What's on TV? Detecting age-related neurodegenerative eye disease using eye movement scanpaths

A review of machine learning in scanpath analysis for passive gaze-based interaction

The scanpath is an important concept in eye tracking. It refers to a person's eye movements over a period of time, commonly represented as a series of alternating fixations and saccades. Machine learning has been increasingly used for the automatic interpretation of scanpaths over the past few years, particularly in research on passive gaze-based interaction, i.e., interfaces that implicitly observe and interpret human eye movements, with the goal of improving the interaction. This literature review investigates research on machine learning applications in scanpath analysis for passive gaze-based interaction between 2012 and 2022, starting from 2,425 publications and focussing on 77 publications. We provide insights on research domains and common learning tasks in passive gaze-based interaction and present common machine learning practices from data collection and preparation to model selection and evaluation. We discuss commonly followed practices and identify gaps and challenges, especially concerning emerging machine learning topics, to guide future research in the field.

Does the sampling frequency of an eye tracker affect the detection of glaucomatous visual field loss?

PURPOSE

Evidence suggests that eye movements have potential as a tool for detecting glaucomatous visual field defects. This study evaluated the influence of sampling frequency on eye movement parameters in detecting glaucomatous visual field defects during a free-viewing task.

METHODS

We investigated eye movements in two sets of experiments: (a) young adults with and without simulated visual field defects and (b) glaucoma patients and age-matched controls. In Experiment 1, we recruited 30 healthy volunteers. Among these, 10 performed the task with a gaze-contingent superior arcuate (SARC) scotoma, 10 performed the task with a gaze-contingent biarcuate (BARC) scotoma and 10 performed the task without a simulated scotoma (NoSim). The experimental task involved participants freely exploring 100 images, each for 4 s. Eye movements were recorded using the LiveTrack Lightning eye-tracker (500 Hz). In Experiment 2, we recruited 20 glaucoma patients and 16 age-matched controls. All participants underwent similar experimental tasks as in Experiment 1, except only 37 images were shown for exploration. To analyse the effect of sampling frequency, data were downsampled to 250, 120 and 60 Hz. Eye movement parameters, such as the number of fixations, fixation duration, saccadic amplitude and bivariate contour ellipse area (BCEA), were computed across various sampling frequencies.

RESULTS

Two-way ANOVA revealed no significant effects of sampling frequency on fixation duration (simulation, p = 0.37; glaucoma patients, p = 0.95) and BCEA (simulation, p = 0.84; glaucoma patients: p = 0.91). BCEA showed good distinguishability in differentiating groups across different sampling frequencies, whereas fixation duration failed to distinguish between glaucoma patients and controls. Number of fixations and saccade amplitude showed variations with sampling frequency in both simulations and glaucoma patients.

CONCLUSION

In both simulations and glaucoma patients, BCEA consistently differentiated them from controls across various sampling frequencies.

Data on eye movements of glaucoma patients with asymmetrical visual field loss during free viewing

This paper describes data from Asfaw at al. [1], which examined the eye movements of glaucoma patients (n=15) with pronounced asymmetrical vision loss (visual field loss worse in one eye). This allows for within-subject comparisons between the better and worse eye, thereby controlling for the effects of individual differences between patients. All patients had a clinical diagnosis of open angle glaucoma (OAG). Participants were asked to look at images of nature monocularly (free viewing; fellow eye patched) while gaze was recorded at 1000 Hz using a remote eye tracker (EyeLink 1000). Raw and processed eye tracking data are provided. In addition, clinical (visual acuity, contrast sensitivity and visual field) and demographic information (age, sex) are provided.

