Optimal measurement of visual motion across spatial and temporal scales
This work provides a principled explanation for puzzling phenomena in visual sensitivity, adaptation, and perceptual organization, with potential implications for understanding sensory systems.
The study tackled the problem of efficient resource allocation in visual perception by developing a normative framework for optimal sensor allocation to reliably perceive visual motion, revealing that human vision's spatiotemporal contrast sensitivity function closely matches the optimal prescription.
Sensory systems use limited resources to mediate the perception of a great variety of objects and events. Here a normative framework is presented for exploring how the problem of efficient allocation of resources can be solved in visual perception. Starting with a basic property of every measurement, captured by Gabor's uncertainty relation about the location and frequency content of signals, prescriptions are developed for optimal allocation of sensors for reliable perception of visual motion. This study reveals that a large-scale characteristic of human vision (the spatiotemporal contrast sensitivity function) is similar to the optimal prescription, and it suggests that some previously puzzling phenomena of visual sensitivity, adaptation, and perceptual organization have simple principled explanations.