Modeling Cerebellar Flocculus and Paraflocculus Involvement in Complex Predictive Smooth Eye Pursuit in Monkeys

Abstract: The role of flocculus and paraflocculus neurons in the cerebellar control of predictive eye movements was examined using two modeling techniques. The first study characterized the dependence of individual Purkinje‐cell firing patterns on oculomotor output, visual input, and response timing using multilinear regression techniques. Interestingly, no dependence on visual input was detected. Purkinje cell firing was explained by sensitivities to eye position and eye velocity alone. However, complex responses occurred when sensitivity vectors pointed in different directions. For example, some neurons showed a preference for circular pursuit in a particular rotation direction. Responses also tended to lead the eye during predictable pursuit and to lag during unpredictable, visually driven pursuit. This suggests that flocculus and paraflocculus neurons played a stronger role during predictive pursuit than visually driven pursuit. A second modeling study demonstrated how the flocculus/paraflocculus system might generate predictive pursuit. A biologically realistic neural network was simulated based on the known anatomy and physiology of this cerebellar system. It included mossy and climbing fibers with realistic responses, Purkinje cells acting on well‐characterized brain‐stem circuits, and granule, Golgi, basket, and stellate cells with appropriate connections. The network was able to learn new pursuit trajectories based on long‐term alterations in synaptic connectivity at parallel‐to‐Purkinje synapses. Interestingly, this model was able to generate predictive pursuit without visual input based only on eye‐motion input. Thus, both models provide complementary evidence for the generation of nonvisual predictive control by flocculus and paraflocculus neurons.