Mathematical models are widely used and well-established in studies of the oculomotor system. Some of the newer techniques of nonlinear systems analysis also are now beginning to be applied to data from eye movement experiments. This convergence of established models and new methods allows us to address two issues in computational neuroscience. First, many published models are seldom subject to verification and further study by independent researchers. Second, some of the newly-developed measures of nonlinear dynamics are not easily interpreted in a way that is physiologically meaningful. We set out to address these issues by applying nonlinear dynamical measures to a specific model of oculomotor control, and also to the animal data upon which the model was based, to verify the model. We then made systematic alterations to the model to see how the dynamic measures changed, to help provide some basis for interpretation of these measures.
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