A paradigm for characterizing motion misperception in people with typical vision and low vision.

PURPOSE: We aimed to develop a paradigm that can efficiently characterize motion percepts in people with low vision and compare their responses with well-known misperceptions made by people with typical vision when targets are hard to see. METHODS: We recruited a small cohort of individuals with reduced acuity and contrast sensitivity (n = 5) as well as a comparison cohort with typical vision (n = 5) to complete a psychophysical study. Study participants were asked to judge the motion direction of a tilted rhombus that was either high or low contrast. In a series of trials, the rhombus oscillated vertically, horizontally, or diagonally. Participants indicated the perceived motion direction using a number wheel with 12 possible directions, and statistical tests were used to examine response biases. RESULTS: All participants with typical vision showed systematic misperceptions well predicted by a Bayesian inference model. Specifically, their perception of vertical or horizontal motion was biased toward directions orthogonal to the long axis of the rhombus. They had larger biases for hard-to-see (low contrast) stimuli. Two participants with low vision had a similar bias, but with no difference between high- and low-contrast stimuli. The other participants with low vision were unbiased in their percepts or biased in the opposite direction. CONCLUSIONS: Our results suggest that some people with low vision may misperceive motion in a systematic way similar to people with typical vision. However, we observed large individual differences. Future work will aim to uncover reasons for such differences and identify aspects of vision that predict susceptibility.

Perceptual consequences of interocular differences in the duration of temporal integration.

Temporal differences in visual information processing between the eyes can cause dramatic misperceptions of motion and depth. Processing delays between the eyes cause the Pulfrich effect: oscillating targets in the frontal plane are misperceived as moving along near-elliptical motion trajectories in depth (Pulfrich, 1922). Here, we explain a previously reported but poorly understood variant: the anomalous Pulfrich effect. When this variant is perceived, the illusory motion trajectory appears oriented left- or right-side back in depth, rather than aligned with the true direction of motion. Our data indicate that this perceived misalignment is due to interocular differences in neural temporal integration periods, as opposed to interocular differences in delay. For oscillating motion, differences in the duration of temporal integration dampen the effective motion amplitude in one eye relative to the other. In a dynamic analog of the Geometric effect in stereo-surface-orientation perception (Ogle, 1950), the different motion amplitudes cause the perceived misorientation of the motion trajectories. Forced-choice psychophysical experiments, conducted with both different spatial frequencies and different onscreen motion damping in the two eyes show that the perceived misorientation in depth is associated with the eye having greater motion damping. A target-tracking experiment provided more direct evidence that the anomalous Pulfrich effect is caused by interocular differences in temporal integration and delay. These findings highlight the computational hurdles posed to the visual system by temporal differences in sensory processing. Future work will explore how the visual system overcomes these challenges to achieve accurate perception.

Predicting the Partition of Behavioral Variability in Speed Perception with Naturalistic Stimuli.

A core goal of visual neuroscience is to predict human perceptual performance from natural signals. Performance in any natural task can be limited by at least three sources of uncertainty: stimulus variability, internal noise, and suboptimal computations. Determining the relative importance of these factors has been a focus of interest for decades but requires methods for predicting the fundamental limits imposed by stimulus variability on sensory-perceptual precision. Most successes have been limited to simple stimuli and simple tasks. But perception science ultimately aims to understand how vision works with natural stimuli. Successes in this domain have proven elusive. Here, we develop a model of humans based on an image-computable (images in, estimates out) Bayesian ideal observer. Given biological constraints, the ideal optimally uses the statistics relating local intensity patterns in moving images to speed, specifying the fundamental limits imposed by natural stimuli. Next, we propose a theoretical link between two key decision-theoretic quantities that suggests how to experimentally disentangle the impacts of internal noise and deterministic suboptimal computations. In several interlocking discrimination experiments with three male observers, we confirm this link and determine the quantitative impact of each candidate performance-limiting factor. Human performance is near-exclusively limited by natural stimulus variability and internal noise, and humans use near-optimal computations to estimate speed from naturalistic image movies. The findings indicate that the partition of behavioral variability can be predicted from a principled analysis of natural images and scenes. The approach should be extendable to studies of neural variability with natural signals.SIGNIFICANCE STATEMENT Accurate estimation of speed is critical for determining motion in the environment, but humans cannot perform this task without error. Different objects moving at the same speed cast different images on the eyes. This stimulus variability imposes fundamental external limits on the human ability to estimate speed. Predicting these limits has proven difficult. Here, by analyzing natural signals, we predict the quantitative impact of natural stimulus variability on human performance given biological constraints. With integrated experiments, we compare its impact to well-studied performance-limiting factors internal to the visual system. The results suggest that the deterministic computations humans perform are near optimal, and that behavioral responses to natural stimuli can be studied with the rigor and interpretability defining work with simpler stimuli.