How Uncertainty bounds the shape index of simple cells

TL;DR

This paper uses the Uncertainty Principle to theoretically bound the shape index distributions of simple cells in the visual cortex, linking physiological measurements with fundamental detection limits.

Contribution

It introduces a novel theoretical framework applying the Uncertainty Principle to quantify physiological features of simple cells in visual cortex.

Findings

Provides quantitative bounds on shape index distributions

Links physiological data with detection uncertainty

Offers a new theoretical perspective on visual cortex features

Abstract

We propose a theoretical motivation to quantify actual physiological features, such as the shape index distributions measured by Jones and Palmer in cats and by Ringach in macaque monkeys. We will adopt the Uncertainty Principle associated to the task of detection of position and orientation as the main tool to provide quantitative bounds on the family of simple cells concretely implemented in primary visual cortex.