A Nonlinear Model for Context-Dependent Modulation of the Binocular VOR

Abstract

Studies on the behavior of the vestibulo-ocular reflex (VOR) reveal that the monocular reflex gain is adjusted according to target position relative to each eye. In this paper, we present a nonlinear approach in modeling the viewing-context dependency of the slow-phase angular VOR. We show that including appropriate nonlinearities in the responses of premotor neurons in the brainstem is sufficient to account for the online modulation of the VOR with target position. This approach allows very complex behaviors in response to sensory patterns without resorting to currently assumed cortical computations. A local premotor topology with nonlinear properties has repercussions in the study of all ocular reflexes, since it implies context dependent dynamics in all behavioral responses (pursuit, optokinetic, VOR, saccades, etc.) that share this network. Local nonlinearities in spinal circuits could similarly influence the context dependence of other motor systems (such as stretch reflex modulation during rhythmic walking).

Implications of gain modulation in brainstem circuits: VOR control system

“…The nonlinear integration proposed by Khojasteh and Galiana (2006) is compatible with prior experimental studies on modulations of horizontal angular VOR with target distance, which provided evidence for linear and nonlinear pathways in the VOR (Minor et al 1999). The nonlinear pathway that is likely to be mediated by irregularly discharging vestibular afferents is a highly modifiable pathway especially during VOR adaptation and compensation.…”

“…The positive feedback loops around medial vestibular nuclei and prepositus nuclei implement the dynamics of a gazeholding network (integrator) beyond the time constant of the eye plant filter (Cheron and Godaux 1987;Robinson 1989). For complete physiological details of the model see (Khojasteh and Galiana 2006). The eye plant is modeled with first order low-pass dynamics, P(s) = sT v +1 .…”

“…1. A detailed explanation for solving the small signal model is provided in the Appendix of Khojasteh and Galiana (2006). Note that when testing the VOR response while initially fixating targets at specific locations, x 0 equals the initial value of the efference copy of the eye position corresponding to that target location.…”

“…Considering that the efference copies of monocular position signals at the output of the neural integrator are available in the vestibular nuclei (Zhou and King 1996), and that such information can provide a measure of target distance, Chen-Huang and McCrea also suggested that the viewing-distance-related modulations in the VOR gain are probably related to the eye position signals. Using a physiologically compatible model for the angular VOR, Khojasteh and Galiana later showed that if piece-wise linear functions are embedded in the response of EHV neurons (instead of commonly assumed linear cells), VOR gain changes with target distance can be replicated for the special case of midline targets (Khojasteh and Galiana 2006;Khojasteh-Lakelayeh and Galiana 2003). The importance of this model was that it used the efference copies of monocular position signals to regulate the gain of the EHV cells to vestibular inputs.…”

“…both viewing distance and gaze direction). One major shortcoming of the model in (Khojasteh and Galiana 2006) is that it merely simulates correct VOR gains for central targets at different distances, failing to simulate appropriate monocular gains for eccentric targets. Hence this modeling approach is now extended to include a proper non-linear function that covers the whole oculomotor range.…”