A novel eye-movement impairment in multiple sclerosis indicating widespread cortical damage

In multiple sclerosis, remyelination trials have yet to deliver success like that achieved for relapse rates with disease course modifying treatment trials. The challenge is to have a clinical, functional outcome measure. Currently, there are none that have been validated, other than visual evoked potentials in optic neuritis. Like vision, quick eye movements (saccades) are heavily dependent on myelination. We proposed that it is possible to extrapolate from demyelination of the medial longitudinal fasciculus in the brainstem to quantitative assessment of cortical networks governing saccadic eye movements in multiple sclerosis. We have developed and validated a double-step saccadic test, which consists of a pair of eye movements towards two stimuli presented in quick succession (the demonstrate eye movement networks with saccades protocol). In this single-centre, cross-sectional cohort study we interrogated the structural and functional relationships of double-step saccades in multiple sclerosis. Data were collected for double-step saccades, cognitive function (extended Rao's Brief Repeatable Battery), disability (Expanded Disability Status Scale) and visual functioning in daily life (National Eye Institute Visual Function Questionnaire). MRI was used to quantify grey matter atrophy and multiple sclerosis lesion load. Multivariable linear regression models were used for analysis of the relationships between double-step saccades and clinical and MRI metrics. We included 209 individuals with multiple sclerosis (mean age 54.3 ± 10.5 years, 58% female, 63% relapsing-remitting multiple sclerosis) and 60 healthy control subjects (mean age 52.1 ± 9.2 years, 53% female). The proportion of correct double-step saccades was significantly reduced in multiple sclerosis (mean 0.29 ± 0.22) compared to controls (0.45 ± 0.22, P < 0.001). Consistent with this, there was a significantly larger double-step dysmetric saccadic error in multiple sclerosis (mean vertical error -1.18 ± 1.20°) compared to controls (-0.54 ± 0.86°, P < 0.001). Impaired double-step saccadic metrics were consistently associated with more severe global and local grey matter atrophy (correct responses-cortical grey matter: β = 0.42, P < 0.001), lesion load (vertical error: β = -0.28, P < 0.001), progressive phenotypes, more severe physical and cognitive impairment (correct responses-information processing: β = 0.46, P < 0.001) and visual functioning. In conclusion, double-step saccades represent a robust metric that revealed a novel eye-movement impairment in individuals with multiple sclerosis. Double-step saccades outperformed other saccadic tasks in their statistical relationship with clinical, cognitive and visual functioning, as well as global and local grey matter atrophy. Double-step saccades should be evaluated longitudinally and tested as a potential novel outcome measure for remyelination trials in multiple sclerosis.

[Research on eye movement data classification using support vector machine with improved whale optimization algorithm]

When performing eye movement pattern classification for different tasks, support vector machines are greatly affected by parameters. To address this problem, we propose an algorithm based on the improved whale algorithm to optimize support vector machines to enhance the performance of eye movement data classification. According to the characteristics of eye movement data, this study first extracts 57 features related to fixation and saccade, then uses the ReliefF algorithm for feature selection. To address the problems of low convergence accuracy and easy falling into local minima of the whale algorithm, we introduce inertia weights to balance local search and global search to accelerate the convergence speed of the algorithm and also use the differential variation strategy to increase individual diversity to jump out of local optimum. In this paper, experiments are conducted on eight test functions, and the results show that the improved whale algorithm has the best convergence accuracy and convergence speed. Finally, this paper applies the optimized support vector machine model of the improved whale algorithm to the task of classifying eye movement data in autism, and the experimental results on the public dataset show that the accuracy of the eye movement data classification of this paper is greatly improved compared with that of the traditional support vector machine method. Compared with the standard whale algorithm and other optimization algorithms, the optimized model proposed in this paper has higher recognition accuracy and provides a new idea and method for eye movement pattern recognition. In the future, eye movement data can be obtained by combining it with eye trackers to assist in medical diagnosis.

