Panoramic visual cues, as generated by the objects in the environment, provide the brain with important information about gravity direction. To derive an optimal, i.e. Bayesian, estimate of gravity direction, the brain must combine panoramic information with gravity information detected by the vestibular system. Here, we examined the individual sensory contributions to this estimate psychometrically. We asked human subjects to judge the orientation (clockwise or counterclockwise relative to gravity) of a briefly flashed luminous rod, presented within an oriented square frame (rod-in-frame). Vestibular contributions were manipulated by tilting the subjects’ head, whereas visual contributions were manipulated by changing the viewing distance of the rod and frame. Results show a cyclical modulation of the frame-induced bias in perceived verticality across a 90° range of frame orientations. The magnitude of this bias decreased significantly with larger viewing distance, as if visual reliability was reduced. Biases increased significantly when the head was tilted, as if vestibular reliability was reduced. A Bayesian optimal integration model, with distinct vertical and horizontal panoramic weights, a gain factor to allow for visual reliability changes and ocular counterroll in response to head tilt, provided a good fit to the data. We conclude that subjects flexibly weigh visual panoramic and vestibular information based on their orientation-dependent reliability, resulting in the observed verticality biases and the associated response variabilities.
Significance Statement: Sensing the direction of gravity is very relevant for human perception and action. While estimating gravity direction is known to depend on our inertial sensors, such as the vestibular organs, panoramic vision may also be important, providing cues that are oriented along gravity. The present study is the first that psychophysically characterizes this multisensory interaction. We further show that a Bayesian model involving a flexible weighting of vestibular and panoramic visual signals, with separate weights for vertical and horizontal visual cues, can account for the results. We discuss how this model could serve as a useful tool to establish the quality of signals in neurological disease.
- Bayesian Inference
- Internal models
- Multisensory Integration
- Rod-and-Frame Task
- Spatial Orientation
- Verticality Perception
Authors report no conflict of interest.
This work was supported by the European Research Council (EU–ERC 283567) and the Netherlands Organisation for Scientific Research (NWO-MaGW 404-10-142, NWO–VICI: 453–11–001 & NWO-VENI: 451-10-017).