Fast Eye Research Articles

Tau P301S Transgenic Mice Develop Gait and Eye Movement Impairments That Mimic Progressive Supranuclear Palsy.

Progressive supranuclear palsy (PSP) is a neurodegenerative disorder with an estimated prevalence of 5-7 people in 100,000. Clinically characterized by impairments in gait, balance, and eye movements, as well as aggregated Tau pathology, PSP leads to death in approximately 5-8 years. No disease-modifying treatments are currently available. The contribution of Tau pathology to the symptoms of patients with PSP is poorly understood, in part due to lack of a rodent model that recapitulates characteristic aspects of PSP. Here, we assessed the hTau.P301S mouse for key clinical features of PSP, finding progressive impairments in balance and gait coordination. Additionally, we found impairments in fast vertical eye movements, one of the most distinctive features of PSP. Across animals, we found that Tau pathology in motor control regions correlated with motor deficits. These findings highlight the utility of the hP301S mouse in modeling key aspects of PSP.

E-Gaze: Gaze Estimation With Event Camera.

Near-eye gaze estimation is a task that maps the recording of an eye captured by an adjacent camera to the direction of a person's gaze in space. In contrast to frame-based cameras, event cameras are characterized by high sensing rates, low latency, sparse asynchronous data outputs, and high dynamic range, which are well suited for recording the fast eye movements. However, algorithms and system designs that operate on frame-based cameras are not applicable to event-based data, due to the natural differences in the data characteristics. In this work, we study the pattern of near-eye event-based data streams and extract eye features to estimate gaze. First, by analyzing eye parts and movements, and harnessing the polar, spatial, and temporal distribution of the events, we introduce a real-time pipeline to extract pupil features. Second, we present a recurrent neural network with a proposed coordinate-to-angle loss function to accurately estimate gaze from pupil feature sequence. We demonstrated that our system achieves accurate real-time estimation with angular accuracy of 0.46 ° and update rates of 950 Hz, thus opening up avenues for novel applications. To our knowledge, this is the first system that operates only on event-based data to perform gaze estimation.

Effects of post-saccadic oscillations on visual processing times.

Saccadic eye movements enable us to search for the target of interest in a crowded scene or, in the case of goal-directed saccades, to simply bring the image of the peripheral target to the very centre of the fovea. This mechanism extends the use of the superior image processing performance of the fovea over a large visual field. We know that visual information is processed quickly at the end of each saccade but estimates of the times involved remain controversial. This study aims to investigate the processing of visual information during post fixation oscillations of the eyeball. A new psychophysical test measures the combined eye movement response latencies, including fixation duration and visual processing times. When the test is used in conjunction with an eye tracker, each component that makes up the 'integrated saccade latency' time, from the onset of the peripheral stimulus to the correct interpretation of the information carried by the stimulus, can be measured and the discrete components delineated. The results show that the time required to process and encode the stimulus attribute of interest at the end of a saccade is longer than the time needed to carry out the same task in the absence of an eye movement. We propose two principal hypotheses, each of which can account for this finding. 1. The known inhibition of afferent retinal signals during fast eye movements extends beyond the end point of the saccade. 2. The extended visual processing times measured when saccades are involved are caused by the transient loss of spatial resolution due to eyeball instability during post-saccadic oscillations. The latter can best be described as retinal image smear with greater loss of spatial resolution expected for stimuli of low luminance contrast.

