Fixational Eye Movements: Data Augmentation for the Brain?

Fixational eye movements are ubiquitous and have a large impact on visual perception. Although their physical characteristics and, to some extent, neural underpinnings are well documented, their function, with the exception of preventing visual fading, remains poorly understood. In this paper, we propose that the visual system might utilize the relatively large number of similar slightly jittered images produced by fixational eye movements to help learn robust and spatially invariant representations as a form of neural data augmentation. Additionally, we form a link between effects such as retinal stabilization and predictive processing theory, and argue that they may be best explained under such a paradigm.