Impact of glaucoma on the spatial frequency processing of scenes in central vision

Glaucoma is an eye disease characterized by a progressive vision loss usually starting in peripheral vision. However, a deficit for scene categorization is observed even in the preserved central vision of patients with glaucoma. We assessed the processing and integration of spatial frequencies in the central vision of patients with glaucoma during scene categorization, considering the severity of the disease, in comparison to age-matched controls. In the first session, participants had to categorize scenes filtered in low-spatial frequencies (LSFs) and high-spatial frequencies (HSFs) as a natural or an artificial scene. Results showed that the processing of spatial frequencies was impaired only for patients with severe glaucoma, in particular for HFS scenes. In the light of proactive models of visual perception, we investigated how LSF could guide the processing of HSF in a second session. We presented hybrid scenes (combining LSF and HSF from two scenes belonging to the same or different semantic category). Participants had to categorize the scene filtered in HSF while ignoring the scene filtered in LSF. Surprisingly, results showed that the semantic influence of LSF on HSF was greater for patients with early glaucoma than controls, and then disappeared for the severe cases. This study shows that a progressive destruction of retinal ganglion cells affects the spatial frequency processing in central vision. This deficit may, however, be compensated by increased reliance on predictive mechanisms at early stages of the disease which would however decline in more severe cases.

Eye Movement Abnormalities in Glaucoma Patients: A Review

Glaucoma is a common condition that relies on careful clinical assessment to diagnose and determine disease progression. There is growing evidence that glaucoma is associated not only with loss of retinal ganglion cells but also with degeneration of cortical and subcortical brain structures associated with vision and eye movements. The effect of glaucoma pathophysiology on eye movements is not well understood. In this review, we examine the evidence surrounding altered eye movements in glaucoma patients compared to healthy controls, with a focus on quantitative eye tracking studies measuring saccades, fixation, and optokinetic nystagmus in a range of visual tasks. The evidence suggests that glaucoma patients have alterations in several eye movement domains. Patients exhibit longer saccade latencies, which worsen with increasing glaucoma severity. Other saccadic abnormalities include lower saccade amplitude and velocity, and difficulty inhibiting reflexive saccades. Fixation is pathologically altered in glaucoma with reduced stability. Optokinetic nystagmus measures have also been shown to be abnormal. Complex visual tasks (eg reading, driving, and navigating obstacles), integrate these eye movements and result in behavioral adaptations. The review concludes with a summary of the evidence and recommendations for future research in this emerging field.

Developing a Screening Tool for Areas of Abnormal Central Vision Using Visual Stimuli With Natural Scene Statistics

Purpose

Previous studies show that some visual field (VF) defects are detectable from visual search behavior; for example, when watching video. Here, we developed and tested a VF testing approach that measures the number of fixations to find targets on a background with spatial frequency content similar to natural scenes.

Methods

Twenty-one older controls and 20 people with glaucoma participated. Participants searched for a Gabor (6 c/°) that appeared in one of 25 possible locations within a 15° (visual angle) 1/f noise background (RMS contrast: 0.20). Procedure performance was assessed by calculating sensitivity and specificity for different combinations of control performance limits (p = 95%, 98%, 99%), number of target locations with fixations outside control performance limits (k = 0 to 25) and number of repeated target presentations (n = 1 to 20).

Results

Controls made a median of two to three fixations (twenty-fifth to seventy-fifth percentile: two to four) to locate the target depending on location. A VF was flagged “abnormal” when the number of fixations was greater than the p = 99% for k = 3 or more locations with n = 2 repeated presentations, giving 85% sensitivity and 95.2% specificity. The median test time for controls was 85.71 (twenty-fifth to seventy-fifth percentile: 66.49–113.53) seconds.

Conclusion

Our prototype test demonstrated effective and efficient screening of abnormal areas in central vision.

Translational Relevance

Visual search behavior can be used to detect central vision loss and may produce results that relate well to performance in natural visual environments.

Intelligent-based decision support system for diagnosing glaucoma in primary eyecare centers using eye tracker

It is quite alarming that the increase of glaucoma is due to the lack of awareness of the disease and the cost for glaucoma screening. The primary eye care centers need to include a comprehensive glaucoma screening and include machine learning models to elaborate it as decision support system. The proposed system considers the state of art of eye gaze features to understand cognitive processing, direction and restriction of visual field. There is no significant difference in global and local ratio and skewness value of fixation duration and saccade amplitude, which suggest that there is no difference in cognitive processing. The significance value of saccadic extent along vertical axis, Horizontal Vertical ratio (HV ratio), convex hull area and saccadic direction show that there is restriction in vertical visual field. The statistical measures (p < 0.05) and Spearman correlation coefficient with class label validate the results. The proposed system compared the performance of seven classifiers: Naïve Bayes classifier, linear and kernel Support Vector classifiers, decision tree classifier, Adaboost, random forest and eXtreme Gradient Boosting (XGBoost) classifier. The discrimination of eye gaze features of glaucoma and normal is efficiently done by XGBoost with accuracy 1.0. The decision support system is cost-effective and portable.