Eye movement function captured via an electronic tablet informs on cognition and disease severity in Parkinson’s disease

Studying the oculomotor system provides a unique window to assess brain health and function in various clinical populations. Although the use of detailed oculomotor parameters in clinical research has been limited due to the scalability of the required equipment, the development of novel tablet-based technologies has created opportunities for fast, easy, cost-effective, and reliable eye tracking. Oculomotor measures captured via a mobile tablet-based technology have previously been shown to reliably discriminate between Parkinson’s Disease (PD) patients and healthy controls. Here we further investigate the use of oculomotor measures from tablet-based eye-tracking to inform on various cognitive abilities and disease severity in PD patients. When combined using partial least square regression, the extracted oculomotor parameters can explain up to 71% of the variance in cognitive test scores (e.g. Trail Making Test). Moreover, using a receiver operating characteristics (ROC) analysis we show that eye-tracking parameters can be used in a support vector classifier to discriminate between individuals with mild PD from those with moderate PD (based on UPDRS cut-off scores) with an accuracy of 90%. Taken together, our findings highlight the potential usefulness of mobile tablet-based technology to rapidly scale eye-tracking use and usefulness in both research and clinical settings by informing on disease stage and cognitive outcomes.

Fast eye centre localization using combined unsupervised technics

Eye movements offer precious information about persons? state. Video surveillance, marketing, driver fatigue as well as medical diagnosis assistance applications manage eye behavior. We propose a new method for efficiently detecting eye movement. In this paper, we combine circle eye model with eye feature method to improve the accuracy. A set of detectors estimate the eyes centers to increase the localization rate. As a pre-processing stage, the mean of the edges yields the center of the two eye regions. Image treatment operations reduce the ROI. A Circle Hough Transform (CHT) algorithm is adopted in a modified version as a detector to find the circle eye in the image; the circle center found represents the eye's pupil estimation. We introduced the Maximally Stable Extremal Region (MSER) as a second detector, which has never been used for eye localization. Invariant to continuous geometric transformations and affine intensity changes and detected at several scales, MSERs efficiently detect regions of interest, in our case eye regions, and precisely, their centers. Ellipses fit MSERs, and their centroid estimation match eyes center. We demonstrate that the true eye centers can be found by combining these methods. The validation of the proposed method is performed on a very challenging BioID base. The proposed approach compares well with existing state-of-the-art techniques and achieves an accuracy of 82.53% on the BioID database when the normalized error is less than 0.05, without prior knowledge or any learning model.

Recording and interpretation of ocular movements: saccades, smooth pursuit, and optokinetic nystagmus

The ultimate role of ocular movements is to keep the image of an object within the fovea and thereby prevent image slippage on the retina. Accurate evaluations of eye movements provide very useful information for understanding the functions of the oculomotor system and determining abnormalities therein. Such evaluations also play an important role in enabling accurate diagnoses by identifying the location of lesions and discriminating from other diseases. There are various types of ocular movements, and this article focuses on saccades, fast eye movements, smooth pursuit, and slow eye movements, which are the most important types of eye movements used in evaluations performed in clinical practice.

Eye growth pattern of myopic children wearing spectacle lenses with aspherical lenslets compared with non-myopic children.

To evaluate eye growth of children wearing spectacle lenses with highly aspherical lenslets (HAL), slightly aspherical lenslets (SAL) and single-vision lenses (SVL) compared to eye growth patterns in non-myopes in Wenzhou, China. The randomised trial had 170 myopic children (aged 8-13 years) randomly assigned to the HAL, SAL or SVL group. Normal eye growth was examined using 700 non-myopic schoolchildren (aged 7-9 years) in the Wenzhou Medical University-Essilor Progression and Onset of Myopia (WEPrOM) cohort study using logistic function models. Slow, normal and fast eye growth was defined as range of values <25th, 25th-75th and >75th percentiles, respectively. The predicted upper limits of slow eye growth (25th percentile) among non-myopes aged 7-10 years and 11-13 years were 0.20-0.13 and 0.08-0.01 mm (after 2-year period; 0.37-0.33 and 0.29-0.14 mm), respectively, while the upper limits of normal eye growth (75th percentile) were 0.32-0.31 and 0.28-0.10 mm (after 2-year period; 0.58-0.55 and 0.50-0.24 mm), respectively. The 2-year trial had 157 children, 96 of whom wore their lenses full time (everyday ≥12 h/day). The mean 2-year axial length change for HAL, SAL and SVL was 0.34, 0.51 and 0.69 mm (0.28, 0.46 and 0.69 mm in full-time wear), respectively. Slow eye growth was found in 35%, 17% and 2% (44%, 29% and 3% in full-time wear); normal eye growth in 35%, 26% and 12% (44%, 32% and 9% in full-time wear) and fast eye growth in 30%, 57% and 86% (12%, 39% and 88% in full-time wear), respectively (p < 0.001). The eye growth pattern in approximately 90% wearing HAL full time (compared with about 10% wearing SVL full time) was similar or slower than that of non-myopic children both after 1- and 2-year periods.

