Computational modeling of the vestibulo-ocular circuitry
is essential for an understanding of the sensory-motor
transformation that generates spatially and dynamically
appropriate compensatory eye movements during selfmotion. The generation of the neuronal commands for
gaze stabilization in the central nervous system depends
on the cellular characteristics of the involved neurons as
well as on the functional organization of the neuronal circuits in which these neurons are embedded. Thus, any reasonable model must adequately incorporate both the
intrinsic membrane properties of the neuronal elements
as well as the properties of the networks. Central vestibular neurons in the brainstem are responsible for the major
computational step in the transformation of sensory vestibular signals during body motion into motor commands for extraocular muscles that cause compensatory
eye motion. In frog, these second-order vestibular neurons (2°VN) separate into two distinctly different functional subgroups (tonic-phasic neurons) based on
differences in intrinsic membrane properties and discharge characteristics. Correlated with these cellular properties, tonic and phasic 2°VN exhibit pronounced
differences in the dynamics of the synaptic activation following stimulation of individual labyrinthine nerve
branches [1]. A detailed physio-pharmacological analysis