Development of a Neural Network Model for Controlling Horizontal Saccadic Eye Movements

Abstract

We present a neural network that mimics the timing, firing rate and synchrony of the neuronal populations involved in the execution of horizontal saccades. While each involved neuron encompasses dendritic, axonal and synaptic components, the control mechanism of the saccades is also investigated in our study. The proposed saccade generator captures in essence the neural dynamics of the Hodgkin-Huxley model and a time-varying FitzHugh-Nagumo model. It evolves so that a burst discharge (pulse) from the agonist motoneurons and a pause in firing from antagonist motoneurons serve as the neural inputs to the agonist and antagonist muscles. The importance of simulating horizontal saccades is that it provides a framework for early diagnosis and treatment of injuries sustained during the mild traumatic brain injury.