Effects of cerebellar lesions on saccade simulations

Experimental studies involving cerebellar lesions have been important tools for learning about the operation of the saccadic eye movement system. These studies have been used to further develop a neural network model for horizontal saccadic eye movement control. The neural control mechanism is first order time optimal, initiated by the deep layers of the superior colliculus and terminated by the cerebellar fastigial nucleus. The neural circuit consists of neurons in the paramedian pontine reticular formation (burst, tonic and pause cells), the vestibular nucleus, abducens nucleus, oculomotor nucleus, cerebellum, substantia nigra, nucleus reticularis tegmenti pontis, the thalamus, the deep layers of the superior colliculus and the oculomotor plant for each eye. Agonist burst cell activity is initiated with maximal firing due to an error between the target and eye position, and continues until the internal eye position in the cerebellar vermis reaches the desired position, then decays to zero. The cerebellar vermis is responsible for adapting the duration of maximal firing based on the initial position of the eye. There are two sets of neural integrators in the neural network. One operates within the cerebellar vermis to predict the width of the pulse, and the other within the paramedian pontine reticular formation to maintain the eyes at their destination. Antagonist neural activity is inhibited during the agonist burst activity. After the agonist burst, antagonist neural activity rises with a stochastic rebound burst and from input from the fastigial nucleus, then falls to a tonic firing level necessary to keep the eye at its destination. The onset of the antagonist tonic firing is stochastic, weakly coordinated with the end of the agonist burst, and under cerebellar control. A common mechanism of action is described, based on cerebellar gating, through the fastigial nucleus, that explains a number of different saccadic eye movement types, including dynamic overshoot, glissadic overshoot and undershoot, and undershoot. A linear homeomorphic oculomotor muscle model is used in the simulations of the operation of the neural network. Each of the neural sites in the model fire similar to experimental data, and simulate fast eye movements.