Stimulus Motion Perception Studies Imply Specific Neural Computations in Human Visual Stabilization

TL;DR

This paper investigates how the human visual system perceives stable objects despite constant eye jitter, revealing complex neural computations that likely underlie visual stabilization.

Contribution

It provides a detailed psychophysical analysis and proposes a functional model and neural circuit hypotheses for visual stabilization mechanisms.

Findings

Eye jitter is compensated by specific neural operations.

Psychophysics suggest complex retinal signal processing.

Proposed neural circuits may implement stabilization functions.

Abstract

Even during fixation the human eye is constantly in low amplitude motion, jittering over small angles in random directions at up to 100Hz. This motion results in all features of the image on the retina constantly traversing a number of cones, yet objects which are stable in the world are perceived to be stable, and any object which is moving in the world is perceived to be moving. A series of experiments carried out over a dozen years revealed the psychophysics of visual stabilization to be more nuanced than might be assumed, say, from the mechanics of stabilization of camera images, or what might be assumed to be the simplest solution from an evolutionary perspective. The psychophysics revealed by the experiments strongly implies a specific set of operations on retinal signals resulting in the observed stabilization behavior. The presentation is in two levels. First is a functional description of the action of the mechanism that is very likely responsible for the experimentally observed behavior. Second is a more speculative proposal of circuit-level neural elements that might implement the functional behavior.