How Free-Viewing Eye Movements Can Be Used to Detect the Presence of Visual Field Defects in Glaucoma Patients

Purpose: There is a need for more intuitive perimetric screening methods, which can also be performed by elderly people and children currently unable to perform standard automated perimetry (SAP). Ideally, these methods should also be easier to administer, such that they may be used outside of a regular clinical environment. We evaluated the suitability of various methodological and analytical approaches for detecting and localizing VFD in glaucoma patients, based on eye movement recordings. Methods: The present study consisted of two experiments. In experiment 1, we collected data from 20 glaucoma patients and 20 age-matched controls, who monocularly viewed 28 1-min video clips while their eyes were being tracked. In experiment 2, we re-analyzed a published dataset, that contained data of 44 glaucoma patients and 32 age-matched controls who had binocularly viewed three longer-duration (3, 5, and 7 min) video clips. For both experiments, we first examined if the two groups differed in the basic properties of their fixations and saccades. In addition, we computed the viewing priority (VP) of each participant. Following a previously reported approach, for each participant, we mapped their fixation locations and used kernel Principal Component Analysis (kPCA) to distinguish patients from controls. Finally, we attempted to reconstruct the location of a patient's VFD by mapping the relative fixation frequency and the VP across their visual field. Results: We found direction dependent saccade amplitudes in glaucoma patients that often differed from those of the controls. Moreover, the kPCA indicated that the fixation maps of the two groups separated into two clusters based on the first two principal components. On average, glaucoma patients had a significantly lower VP than the controls, with this decrease depending on the specific video viewed. Conclusions: It is possible to detect the presence of VFD in glaucoma patients based on their gaze behavior made during video viewing. While this corroborates earlier conclusions, we show that it requires participants to view the videos monocularly. Nevertheless, we could not reconstruct the VFD with any of the evaluated methods, possibly due to compensatory eye movements made by the glaucoma patients.

Patients Prefer a Virtual Reality Approach Over a Similarly Performing Screen-Based Approach for Continuous Oculomotor-Based Screening of Glaucomatous and Neuro-Ophthalmological Visual Field Defects

Standard automated perimetry (SAP) is the gold standard for evaluating the presence of visual field defects (VFDs). Nevertheless, it has requirements such as prolonged attention, stable fixation, and a need for a motor response that limit application in various patient groups. Therefore, a novel approach using eye movements (EMs) - as a complementary technique to SAP - was developed and tested in clinical settings by our group. However, the original method uses a screen-based eye-tracker which still requires participants to keep their chin and head stable. Virtual reality (VR) has shown much promise in ophthalmic diagnostics - especially in terms of freedom of head movement and precise control over experimental settings, besides being portable. In this study, we set out to see if patients can be screened for VFDs based on their EM in a VR-based framework and if they are comparable to the screen-based eyetracker. Moreover, we wanted to know if this framework can provide an effective and enjoyable user experience (UX) compared to our previous approach and the conventional SAP. Therefore, we first modified our method and implemented it on a VR head-mounted device with built-in eye tracking. Subsequently, 15 controls naïve to SAP, 15 patients with a neuro-ophthalmological disorder, and 15 glaucoma patients performed three tasks in a counterbalanced manner: (1) a visual tracking task on the VR headset while their EM was recorded, (2) the preceding tracking task but on a conventional screen-based eye tracker, and (3) SAP. We then quantified the spatio-temporal properties (STP) of the EM of each group using a cross-correlogram analysis. Finally, we evaluated the human-computer interaction (HCI) aspects of the participants in the three methods using a user-experience questionnaire. We find that: (1) the VR framework can distinguish the participants according to their oculomotor characteristics; (2) the STP of the VR framework are similar to those from the screen-based eye tracker; and (3) participants from all the groups found the VR-screening test to be the most attractive. Thus, we conclude that the EM-based approach implemented in VR can be a user-friendly and portable companion to complement existing perimetric techniques in ophthalmic clinics.

