# Normative theory of visual receptive fields

## TL;DR

This paper presents a normative computational theory for visual receptive fields, deriving models based on environmental and internal system assumptions, which closely match biological receptive fields in mammals.

## Contribution

It introduces an axiomatic framework for modeling visual receptive fields that predicts their shapes aligning with biological observations.

## Key findings

- Receptive field shapes predicted by the theory match biological data
- The theory provides a unified framework for early visual processing
- Models derived are consistent across spatial, chromatic, and temporal domains

## Abstract

This article gives an overview of a normative computational theory of visual receptive fields, by which idealized functional models of early spatial, spatio-chromatic and spatio-temporal receptive fields can be derived in an axiomatic way based on structural properties of the environment in combination with assumptions about the internal structure of a vision system to guarantee consistent handling of image representations over multiple spatial and temporal scales. Interestingly, this theory leads to predictions about visual receptive field shapes with qualitatively very good similarity to biological receptive fields measured in the retina, the LGN and the primary visual cortex (V1) of mammals.