Although pursuit eye movements are necessarily guided by visual feedback, the pursuit system also uses predictive control to improve performance. This is due to very large (about 100ms) delays in processing visual information about target location. In spite of these long delays, the eye can actually lead the target during sinusoidal pursuit at low frequencies. Predictive strategies also improve performance along more complicated trajectories. Our own work (Leung & Kettner 1997) & Kettner 1997) indicates that the eye lags the target by an average of only 3 ms for circles, 4 ms for sum-of-two-sines trajectories, and actually leads the target by 9 ms for sum-of-three-sines trajectories. In contrast, visual delays were estimated at 90 ms when the same monkeys responded to unpredictable perturbations. New experiments in progress indicate that half-circle, CW-to-CCW, and gap trajectories can be tracked using predictive control, but only after extended training. The proposed experiments will study single neuron responses in the flocculus and paraflocculus during the learning and/or performance of these new predictive behaviors. A biologically realistic model that shows how the flocculus/paraflocculus could generate predictive behaviors will also be tested. This work has clinical relevance. Deficits in oculomotor control are currently used as markers for clinical disorders such as schizophrenia and Parkinson's disease that involve deficits in thinking and motor processing. The measures of predictive control being developed in these studies will allow detailed assessments of predictive deficits. In addition, an understanding of how the brain learns predictive control may lead to strategies for rehabilitating patients.
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