Slowed Saccadic Reaction Times in Seemingly Normal Parts of Glaucomatous Visual Fields

Purpose: In eye movement perimetry, peripheral stimuli are confirmed by goal-directed eye movements toward the stimulus. The saccadic reaction time (SRT) is regarded as an index of visual field responsiveness, whereas in standard automated perimetry (SAP), the visual field sensitivity is tested. We investigated the relation between visual field sensitivity and responsiveness in corresponding locations of the visual field in healthy controls and in patients with mild, moderate and advanced glaucoma.

Materials and Methods: Thirty-four healthy control subjects and 42 glaucoma patients underwent a 54-point protocol in eye movement perimetry (EMP) and a 24-2 SITA standard protocol in a Humphrey Field Analyzer. The visual field points were stratified by total deviation sensitivity loss in SAP into 6 strata. A generalized linear mixed model was applied to determine the influence of the various factors.

Results: The generalized linear mixed model showed that the mean SRT increased with increasing glaucoma severity, from 479 ms in the control eyes to 678 ms in the eyes of patients with advanced glaucoma (p < 0.001). Mean SRTs significantly increased with increasing SAP sensitivity loss. Even at the locations where no sensitivity loss was detected by SAP (total deviation values greater or equal than 0 dB), we found lengthened SRTs in mild, moderate and advanced glaucoma compared to healthy controls (p < 0.05) and in moderate and advanced glaucoma compared to mild glaucoma (p < 0.05). At locations with total deviation values between 0 and −3 dB, −3 and −6 dB and −6 and −12 dB, we found similar differences.

Conclusions: The lengthened SRT in areas with normal retinal sensitivities in glaucomatous eyes, i.e., planning and execution of saccades to specific locations, precede altered sensory perception as assessed with SAP. Better understanding of altered sensory processing in glaucoma might allow earlier diagnosis of emerging glaucoma.

Comparison of Saccadic Eye Movements Among the High-tension Glaucoma, Primary Angle-closure Glaucoma, and Normal-tension Glaucoma

PRCIS

Saccadic eye movements were compared between high-tension glaucoma (HTG), normal-tension glaucoma (NTG), and primary angle-closure glaucoma (PACG). Saccades were differently affected between the subtypes of primary glaucoma.

AIM

The aim of the study was to compare saccadic eye movements in eyes with HTG, PACG, and NTG.

METHODS

Saccadic eye movements were recorded using the eye tracker Eyelink-1000 in 52 participants: 15 HTG, 14 PACG, 8 NTG, and 15 normal controls. All participants underwent a complete ophthalmic and visual field examination. Prosaccades were measured using the gap paradigm. Prosaccades were measured at 3 target eccentricities (5-, 7-, and 10-degree eccentricity). All prosaccade targets were projected outside the area of visual field defect. Saccade latency, average and peak velocity, and amplitude difference of the saccades were compared between glaucoma subtypes.

RESULTS

The mean±SD age was lesser in controls compared with glaucoma (P=0.02). The mean age in all the glaucoma subtypes was comparable (P=0.92). The average mean deviation in PACG (-16.66±6.69 dB) was worse (P=0.01) than in HTG (-11.56±6.08 dB) and NTG (-9.55±3.96 dB). The latencies were delayed, average and peak velocities were reduced, and saccades were hypometric in glaucoma compared with controls (P<0.01). Between subtypes, the differences in latency (P<0.01), peak velocity (P=0.02), and amplitude (P=0.02) were significant. Saccadic eye movements were significantly different in NTG compared with other glaucoma subtypes (post hoc analysis; latency (HTG vs. NTG; P<0.01, HTG vs. PACG; P=0.01), peak velocity (HTG vs. NTG; P=0.02) and amplitude difference (HTG vs. NTG; P=0.02).

