Causal Inference in the Perception of Verticality

Abstract

The perceptual upright is thought to be constructed by the central nervous system (CNS) as a vector sum; by combining estimates on the upright provided by the visual system and the body's inertial sensors with prior knowledge that upright is usually above the head. Recent findings furthermore show that the weighting of the respective sensory signals is proportional to their reliability, consistent with a Bayesian interpretation of a vector sum (Forced Fusion, FF). However, violations of FF have also been reported, suggesting that the CNS may rely on a single sensory system (Cue Capture, CC), or choose to process sensory signals based on inferred signal causality (Causal Inference, CI). We developed a novel alternative-reality system to manipulate visual and physical tilt independently. We tasked participants (n = 36) to indicate the perceived upright for various (in-)congruent combinations of visual-inertial stimuli, and compared models based on their agreement with the data. The results favor the CI model over FF, although this effect became unambiguous only for large discrepancies (±60°). We conclude that the notion of a vector sum does not provide a comprehensive explanation of the perception of the upright, and that CI offers a better alternative.

Figure 1

(a) (Monoscopic) screenshot of a participant’s view through the alternative-reality system, showing the entrance and control area of the simulator hall. (b) photograph of the alternative-reality system. (c) view of the experimental setup, showing the motion platform and seat. The green arrows indicate axes of rotation. The pointer device is on the right hand side of the seat.

Figure 2

Overview of the results for an example participant (31). Each panel shows the data of a particular experimental condition. Responses (white dots) reflect the negative of the perceived tilt. The gray-shaded areas show the corresponding kernel density estimates. The thin black line at 0° is the Earth-vertical. The colored lines represent the response densities according to the SS (blue), FF (green), and CI (red) models that allowed for distortion in perceptions. Note how the CI model allows for behaviors in between the FF and SS models.