Correcting for miniature eye movements in high-resolution scanning laser ophthalmoscopy

Background: Scanning laser ophthalmoscopes with adaptive optics correction of ocular aberrations provide retinal images of unprecedented resolution, allowing for real-time imaging of photoreceptors. Eye movements made by the subject/patient during recording produce distortions that must be corrected before multiple frames can be added together to achieve noise reduction or to build a mosaic image from different retinal areas. These distortions also provide a high spatial and temporal resolution record of the miniature eye movements made during fixation. Here we report simultaneous measurements of fixation eye movements with an Adaptive Optics Scanning Laser Ophthalmoscope (AOSLO) and a dual-Purkinje image (dPi) eye tracker in order to cross-validate these two methods of recording miniature eye movement. Method: Foveas of three subjects were imaged with a one degree square scan using the Houston AOSLO, at a resolution of 8 pixels per arc minute. A Generation V dPi tracker from SRI was placed in front of the AOSLO, and eye movements were recorded at the same time from the same eye being imaged by the AOSLO. AOSLO movies were analyzed off line to extract retinal image motion. The resulting traces were then overlaid on the dPi recordings for comparison. Results: The two methods produced records that agreed to within about one arc minute, with more significant disagreements occurring after eye blinks. Microsaccades in the dPi record were accompanied by overshoots that have previously been associated with lens wobble. AOSLO traces also showed saccade-related overshoots, but of much smaller amplitude. Conclusions: Eye movement recordings measured with dual Purkinje image trackers predict retinal image motion to a precision of about 1 arc minute, except for 10–20 milliseconds following each saccade and 500 – 1000 milliseconds following each eye blink. Retinal image motion measured directly from AOSLO recordings can be recovered to a precision of just a few arc seconds.

Oculomotor behavior and perceptual strategies in complex tasks

In this paper, we call the point on an object where human looks a subjective viewpoint and we call the point where the object and the straight line going through the center of pupil and the center of the fovea crosses an objective viewpoint. We realize eye movements in reading on the computer when an objective viewpoint is a subjective viewpoint and when an objective viewpoint is shifted to the right of a subjective viewpoint and we investigate the characteristics of eye movements. First, we realize a computer-simulation of human eye movements in reading. Secondly, the superiority of the right visual field appears in the foveated vision realized by shifting an objective viewpoint to the right of a subjective viewpoint. And we confirm that the gap between the subjective viewpoint and the objective viewpoint is important by comparing the characteristics of human eye movements to the characteristics of eye movements when an objective viewpoint is shifted to the right of a subjective viewpoint. Furthermore, we perform eye movements on the computer while shifting an objective viewpoint to the right of a subjective viewpoint and measure the speed at which an English sentence is read. We conclude that reading speed when the foveated vision has the superiority of the right visual field is faster than that when the foveated vision doesn't have it.

A recent theory posits that ocular drifts of fixational eye movements serve to reformat the visual input of natural images, so that the power of the input image is equalized across a range of spatial frequencies. This “spectral whitening” effect is postulated to improve the processing of high-spatial-frequency information and requires normal fixational eye movements. Given that people with macular disease exhibit abnormal fixational eye movements, do they also exhibit spectral whitening? To answer this question, we computed the power spectral density of movies of natural images translated in space and time according to the fixational eye movements (thus simulating the retinal input) of a group of observers with long-standing bilateral macular disease. Just as for people with normal vision, the power of the retinal input at low spatial frequencies was lower than that based on the 1/f2 relationship, demonstrating spectral whitening. However, the amount of whitening was much less for observers with macular disease when compared with age-matched controls with normal vision. A mediation analysis showed that the eccentricity of the preferred retinal locus adopted by these observers and the characteristics of ocular drifts are important factors limiting the amount of whitening. Finally, we did not find a normal aging effect on spectral whitening. Although these findings alone cannot form a causal link between macular disease and spectral properties of eye movements, they suggest novel potential means of modifying the characteristics of fixational eye movements, which may in turn improve functional vision for people with macular disease.

