EXPRESS: The Influence of Three-Dimensional Cues on Body Size Judgements

Research has shown that body size judgements are frequently biased, or inaccurate. Critically, judgement biases are further exaggerated for individuals with eating disorders, a finding that has been attributed to difficulties integrating body features into a perceptual whole. However, current understanding of which body features are integrated when judging body size is lacking. In this study, we examine whether individuals integrate three-dimensional (3D) cues to body volume when making body size judgements. Computer-generated body stimuli were presented in a 3D Virtual Reality (VR) environment. Participants (N = 412) were randomly assigned to one of two conditions: in one condition the to-be-judged body was displayed binocularly (containing 3D cues to body volume), in the other, bodies were presented monocularly (2D cues only). Across 150 trials, participants were required to make a body size judgement of a target female body from a third-person point of view using an unmarked visual analogue scale (VAS). It was found that 3D cues significantly influenced body size judgements. Namely, thin 3D bodies were judged smaller, and overweight 3D bodies were judged larger, than their 2D counterpart. Furthermore, to reconcile these effects, we present evidence that the two perceptual biases, regression to the mean and serial dependence, were reduced by the additional 3D feature information. Our findings increase our understanding of how body size is perceptually encoded and creates testable predictions for clinical populations exhibiting integration difficulties.

Illusion of visual stability through active perceptual serial dependence

Visual stability is achieved through an active serial dependence mechanism that continuously biases perception toward the past.

Measuring Dispersion and Serial Dependence in Ordinal Time Series Based on the Cumulative Paired ϕ-Entropy

The family of cumulative paired ϕ-entropies offers a wide variety of ordinal dispersion measures, covering many well-known dispersion measures as a special case. After a comprehensive analysis of this family of entropies, we consider the corresponding sample versions and derive their asymptotic distributions for stationary ordinal time series data. Based on an investigation of their asymptotic bias, we propose a family of signed serial dependence measures, which can be understood as weighted types of Cohen’s κ, with the weights being related to the actual choice of ϕ. Again, the asymptotic distribution of the corresponding sample κϕ is derived and applied to test for serial dependence in ordinal time series. Using numerical computations and simulations, the practical relevance of the dispersion and dependence measures is investigated. We conclude with an environmental data example, where the novel ϕ-entropy-related measures are applied to an ordinal time series on the daily level of air quality.

Effect of spatiotemporally changing environment on serial dependence in ensemble representations

The recent visual past has a strong impact on our current perception. Recent studies of serial dependence in perception show that low-level adaptation repels our current perception away from previous stimuli whereas post-perceptual decision attracts perceptual report toward the immediate past. In their studies, these repulsive and attractive biases were observed with different task demands perturbing ongoing sequential process. Therefore, it is unclear whether the opposite biases arise naturally in navigating complex real-life environments. Here we only manipulated the environmental statistics to characterize how serially dependent perceptual decisions unfold in spatiotemporally changing visual environments. During sequential mean orientation adjustment task on the array of Gabor patches, we found that the repulsion effect dominated only when ensemble variance increased across consecutive trials whereas the attraction effect prevailed when ensemble variance decreased or remained the same. The observed attractive bias by high-to-low-variance stimuli and repulsive bias by low-to-high-variance stimuli were reinforced by the repeated exposure to the low and the high ensemble variance, respectively. Further, this variance-dependent differential pattern of serial dependence in ensemble representation remained the same regardless of whether observers had a prior knowledge of environmental statistics or not. We used a Bayesian observer model constrained by visual adaptation to provide a unifying account of both attractive and repulsive bias in perception. Our results establish that the temporal integration and segregation of visual information is flexibly adjusted through variance adaptation.

Multiple and Dissociable Effects of Sensory History on Working-Memory Performance

Behavioural reports of sensory information are biased by stimulus history. The nature and direction of such serial-dependence biases can differ between experimental settings - both attractive and repulsive biases towards previous stimuli have been observed. How and when these biases arise in the human brain remains largely unexplored. They could occur either via a change in sensory processing itself, post-perceptual maintenance or decision-making processes, or both. Here, we analysed behavioural and magnetoencephalographic data from a working-memory task in which participants were sequentially presented with two randomly oriented gratings, one of which was cued for recall at the end of the trial. Behavioural responses showed evidence for two distinct biases: 1) a within-trial repulsive bias away from the previously encoded orientation on the same trial, and 2) a between-trial attractive bias towards the task-relevant orientation on the previous trial. Multivariate classification of stimulus orientation revealed that neural representations during stimulus encoding were biased away from the previous grating orientation, regardless of whether we considered the within- or between-trial prior orientation - despite opposite effects on behaviour. These results suggest that repulsive biases occur at the level of sensory processing and can be overturned at post-perceptual stages to result in attractive biases in behaviour.