The Development of Dominance Stripes and Orientation Maps in a Self-Organising Visual Cortex Network (VICON)

TL;DR

This paper introduces a self-organising neural network model, VICON, which develops properties like dominance stripes and orientation maps similar to mammalian visual cortex, based on Bayesian analysis of neural firing data.

Contribution

The paper presents a novel Bayesian-based self-organising neural network model that replicates key visual cortex features such as dominance stripes and orientation maps.

Findings

VICON develops dominance stripes and orientation maps.

The model is based on Bayesian analysis of neural firing.

Properties emerge from data from two imaging sensors.

Abstract

A self-organising neural network is presented that is based on a rigorous Bayesian analysis of the information contained in individual neural firing events. This leads to a visual cortex network (VICON) that has many of the properties emerge when a mammalian visual cortex is exposed to data arriving from two imaging sensors (i.e. the two retinae), such as dominance stripes and orientation maps.