Department of Physiology and the Neuroscience Institute, Northwestern University Medical School, Chicago, Illinois 60611, USA
aDepartment of Physiology/Neuroscience, New York University School of Medicine, New York, New York 10016, USA
bDepartment of Psychology, State University of New York, Stony Brook, New York 11794, USA
Address for correspondence: Ronald E. Kettner, Department of Physiology and the Neuroscience Institute, Northwestern University Medical School, Chicago, IL 60611. Voice: 312-503-0456; fax: 312-503-5101.
r-kettner{at}nwu.edu
Ann. N.Y. Acad. Sci. 978: 455-467 (2002).
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.