When we fixate a stationary target, our eyes generate miniature (or fixational) eye movements involuntarily. These fixational eye movements are classified as slow components (physiological drift, tremor) and microsaccades, which represent rapid, small-amplitude movements. Here we propose an integrated mathematical model for the generation of slow fixational eye movements and microsaccades. The model is based on the concept of self-avoiding random walks in a potential, a process driven by a self-generated activation field. The self-avoiding walk generates persistent movements on a short timescale, whereas, on a longer timescale, the potential produces antipersistent motions that keep the eye close to an intended fixation position. We introduce microsaccades as fast movements triggered by critical activation values. As a consequence, both slow movements and microsaccades follow the same law of motion; i.e., movements are driven by the self-generated activation field. Thus, the model contributes a unified explanation of why it has been a long-standing problem to separate slow movements and microsaccades with respect to their motion-generating principles. We conclude that the concept of a self-avoiding random walk captures fundamental properties of fixational eye movements and provides a coherent theoretical framework for two physiologically distinct movement types.

Fixation stability is known to be poor for people with macular disease and has been suggested as a contributing factor for the poor visual performance of these individuals. In this study, we examined the characteristics of the different components of fixational eye movements and determined the component that plays a major role in limiting fixation stability in people with macular disease. Sixteen observers with macular disease and 14 older adults with normal vision (control observers) monocularly fixated a small cross presented using a Rodenstock scanning laser ophthalmoscope, for trials of 30 seconds. The retinal image and the position of the cross on the retina were recorded digitally. Eye movements were extracted from the recorded videos at a sampling rate of 540 Hz using a cross-correlation technique. A velocity criterion of 8°/s was used to differentiate between slow drifts and microsaccades. Observers with macular disease demonstrated higher fixation instability, larger amplitudes of slow drifts and microsaccades, and lower drift velocities, when compared with older adults with normal vision. The velocity and the rate of microsaccades were comparable between the two groups of observers. Multiple linear regression analysis showed that the amplitude of microsaccades, and to a smaller extent, the amplitude of slow drifts, play a major role in limiting fixation stability. Fixation stability in people with macular disease is primarily limited by the amplitude of microsaccades, implying that rehabilitative strategies targeted at reducing the amplitude of microsaccades should improve fixation stability, and may lead to improved visual functions.

Even when the body is stationary, the whole retinal image is always in motion by fixational eye movements and saccades that move the eye between fixation points. Accumulating evidence indicates that the brain is equipped with specific mechanisms for compensating for the global motion induced by these eye movements. However, it is not yet fully understood how the retina processes global motion images during eye movements. Here we show that global motion images evoke novel coordinated firing in retinal ganglion cells (GCs). We simultaneously recorded the firing of GCs in the goldfish isolated retina using a multi-electrode array, and classified each GC based on the temporal profile of its receptive field (RF). A moving target that accompanied the global motion (simulating a saccade following a period of fixational eye movements) modulated the RF properties and evoked synchronized and correlated firing among local clusters of the specific GCs. Our findings provide a novel concept for retinal information processing during eye movements.