Opsoclonus and ocular flutter: evaluation and management.

Opsoclonus and ocular flutter are saccadic intrusions characterized by spontaneous, back-to-back, fast eye movements (saccades) that oscillate about the midline of central visual fixation without intervening inter-saccadic intervals. When this type of movement occurs exclusively in the horizontal plane, it is called ocular flutter. When it occurs in multiple planes (i.e. horizontal, vertical, and torsional) it is called opsoclonus. The most common etiologic categories are parainfectious and paraneoplastic diseases. Less common are toxic-metabolic, traumatic, or idiopathic origins. The mechanism of these movements relates to dysfunction of brainstem and cerebellar machinery involved in the generation of saccades. In this review, we discuss the characteristics of opsoclonus and ocular flutter, describe approaches to clinical evaluation and management of the patient with opsoclonus and ocular flutter, and review approaches to therapeutic intervention. Recent publications demonstrated eye position-dependent opsoclonus present only in left gaze, which may be related to dysfunction of frontal eye fields or structures in the cerebellar vermis. Opsoclonus and ocular flutter originate from a broad array of neuropathologies and have value from both a neuroanatomic and etiologic perspective.

Saccadic eye movement speed is related to variations in phantom array effect visibility

The phantom array effect is one of the temporal light artefacts that can decrease performance and increase fatigue. The phantom array effect visibility shows large individual differences; however, the dominant factors that can explain these individual differences remain unclear. We investigated the relationship between saccadic eye movement speed and phantom array visibility at two different angles and four different directions of saccadic eye movement. The peak speed of saccadic eye movement and the phantom array effect visibility were measured at different modulation frequencies of the light source. Our results show that phantom array visibility increased as eye movement speed increased; the phantom array visibility was higher at a wide viewing angle with fast eye movement speed than at a narrow viewing angle. Moreover, when clustered into subgroups according to individual eye movement speed, the mean speed of the saccadic eye movement of each subgroup is related to the variations in the visibility of the phantom array effect of the subgroup. Therefore, saccadic eye movement speed is related to variations in phantom array effect visibility.

Electroencephalography (EEG) eye state classification using learning vector quantization and bagged trees

The analysis of Electroencephalography (EEG) signals has been an effective way of eye state identification. Its significance is highlighted by studies that examined the classification of eye states using machine learning techniques. In previous studies, supervised learning techniques have been widely used in EEG signals analysis for eye state classification. Their main goal has been the improvement of classification accuracy through the use of novel algorithms. The trade-off between classification accuracy and computation complexity is an important task in EEG signals analysis. In this paper, a hybrid method that can handle multivariate signals and non-linear is proposed with supervised and un-supervised learning to achieve a fast EEG eye state classification with high prediction accuracy to provide real-time decision-making applicability. We use the Learning Vector Quantization (LVQ) technique and bagged tree techniques. The method was evaluated on a real-world EEG dataset which included 14976 instances after the removal of outlier instances. Using LVQ, 8 clusters were generated from the data. The bagged tree was applied on 8 clusters and compared with other classifiers. Our experiments revealed that LVQ combined with the bagged tree provides the best results (Accuracy = 0.9431) compared with the bagged tree, CART (Classification And Regression Tree) (Accuracy = 0.8200), LDA (Linear Discriminant Analysis) (Accuracy = 0.7931), Random Trees (Accuracy = 0.8311), Naïve Bayes (Accuracy = 0.8331) and Multilayer Perceptron (Accuracy = 0.7718), which demonstrates the effectiveness of incorporating ensemble learning and clustering approaches in the analysis of EEG signals. We also provided the time complexity of the methods for prediction speed (Observation/Second). The result showed that LVQ + Bagged Tree provides the best result for prediction speed (58942 Obs/Sec) in relation to Bagged Tree (28453 Obs/Sec), CART (27784 Obs/Sec), LDA (26435 Obs/Sec), Random Trees (27921), Naïve Bayes (27217) and Multilayer Perceptron (24163).