CONCLUSIONS

Saccadic eye movement parameters were differently affected among the glaucoma subtypes. Saccadic parameters were more affected in NTG.

A COMPARATIVE RESEARCH ON G-HMM AND TSS TECHNOLOGIES FOR EYE MOVEMENT TRACKING ANALYSIS

Eye movement analysis provides a new way for disease screening, quantification and assessment. In order to track and analyze eye movement scanpaths under different conditions, this paper proposed the Gaussian mixture-Hidden Markov Model (G-HMM) modeling the eye movement scanpath during saccade, combing with the Time-Shifting Segmentation (TSS) method for model optimization, and also the Linear Discriminant Analysis (LDA) method was utilized to perform the recognition and evaluation tasks based on the multi-dimensional features. In the experiments, 800 real scene images of eye-movement sequences datasets were used, and the experimental results show that the G-HMM method has high specificity for free searching tasks and high sensitivity for prompt object search tasks, while TSS can strengthen the difference of eye movement characteristics, which is conducive to eye movement pattern recognition, especially for search tasks.

Glaucoma and Computer Use: Do Contrast and Color Enhancements Improve Visual Comfort in Patients?

PURPOSE

To estimate the impact of glaucoma on computer use and to assess specific adaptations of the graphical interface to this form of visual impairment.

DESIGN

Prospective, experimental cohort study.

PARTICIPANTS

Forty-nine participants were recruited: 16 patients with primary open-angle glaucoma (mean ± SD, 62.7 ± 5.6 years of age), 17 age-matched participants (mean ± SD, 59.1 ± 8.3 years of age), and 16 young control participants (mean ± SD, 23.3 ± 2.1 years of age).

METHODS

An ophthalmologic examination before the study evaluated the level of visual loss (mean deviation), visual acuity (logarithm of the minimum angle of resolution units), and contrast sensitivity (CS) of the primary open-angle glaucoma patients. Each participant underwent the following measurements: an information technology (IT) experience questionnaire, a preference task monitored by eye tracking, and a feedback session. The experimental task was based on ecological computer scenes with 3 enhancement levels (low, medium, and high), determined by gradual modulation of contrast, luminance, and color. Participants were asked to select the most readable and comfortable stimulus among 4 images displayed on the screen: the original computer scene and 3 enhanced versions.

MAIN OUTCOME MEASURES

Clinical, oculomotor, and subjective data were computed together in a multivariate model by using a principal component analysis (PCA).

RESULTS

The PCA revealed 3 principal components accounting for 72% of the total variance of the data and showed a greater need for enhanced computer scenes in glaucoma patients, an equal preference for low and medium enhancement within the 3 groups, and significantly longer oculomotor behavior in the patient groups. Subjective reports of difficulty using IT because of vision were correlated with visual impairment and high enhancement preference. Contrast sensitivity was critical to explaining the main variations of the data. A reduced CS had a significant effect on the preference for enhanced computer scenes (r = -0.43; P < 0.002) and a less effective exploration velocity (r = 0.43; P < 0.002).

CONCLUSIONS

Glaucoma alters the global exploration of computer scenes. High enhancement of the graphical interface could improve visual comfort during computer use. Subjective patients' reports underline the importance of including IT questions in visual-related quality-of-life questionnaires.

