Smooth intersaccadic eye movements are the primary source of retinal image motion in the inter-saccadic periods in which visual information is acquired and processed. Yet, whereas microsaccades have received considerable attention in the scientific literature, relatively few studies have focused on ocular drift and its visual consequences. Main limiting factors in the study of ocular drift are its small size and low velocity, which make it difficult to resolve with standard eyetrackers.

Research in the Active Perception Laboratory has revealed a form of matching between the characteristics of ocular drift and those of natural images: luminance modulations resulting from drift counterbalance the spectral distributions of natural images to yield a retinal input with equalized power (Kuang et al., 2012). This effect enhance high-frequency vision (Rucci et al., 2007) and has important implications for theories of neural encoding, as the temporal input is already decorrelated before any neural processing takes place. We have also shown that (a) drift velocity is much higher than commonly assumed (Cherici et al., 2012) and (b) perceptual suppression of image motion caused by drift relies primarily on the visual input rather than possible extraretinal signals (Poletti et al., 2010).
Ocular drift

Abstract: Humans and other species continually perform microscopic eye movements, even when attending to a single point. These movements, which include drifts and microsaccades, are under oculomotor control, elicit strong neural responses, and have been thought to serve important functions. The influence of these fixational eye movements on the acquisition and neural processing of visual information remains unclear. Here, we show that during viewing of natural scenes, microscopic eye movements carry out a crucial information-processing step: they remove predictable correlations in natural scenes by equalizing the spatial power of the retinal image within the frequency range of ganglion cells' peak sensitivity. This transformation, which had been attributed to center-surround receptive field organization, occurs prior to any neural processing and reveals a form of matching between the statistics of natural images and those of normal eye movements. We further show that the combined effect of microscopic eye movements and retinal receptive field organization is to convert spatial luminance discontinuities into synchronous firing events, beginning the process of edge detection. Thus, microscopic eye movements are fundamental to two goals of early visual processing: redundancy reduction and feature extraction.

Spatiotemporal input to the retina during intersaccadic fxation (left) together with its static (center) and dynamic components (right). The sum of these two components gives the original movie to the left. Energy at nonzero temporal frequencies is spatially equalized due to the motion of the eye.

X. Kuang, M. Poletti and J. D. Victor and M. Rucci (2012), Temporal Encoding of Spatial Information during Active Visual Fixation, Current Biology, 22(6), 510514. (See also Dispatch     )
Stimuli (left) and mean subject performance (right). Performance dropped under retinal stabilization at high but not low spatial frequencies.

Abstract: Our eyes are constantly in motion. Even during visual fixation, small eye movements continually jitter the location of gaze. It is known that visual percepts tend to fade when retinal image motion is eliminated in the laboratory. However, it has long been debated whether, during natural viewing, fixational eye movements have functions in addition to preventing the visual scene from fading. In this study, we analysed the influence in humans of fixational eye movements on the discrimination of gratings masked by noise that has a power spectrum similar to that of natural images. Using a new method of retinal image stabilization18, we selectively eliminated the motion of the retinal image that normally occurs during the intersaccadic intervals of visual fixation. Here we show that fixational eye movements improve discrimination of high spatial frequency stimuli, but not of low spatial frequency stimuli. This improvement originates from the temporal modulations introduced by fixational eye movements in the visual input to the retina, which emphasize the high spatial frequency harmonics of the stimulus. In a natural visual world dominated by low spatial frequencies, fixational eye movements appear to constitute an effective sampling strategy by which the visual system enhances the processing of spatial detail.

M. Rucci, R. Iovin, M. Poletti and F. Santini (2007), Miniature eye movements enhance fine spatial detail, Nature, 447, 851-855.
Probability density functions of gaze position for individual observers during sustained fixation. Different panels refer to different subjects.

Abstract: During visual fixation, microscopic eye movements shift the image on the retina over a large number of photoreceptors. Although these movements have been investigated for almost a century, the amount of retinal image motion they create remains unclear. Currently available estimates rely on assumptions about the probability distributions of eye movements that have never been tested. Furthermore, these estimates were based on data collected with only a few, highly experienced and motivated observers and may not be representative of the instability of naive and inexperienced subjects in experiments that require steady fixation. In this study, we used a high-resolution eye-tracker to estimate the probability distributions of gaze position in a relatively large group of human observers, most of whom were untrained, while they were asked to maintain fixation at the center of a uniform field in the presence/absence of a fixation marker. In all subjects, the probability distribution of gaze position deviated from normality, the underlying assumption of most previous studies. The resulting fixational dispersion of gaze was much larger than previously reported and varied greatly across individuals. Unexpectedly, the precision by which different observers maintained fixation on the marker was best predicted by the properties of ocular drift rather than those of microsaccades. Our results show that, during fixation, the eyes move by larger amounts and at higher speeds than commonly assumed and highlight the importance of ocular drift in maintaining accurate fixation.

C. Cherici, X. Kuang, M. Poletti and M. Rucci (2012), Precision of sustained fixation in trained and untrained observers, Journal of Vision, 12(6):31, 1-15.
Influence of ocular drift on the perceived motion of a stationary stimulus. Percentages of moving responses are shown as a function of drift length in the normal condition, when the dot was stationary on the monitor (left); and under retinal stabilization, when the dot was stationary on the retina (right). Data obtained both in the dark (black) and under dim illumination (gray) are reported. The results of a control experiment in which two observers examined the motion of an afterimage are also shown.

Abstract: We are normally not aware of the microscopic eye movements that keep the retinal image in motion during visual fixation. In principle, perceptual cancellation of the displacements of the retinal stimulus caused by fixational eye movements could be achieved either by means of motor/proprioceptive information or by inferring eye movements directly from the retinal stimulus. In this study, we examined the mechanisms underlying visual stability during ocular drift, the primary source of retinal image motion during fixation on a stationary scene. By using an accurate system for gaze-contingent display control, we decoupled the eye movements of human observers from the changes in visual input that they normally cause. We show that the visual system relies on the spatiotemporal stimulus on the retina, rather than on extraretinal information, to discard the motion signals resulting from ocular drift. These results have important implications for the establishment of stable visual representations in the brain and argue that failure to visually determine eye drift contributes to well known motion illusions such as autokinesis and induced movement.

M. Poletti, C. Listorti and M. Rucci (2010), Stability of the Visual World during Eye Drift, The Journal of Neuroscience, , 1114311150.