Artifact reduction in lenslet array near-eye displays

Lenslet array near-eye displays are a revolutionary technology that generates a virtual image in the field of view of the observer. Although this technology is advantageous in creating compact near-eye displays, undesirable artifacts occur when the user pupil moves outside of the pupil practical movable region (PPMR). Even with dynamic image updating based on eye-tracking techniques, artifacts can still be perceived when human eyes turn rapidly. To enlarge PPMR, we proposed a new rendering method in previous work. To improve the rendering speed in the eye tracking system, look-up tables are used. The disadvantage of the onboard system is the large memory consumption. In this study, we analyzed the system parameters of the incident pupil and pupil margin light columns, the feasibility of the optimized system, and evaluated the optimized system that can adapt to the maximum velocity of the saccadic pupil movement. We optimized the rendering method to reduce memory consumption in the process of generating microdisplay images. In addition, we provide GPU rendering method to improve system speed and reduce system latency to meet the maximum human eye rotation speed. We conducted user studies to evaluate the effect of the method using the optimized rendering method combined with eye tracking to reduce artifacts for fast eye rotation on different images and videos. Results showed that our method effectively reduced artifacts via the optimized rendering method with eye tracking, which adapted to faster human eye movements.

Clinical Saccadometry: Establishing Evaluative Standards Using a Simplified Video Oculography Protocol in the Adult Population.

Saccadometry is an advanced ocular motor test battery that allows for the functional evaluation of the varied brain regions and circuits involved in the generation of fast, purposeful, and accurate saccadic eye movements. The test battery is composed of prosaccade (PS) and antisaccade (AS) tests that progressively increase cognitive demand. Existing saccadometry protocols qualitatively describe trends across the lifespan, but have not been widely adopted by clinicians. The aims of this study are to design an efficient and simplified clinical saccadometry protocol using video oculography (VOG) equipment and establish associated evaluative standards across the lifespan. Data were reported on 273 adults ages 18 to 69 years. Evaluative data on four measures: directional error rate (DE), latency (Lat), peak velocity (Vel), and accuracy (Acc) during PS and AS measurements were provided. Age-group differences were found in Lat (p < 0.01) and Vel (p = 0.04) during PS and age-group differences were found in DE (p = 0.04), Lat (p < 0.01) and Vel (p < 0.01) during AS. Gender differences were found in DE (p = 0.01) and Lat (p < 0.01) during AS. This study established a standardized and time-efficient protocol with evaluative standards for individuals ages 18 to 69 years old to enable the use of saccadometry as an objective measure in the clinic. Saccadometry allows clinicians to look beyond the traditional saccade test and evaluate complex oculomotor and cognitive functions that will better help clinicians differentiate between peripheral and central diagnoses.

Detection of insomnia using advanced complexity and entropy features of sleep stage data of EEG recordings

Sleep disorders affect the physical ability in the function under mental, emotional, and physical forms depending upon its intensity. These abnormalities are observed on the basis of structure of sleep. Most prevalent sleep disorders are insomnia, bruxism, depression, and narcolepsy. Common issues in sleep disorder are sleeplessness, irregular leg movements, problems with fast eye movement behavior and breathing abnormalities. Therefore, an early-stage therapy that might save a patient's life depends on a precise diagnosis and categorization. The much more sensitive as well as significant bio-signal is electroencephalographic (EEG) signal. It has capacity to record sleep-sensitive brain activity. We used an available EEG database which had recordings divided into different types of sleep disturbances as well as a healthy control group. Popular sensor's EEG brain function has been examined. Ultimately, using patterns taken from EEG data, a categorization AI model was created. Extracted characteristics worked well as a biomarker for identifying sleep problems when combined with an AI classifier.

