Neural computations in spatial orientation

Abstract

This thesis describes the results of a research project that focused on how visual and vestibular signals are used by the human brain to maintain spatial orientation and visual stability. Given the limitations of the vestibular sensors in terms of bandwidth and precision, outlined in chapter 1, achieving this is far from trivial. Existing spatial orientation models have specified in some detail how the brain could cope with these imperfections when it comes to reconstructing three crucial variables: angular rotation of the body in space, body-tilt with respect to gravity and linear translation of the body. Our objective was to collect extensive quantitative data sets in various static and dynamic conditions, for comparison with the model predictions. In chapters two and three we quantified the selfmotion and verticality percept of human subjects that were rotated in yaw about an off-vertical axis (OVAR). The perceptual data were compared with two spatial orientation models: the frequency segregation hypothesis and the canal-otolith interaction model. In the fourth chapter, we tested whether an extended version of the canal-otolith interaction model could account for the verticality percept during three cycles of constant velocity rotation. In the final chapter, we investigated how the presence of a tilted visual frame influences the verticality percept of roll-tilted human observers and compared the results with two subjective visual vertical models.