Eye Movement Evaluation in Multiple Sclerosis and Parkinson's Disease Using a Standardized Oculomotor and Neuro-Ophthalmic Disorder Assessment (SONDA)

Evaluating the state of the oculomotor system of a patient is one of the fundamental tests done in neuro-ophthalmology. However, up to date, very few quantitative standardized tests of eye movements' quality exist, limiting this assessment to confrontational tests reliant on subjective interpretation. Furthermore, quantitative tests relying on eye movement properties, such as pursuit gain and saccade dynamics are often insufficient to capture the complexity of the underlying disorders and are often (too) long and tiring. In this study, we present SONDA (Standardized Oculomotor and Neurological Disorder Assessment): this test is based on analyzing eye tracking recorded during a short and intuitive continuous tracking task. We tested patients affected by Multiple Sclerosis (MS) and Parkinson's Disease (PD) and find that: (1) the saccadic dynamics of the main sequence alone are not sufficient to separate patients from healthy controls; (2) the combination of spatio-temporal and statistical properties of saccades and saccadic dynamics enables an identification of oculomotor abnormalities in both MS and PD patients. We conclude that SONDA constitutes a powerful screening tool that allows an in-depth evaluation of (deviant) oculomotor behavior in a few minutes of non-invasive testing.

Using natural viewing behavior to screen for and reconstruct visual field defects

There is a need for simple and effective ways to screen for visual field defects (VFD). Watching a movie is a simple task most humans are familiar with. Therefore we assessed whether it is possible to detect and reconstruct visual field defects based on free viewing eye movements, recorded while watching movie clips. Participants watched 90 movie clips of one minute, with and without simulated visual field defects (sVFD), while their eye movements were tracked. We simulated homonymous hemianopia (HH) (left and right sided) and glaucoma (small nasal arc, large nasal arc, and tunnel vision). We generated fixation density maps of the visual field and trained a linear support vector machine to predict the viewing conditions of each trial of each participant based on these maps. To reconstruct the visual field defect, we computed “viewing priority” maps and maps of differences in fixation density of the visual field of each participant. We were able to classify the simulated visual field condition with more than 85% accuracy. In simulated HH, the viewing priority distribution over the visual field indicated the location of the sVFD in the simulated HH condition. In simulated glaucoma the difference in fixation density to the control condition indicated the location of the sVFD. It is feasible to use natural viewing behavior to screen for and reconstruct (simulated) visual field defects. Movie clip viewing in combination with eye tracking may thus provide an alternative to or supplement standard automated perimetry, in particular in patients who cannot perform the latter technique.

Speed and accuracy of saccades in patients with glaucoma evaluated using an eye tracking perimeter

Background

To examine the speed and accuracy of saccadic eye movements during a novel eye tracking threshold visual field assessment and determine whether eye movement parameters may improve ability to detect glaucoma.

Methods

A prospective study including both eyes of 31 patients with glaucoma and 23 controls. Standard automated perimetry (SAP) and eye tracking perimetry (saccadic vector optokinetic perimetry, SVOP) was performed. SVOP provided data on threshold sensitivity, saccade latency, and two measures of accuracy of saccades (direction bias and amplitude bias). The relationship between eye movement parameters and severity of glaucoma was examined and Receiver Operating Characteristic curves were used to assess ability to detect glaucoma.

Results

Patients with glaucoma had significantly slower saccades (602.9 ± 50.0 ms versus 578.3 ± 44.6 ms for controls, P = 0.009) and reduced saccade accuracy (direction bias = 7.4 ± 1.8 versus 6.5 ± 1.5 degrees, P = 0.006). There was a significant slowing of saccades and saccades became less accurate with worsening SAP sensitivity. Slower saccades were associated with increased odds of glaucoma; however, the AUC for saccade latency was only 0.635 compared to 0.914 for SVOP sensitivity.

Conclusion

Patients with glaucoma had significant differences in eye movements compared to healthy subjects, with a relationship between slower and less accurate eye movements and worse glaucoma severity. However, in a multivariable model, eye movement parameters were not of additional benefit in differentiating eyes with glaucoma from healthy controls.