Supervised approach based sleep disorder detection using non - Linear dynamic features (NLDF) of EEG

Depending on its intensity, sleep disorders can affect a person's ability to function mentally, emotionally, and physically. These are medical abnormalities of the subject's sleep structure. Most prevalent ones are bruxism, sleep problems, depression, and narcolepsy. A greater chance of acquiring sleep issues in the elderly includes sleeplessness, irregular leg movements, problems with fast eye movement behaviour and breathing abnormalities. Therefore, an early stage therapy that might save a patient's life depends on a precise diagnosis and categorization. The much more sensitive as well as significant bio-signal is electroencephalographic (EEG) signal. It has the capacity to record sleep-sensitive brain activity. We used an available EEG database which had recordings divided into different types of sleep disturbances as well as a healthy control group. Popular sensor's EEG brain function has been examined. Ultimately, using patterns taken from EEG data, a categorization AI model was created. Extracted characteristics worked well as a biomarker for identifying sleep problems when combined with an AI classifier.

Fast Saccadic Eye Movements Contribute to the Worsened Postural Sway in Older Adults Who Have Experienced Falls.

The purpose of this study was to examine changes and between-group differences in postural sway during saccadic eye movement in older adults (n = 152). The participants were stratified into older adults who have experienced a fall (n = 58) (faller group) and those who have not (n = 94) (non-faller group). We measured postural sway during saccadic eye movement. Saccadic eye movement speed was such that the target was displayed at 0.5 Hz, 2 Hz, and 3 Hz. Postural sway was measured based on path length, velocity, and length between the maximal and minimal position of center of pressure in mediolateral and anteroposterior direction. In the faller group, path length, velocity, and mediolateral displacement of the center of pressure increased significantly during 3 Hz saccadic eye movement stimulation. However, in the non-faller group, there was no significant change in the center of pressure parameters during saccadic eye movement stimulation. Mediolateral displacement of the center of pressure increased significantly in both groups during saccadic eye movement, especially at 3 Hz. Therefore, rapid saccadic eye movement stimulation can contribute to the worsened postural sway in older adults who have experienced falls, and rapid external environmental stimuli may contribute to the deterioration of the upright standing stability in older adults.

Slower velocity perception with stronger optokinetic nystagmus: A paradoxical perception in virtual reality

BackgroundOptokinetic nystagmus (OKN) was studied in an immersive virtual reality (VR) environment with both typical optokinetic stimulation (OKs) wherein the head-tracking is active (similar to be sitting in front of a rotating drum) or a unique stimulus (VR-OKs) wherein the head-tracking is turned off, so head movements do not update the visual image (which moves with the head). ObjectiveTo study both the perception of the stimulus velocity and eye movements while subjects rotated their head from side to side and the visual scene was either a typical OKs or VR-OKs. Methods9 healthy participants (aged 23 ± 2.4 y/o) had head and eye movements recorded under typical OKs and VR-OKS while smoothly rotating their head horizontally from side to side. Stimulation was delivered using a virtual reality setup on top of an eye movements recording system. ResultsUnder VR-OKs participants perceived faster stimulus velocity when the head and stimulus had the same direction as compared to the head and stimulus in opposite directions. When the head turned in the same direction as the stimulus, there were fewer fast phase eye movements than when it rotated counter to stimulus motion direction. Conversely, with typical OKs, participants perceived faster stimulus velocity when the head and stimulus had opposite directions as compared to the head and stimulus having the same direction. ConclusionsThe seemingly paradoxical results in which slower stimulus velocity is perceived in tandem with stronger nystagmus can be explained by the simultaneous activation of the Vestibulo-Ocular Reflex and OKN in accordance with the various visual and vestibular stimuli.

