The constitution of visual perceptual units in the functional architecture of V1

TL;DR

This paper presents a neural model of the visual cortex that explains how perceptual units form in response to visual input, extending previous models to include neurogeometry and eigenmode stability analysis.

Contribution

It introduces a generalized neural model incorporating neurogeometry, demonstrating how stable eigenmodes correspond to perceptual units in visual images.

Findings

Eigenmodes become stable in response to visual input.

Stable eigenmodes represent perceptual units in images.

Model extends previous work by including neurogeometry.

Abstract

Scope of this paper is to consider a mean field neural model which takes into account the functional neurogeometry of the visual cortex modelled as a group of rotations and translations. The model generalizes well known results of Bressloff and Cowan which, in absence of input, accounts for hallucination patterns. The main result of our study consists in showing that in presence of a visual input, the eigenmodes of the linearized operator which become stable represent perceptual units present in the image. The result is strictly related to dimensionality reduction and clustering problems.