccadic eye movement system has been widely studied little is known about what part of the brain calculates motor error, the difference between the desired eye position and the actual eye position, that accurately controls saccade eye movements. In the model we place the superior colliculus inside a brainstem feedback loop in order to replicate collicular discharge profiles observed neurophysiologically. In simulations the model succeeds in making accurate saccadic eye movements of a variety of sizes while producing realistic spatio-temporal patterns of collicular discharge.