Visual perception is often conceptualized as the analysis of static images which are acquired during fixations. These images are then spatially decomposed into their basic components, which form the fundament of visual perception. Understanding these spatial mechanisms has been a central aim of pattern vision, and has led to a successful and widely adopted standard model of spatial vision. The spatial view on pattern vision, however, overlooks a key aspect of visual processing: the eyes are never still. Even during fixations, involuntary eye movements incessantly modulate the visual input. These eye movements challenge the assumption that visual processing can occur independently of motion. In recent years, empirical evidence has accumulated which suggests that fixational eye movements, particularly ocular drift, actively shape visual processing. Building on these findings, this thesis argues that ocular drift is essential to how the visual system encodes spatial structure, even in the absence of external motion. It calls for a shift from static to active, spatiotemporal models of pattern vision. To support this shift, it integrates computational modeling, psychophysics, and new experimental tools to explore how ocular drift influences edge and pattern perception. The first part of this thesis revisits foundational assumptions in spatial vision. In a first study, it presents a proof-of-concept model that extends a standard spatial vision model by ocular drift and temporal processing. The active model components facilitate edge extraction, but also reveal limitations in current datasets which cannot clearly distinguish between static and active accounts of pattern vision. In response, the next two studies introduce new software tools and a benchmark dataset that specifically target the spatial frequency selective mechanisms underlying pattern vision. Using this dataset, the fourth study explicitly contrasts spatial and active accounts of pattern vision. The results show that incorporating ocular drift improves predictions of human edge sensitivity and reveals that traditional models may rely on compensatory biases to account for the absence of these eye movements. The final study introduces a behavioral task in which participants trace edges in natural scenes. This approach enables the study of pattern vision in more naturalistic contexts while maintaining the analytical rigor of traditional psychophysics through signal detection theory. The resulting dataset supports both standard analyses and investigations into individual differences and the visual features that guide edge perception in real-world settings. Altogether, this thesis integrates insights from active perception into a mechanistically grounded framework of pattern vision. It redefines early visual processing as an active, embodied process shaped by the observer’s own movements. These findings challenge static models of early visual processes and advocate for a broader paradigm shift that places motion, context, and environmental interaction at the core of perception. Finally, it lays a foundation for future research into active models of vision, offering both theoretical direction and practical tools to study visual perception under more natural conditions.

Our eyes move constantly, even when we try to fixate our gaze. Fixational eye movements prevent and restore visual loss during fixation, yet the relative impact of each type of fixational eye movement remains controversial. For over five decades, the debate has focused on microsaccades, the fastest and largest fixational eye movements. Some recent studies have concluded that microsaccades counteract visual fading during fixation. Other studies have disputed this idea, contending that microsaccades play no significant role in vision. The disagreement stems from the lack of methods to determine the precise effects of microsaccades on vision versus those of other eye movements, as well as a lack of evidence that microsaccades are relevant to foveal vision. Here we developed a novel generalized method to determine the precise quantified contribution and efficacy of human microsaccades to restoring visibility compared with other eye movements. Our results indicate that microsaccades are the greatest eye movement contributor to the restoration of both foveal and peripheral vision during fixation. Our method to calculate the efficacy and contribution of microsaccades to perception can determine the strength of connection between any two physiological and/or perceptual events, providing a novel and powerful estimate of causal influence; thus, we anticipate wide-ranging applications in neuroscience and beyond.

Vision is one of the most important human senses, accounting for most of the external information pedestrians receive while crossing the street. However, distracted mobile phone usage during street crossing consumes pedestrians’ cognitive resources and diverts their visual attention. As a result, pedestrians may be unable to fully concentrate on observing the traffic environment and effectively planning their crossing path and behavior. This study evaluated the effect of pedestrian behavioral activities at street crossings on eye-movement (EM) characteristics. The crossing tasks were natural behavior, voice call, text messaging, and listening to music. The tasks were further categorized as simple or complex. A total of 29 participants were recruited in Nanjing: 18 males (62.1%) and 11 females (37.9%) with an average age of 23.59 years (SD = 2.44). The Friedman test was used to analyze differences in saccade frequency, fixation time, browsing number, and browsing time across different scenarios. Text messaging had the most significant impact on pedestrians’ EM characteristics, followed by voice call; music listening had a relatively weaker effect. Secondary task difficulty influenced the percentage of browsing, viewing, and to some extent gaze time. On the other hand, music rhythm and style only partially influenced the percentage of gaze and gaze time. Mobile phones substantially affected pedestrians’ EM characteristics and attention allocation for the same level of secondary task difficulty. These findings contribute to a better understanding of pedestrians’ visual characteristics under distracted mobile phone usage conditions and provide valuable insights for developing appropriate measures to enhance pedestrian safety.