Low Gain Values of the Vestibulo-Ocular Reflex Can Optimize Retinal Image Slip.

The angular vestibulo-ocular reflex (aVOR) stabilizes retinal images by counter-rotating the eyes during head rotations. Perfect compensatory movements would thus rotate the eyes exactly opposite to the head, that is, eyes vs. head would exhibit a unity gain. However, in many species, but also in elderly humans or patients with a history of vestibular damage, the aVOR is far from compensatory with gains that are in part considerably lower than unity. The reason for this apparent suboptimality is unknown. Here, we propose that low VOR gain values reflect an optimal adaptation to sensory and motor signal variability. According to this hypothesis, gaze stabilization mechanisms that aim at minimizing the overall retinal image slip must consider the effects of (1) sensory and motor noise and (2) dynamic constraints of peripheral and central nervous processing. We demonstrate that a computational model for optimizing retinal image slip in the presence of such constraints of signal processing in fact predicts gain values smaller than unity. We further show specifically for tadpoles of the clawed toad, Xenopus laevis with particularly low gain values that previously reported VOR gains quantitatively correspond to the observed variability of eye movements and thus constitute an optimal adaptation mechanism. We thus hypothesize that lower VOR gain values in elderly human subjects or recovered patients with a history of vestibular damage may be the sign of an optimization given higher noise levels rather than a direct consequence of the damage, such as an inability of executing fast compensatory eye movements.

An Effective Algorithm to Analyze the Optokinetic Nystagmus Waveforms from a Low-Cost Eye Tracker.

Objective: Most neurological diseases are usually accompanied by changes in the oculomotor nerve. Analysis of different types of eye movements will help provide important information in ophthalmology, neurology, and psychology. At present, many scholars use optokinetic nystagmus (OKN) to study the physiological phenomenon of eye movement. OKN is an involuntary eye movement induced by a large moving surrounding visual field. It consists of a slow pursuing eye movement, called “slow phase” (SP), and a fast re-fixating saccade eye movement, called “fast phase” (FP). Non-invasive video-oculography has been used increasingly in eye movement research. However, research-grade eye trackers are often expensive and less accessible to most researchers. Using a low-cost eye tracker to quantitatively measure OKN eye movement will facilitate the general application of eye movement research. Methods & Results: We design an analytical algorithm to quantitatively measure OKN eye movements on a low-cost eye tracker. Using simple conditional filtering, accurate FP positions can be obtained quickly. The high-precision FP recognition rate is of great help for the subsequent calculation of eye movement analysis parameters, such as mean slow phase velocity (MSPV), which is beneficial as a reference index for patients with strabismus and other eye diseases. Conclusions: Experimental results indicate that the proposed method achieves faster and better results than other approaches, and can provide an effective algorithm to calculate and analyze the FP position of OKN waveforms.

The Sunburst illusion

We report a new visual illusion. When a Mackay Ray figure is observed in paracentral vision or near peripheral vision, a fast but smooth pursuit eye movement produces an impression of bursting of a dazzling light in the center of the figure. We call this effect the Sunburst illusion. We have included movies demonstrating the effects of changing the speed and path of smooth eye movement, saccades, luminance contrast, and color combinations.

Research article summary: “Properties of fast vergence eye movements and horizontal saccades in athletes”

The Aim of this study is to sum up the research paper entitled “Properties of fast vergence eye movements and horizontal saccades in athletes” published by Yoshimura et al. in Physiology and Behavior ( https://doi.org/10.1016/j.physbeh.2021.113397 ). L’objectif de cet article est de résumer l’étude scientifique intitulée « Properties of fast vergence eye movements and horizontal saccades in athlete » publiée par l’équipe de Yoshimura et collaborateurs dans la revue Physiology and Behavior ( https://doi.org/10.1016/j.physbeh.2021.113397 )