How Haptic Size Sensations Improve Distance Perception

Determining distances to objects is one of the most ubiquitous perceptual tasks in everyday life. Nevertheless, it is challenging because the information from a single image confounds object size and distance. Though our brains frequently judge distances accurately, the underlying computations employed by the brain are not well understood. Our work illuminates these computions by formulating a family of probabilistic models that encompass a variety of distinct hypotheses about distance and size perception. We compare these models' predictions to a set of human distance judgments in an interception experiment and use Bayesian analysis tools to quantitatively select the best hypothesis on the basis of its explanatory power and robustness over experimental data. The central question is: whether, and how, human distance perception incorporates size cues to improve accuracy. Our conclusions are: 1) humans incorporate haptic object size sensations for distance perception, 2) the incorporation of haptic sensations is suboptimal given their reliability, 3) humans use environmentally accurate size and distance priors, 4) distance judgments are produced by perceptual “posterior sampling”. In addition, we compared our model's estimated sensory and motor noise parameters with previously reported measurements in the perceptual literature and found good correspondence between them. Taken together, these results represent a major step forward in establishing the computational underpinnings of human distance perception and the role of size information. Author Summary: Perceiving the distance to an object can be difficult because a monocular visual image is influenced by the object's distance and size, so the object's image size alone cannot uniquely determine the distance. However, because object distance is so important in everyday life, our brains have developed various strategies to overcome this difficulty and enable accurate perceptual distance estimates. A key strategy the brain employs is to use touched size sensations, as well as background information regarding the object's size, to rule out incorrect size/distance combinations; our work studies the brain's computations that underpin this strategy. We modified a sophisticated model that prescribes how humans should estimate object distance to encompass a broad set of hypotheses about how humans do estimate distance in actuality. We then used data from a distance perception experiment to select which modified model best accounts for human performance. Our analysis reveals how people use touch sensations and how they bias their distance judgments to conform with true object statistics in the enviroment. Our results provide a comprehensive account of human distance perception and the role of size information, which significantly improves cognitive scientists' understanding of this fundamental, important, and ubiquitous behavior.