The FlEye camera: Sampling the joint distribution of natural scenes and motion

TL;DR

This paper introduces the FlEye camera, a specialized device mimicking the fly's eye, to capture natural scene motion and signals, enabling better understanding of fly visual processing and motion estimation.

Contribution

The paper presents the design and performance of the FlEye camera, a novel instrument for recording natural visual signals and motion in a fly-like context.

Findings

The FlEye camera accurately captures natural scene statistics.

Optimal local motion estimators can be derived from FlEye data.

Comparison with fly neurons reveals insights into motion processing.

Abstract

To make efficient use of limited physical resources, the brain must match its coding and computational strategies to the statistical structure of input signals. An attractive testing ground for these principles is the problem of motion estimation in the fly visual system: we understand the optics of the compound eye, have a quantitative description of input signals and noise from the retina, and can record from output neurons that encode estimates of different velocity components. Furthermore, recent work provides a nearly complete wiring diagram of the intervening circuitry. What is missing is a characterization of the visual signals and motions that flies encounter in a natural context. We attack this directly with the development of a specialized camera that matches the high temporal resolution, optical properties, and spectral sensitivity of the fly's eye; inertial motion sensors provide ground truth about rotations and translations through the world. We describe the design, construction, and performance characteristics of this FlEye camera. To illustrate the opportunities created by this instrument we use data on movies and motion to construct optimal local motion estimators that can be compared with the responses of the fly's motion sensitive neurons.