Uncertainty of visual measurement and efficient allocation of sensory resources

TL;DR

This paper reviews two approaches to combining sensory uncertainties and demonstrates how to optimally allocate sensory resources under uncertainty in visual measurement.

Contribution

It clarifies the relationship between two different approaches to sensory uncertainty and provides methods for optimal resource allocation in visual systems.

Findings

Two approaches to sensory uncertainty are compared and related.

Optimal solutions for resource allocation under uncertainty are demonstrated.

Theoretical insights into sensory integration and resource management are provided.

Abstract

We review the reasoning underlying two approaches to combination of sensory uncertainties. First approach is noncommittal, making no assumptions about properties of uncertainty or parameters of stimulation. Then we explain the relationship between this approach and the one commonly used in modeling "higher level" aspects of sensory systems, such as in visual cue integration, where assumptions are made about properties of stimulation. The two approaches follow similar logic, except in one case maximal uncertainty is minimized, and in the other minimal certainty is maximized. Then we demonstrate how optimal solutions are found to the problem of resource allocation under uncertainty.