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.
Highlights
Whenever we specify objects’ relative locations using terms as ‘above’ or ‘below’, or when we move throughout the world while trying not to topple over, we make use of the fact that we have a perception of upright
Mittelstaedt[8] proposed that the Central Nervous System (CNS) constructs perceptions of verticality by combining the sensory information from the visual system and the body’s collective inertial sensors with the prior knowledge that ‘up’ is usually aligned with the long-body axis, and that the process could be described as a vector sum, where the length of the vectors represents the relative influence of each component
Different measures were used among studies: participants were instructed to either indicate the Subjective Visual Vertical (SVV) by aligning an object in the visual display with the perceived upright[14,16,17,18]; the perceptual upright was inferred from participants’ interpretations of the ambiguous symbol ‘p’, which is defined by its orientation relative to the perceived upright; and estimates of upright have been derived from a discrimination task, where participants discriminated between roll stimuli on the basis of Subjective Body Tilt[17] (SBT)
Summary
Whenever we specify objects’ relative locations using terms as ‘above’ or ‘below’, or when we move throughout the world while trying not to topple over, we make use of the fact that we have a perception of upright. Mittelstaedt[8] proposed that the Central Nervous System (CNS) constructs perceptions of verticality by combining the sensory information from the visual system and the body’s collective inertial sensors with the prior knowledge that ‘up’ is usually aligned with the long-body axis (the idiotropic vector), and that the process could be described as a vector sum, where the length of the vectors represents the relative influence of each component In subsequent work, this concept has been interpreted as a reflection of statistically optimal behavior by the Central Nervous System (CNS): according to Bayes’ rule, if sensory estimates of the upright are normally distributed random variables and the prior is either normally distributed or uninformative, the estimate that is most likely the true upright can be calculated as a weighted average of the sensory estimates, where the weights are proportional to the inverse of estimates’ variances[9,10,11,12,13]. These models state that the CNS constructs intermediate estimates of environmental properties consistent with different interpretations of their causes (i.e., a common cause or separate causes) in tandem, and combines these into final estimates, taking into account a-priori beliefs on the probability of alternative causal structures
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