The study of the saccadic system has focused mainly on neurons active before the beginning of saccades, in order to determine their contribution in movement planning and execution. However, most oculomotor structures contain also neurons whose activity starts only after the onset of saccades, the maximum of their activity sometimes occurring near saccade end. Their characteristics are still largely unknown. We investigated pretectal neurons with saccade-related activity in the alert cat during eye movements towards a moving target. They emitted a high-frequency burst of action potentials after the onset of saccades, irrespective of their direction, and will be referred to as "pretectal saccade-related neurons". The delay between saccade onset and cell activity varied from 17 to 66 ms on average. We found that burst parameters were correlated with the parameters of saccades; the peak eye velocity was correlated with the peak of the spike density function, the saccade amplitude with the number of spikes in the burst, and burst duration increased with saccade duration. The activity of six pretectal saccade-related neurons was studied during smooth pursuit at different velocities. A correlation was found between smooth pursuit velocity and mean firing rate. A minority of these neurons (2/6) were also visually responsive. Their visual activity was proportional to the difference between eye and target velocity during smooth pursuit (retinal slip). These results indicate that the activity of pretectal saccade-related neurons is correlated with the characteristics of eye movements. This finding is in agreement with the known anatomical projections from premotor regions of the saccadic system to the pretectum.

A camera orientation system has been developed to be used as an artificial eye e.g. in the head of humanoid robots or as a head-mounted gaze-driven camera orientation device. In this paper simulation experiments with natural eye movements, such as fixations, smooth pursuit and saccadic eye movements are carried out. The derived models are primary used to prove that the selected piezo-actuators are able to satisfy the high dynamic requirements of the human eye movements. Additionally these models can be integrated in the device as well as in the controller design phase.

BackgroundEye movement is a vital indicator of neurodegenerative diseases, brain health, and behavior. However, existing knowledge is limited to patient populations or cross-sectional samples. Little is known about eye movement in association with longitudinal cognitive and mobility decline in aging.ObjectiveInvestigate relationships between eye movement features with cognitive impairment, including Alzheimer's disease (AD), and longitudinal decline in cognition and mobility.MethodsIn 543 Baltimore Longitudinal Study of Aging participants (mean age = 71 years), we examined associations of eye movements with cognitive impairment of any severity, vascular conditions, and falls using logistic regression, and up to 18-year longitudinal changes in cognition and mobility using linear mixed-effects models. Four eye movement features (saccade, smooth pursuit, vergence, optokinetic nystagmus) were derived from a portable eye-tracking perimeter (Neurolign Dx100) using machine learning Least Absolute Shrinkage Selection Operator regression.ResultsHigher saccade, smooth pursuit, and vergence were bivariately or marginally associated with lower odds of cognitive impairment, including AD, and vascular diseases. In age- and sex-adjusted models, higher saccade was associated with slower declines in cognition (attention: Trail Making Test-Part A), mobility, and balance. Higher smooth pursuit was associated with slower decline in mobility and balance. Higher vergence was associated with slower cognitive decline (executive function: Trail Making Test-Part B; visuoperceptual speed: Digit Symbol Substitution Test). Higher optokinetic nystagmus was associated with lower odds of falls and slower decline in balance.ConclusionsSelect eye movement features may be indicators of age-related cognitive and mobility decline. Future studies are warranted to investigate underlying neuroimaging markers and brain pathology.

Besides allowing us to perceive our surroundings, eye movements are also a window into our mind and a rich source of information on who we are, how we feel, and what we do. Here we show that eye movements during an everyday task predict aspects of our personality. We tracked eye movements of 42 participants while they ran an errand on a university campus and subsequently assessed their personality traits using well-established questionnaires. Using a state-of-the-art machine learning method and a rich set of features encoding different eye movement characteristics, we were able to reliably predict four of the Big Five personality traits (neuroticism, extraversion, agreeableness, conscientiousness) as well as perceptual curiosity only from eye movements. Further analysis revealed new relations between previously neglected eye movement characteristics and personality. Our findings demonstrate a considerable influence of personality on everyday eye movement control, thereby complementing earlier studies in laboratory settings. Improving automatic recognition and interpretation of human social signals is an important endeavor, enabling innovative design of human–computer systems capable of sensing spontaneous natural user behavior to facilitate efficient interaction and personalization.

Electro-Oculography (EOG) Examination of Eye Movements