Using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma

Glaucoma is a leading cause of irreversible sight-loss and has been shown to affect natural eye-movements. These changes may provide a cheap and easy-to-obtain biomarker for improving disease detection. Here, we investigated whether these changes are large enough to be clinically useful. We used a gaze-contingent simulated visual field (VF) loss paradigm, in which participants experienced a variable magnitude of simulated VF loss based on longitudinal data from a real glaucoma patient (thereby controlling for other variables, such as age and general health). Fifty-five young participants with healthy vision were asked to view two short videos and three pictures, either with: (1) no VF loss, (2) moderate VF loss, or (3) advanced VF loss. Eye-movements were recorded using a remote eye tracker. Key eye-movement parameters were computed, including saccade amplitude, the spread of saccade endpoints (bivariate contour ellipse area), location of saccade landing positions, and similarity of fixations locations among participants (quantified using kernel density estimation). The simulated VF loss caused some statistically significant effects in the eye movement parameters. Yet, these effects were not capable of consistently identifying simulated VF loss, despite it being of a magnitude likely easily detectable by standard automated perimetry.

Predicting artificial visual field losses: A gaze-based inference study

Visual field defects are a world-wide concern, and the proportion of the population experiencing vision loss is ever increasing. Macular degeneration and glaucoma are among the four leading causes of permanent vision loss. Identifying and characterizing visual field losses from gaze alone could prove crucial in the future for screening tests, rehabilitation therapies, and monitoring. In this experiment, 54 participants took part in a free-viewing task of visual scenes while experiencing artificial scotomas (central and peripheral) of varying radii in a gaze-contingent paradigm. We studied the importance of a set of gaze features as predictors to best differentiate between artificial scotoma conditions. Linear mixed models were utilized to measure differences between scotoma conditions. Correlation and factorial analyses revealed redundancies in our data. Finally, hidden Markov models and recurrent neural networks were implemented as classifiers in order to measure the predictive usefulness of gaze features. The results show separate saccade direction biases depending on scotoma type. We demonstrate that the saccade relative angle, amplitude, and peak velocity of saccades are the best features on the basis of which to distinguish between artificial scotomas in a free-viewing task. Finally, we discuss the usefulness of our protocol and analyses as a gaze-feature identifier tool that discriminates between artificial scotomas of different types and sizes.

Eye movement analysis using a binocular video-ophthalmoscope

This paper describes an application of binocular video-ophthalmoscope for binocular eye movement analysis during target fixation. We analyze eye movements during monocular and binocular fixation and the changes in eye position for 73 subjects. We show that the standard deviations of differences between eye shifts for vertical and horizontal movements are higher for binocular fixation with respect to monocular fixation. We also present different examples of eye movement visualization.

Does Glaucoma Alter Eye Movements When Viewing Images of Natural Scenes? A Between-Eye Study

Purpose

To investigate whether glaucoma produces measurable changes in eye movements.

Methods

Fifteen glaucoma patients with asymmetric vision loss (difference in mean deviation [MD] > 6 dB between eyes) were asked to monocularly view 120 images of natural scenes, presented sequentially on a computer monitor. Each image was viewed twice-once each with the better and worse eye. Patients' eye movements were recorded with an Eyelink 1000 eye-tracker. Eye-movement parameters were computed and compared within participants (better eye versus worse eye). These parameters included a novel measure: saccadic reversal rate (SRR), as well as more traditional metrics such as saccade amplitude, fixation counts, fixation duration, and spread of fixation locations (bivariate contour ellipse area [BCEA]). In addition, the associations of these parameters with clinical measures of vision were investigated.

Results

In the worse eye, saccade amplitude\(\def\upalpha{\unicode[Times]{x3B1}}\)\(\def\upbeta{\unicode[Times]{x3B2}}\)\(\def\upgamma{\unicode[Times]{x3B3}}\)\(\def\updelta{\unicode[Times]{x3B4}}\)\(\def\upvarepsilon{\unicode[Times]{x3B5}}\)\(\def\upzeta{\unicode[Times]{x3B6}}\)\(\def\upeta{\unicode[Times]{x3B7}}\)\(\def\uptheta{\unicode[Times]{x3B8}}\)\(\def\upiota{\unicode[Times]{x3B9}}\)\(\def\upkappa{\unicode[Times]{x3BA}}\)\(\def\uplambda{\unicode[Times]{x3BB}}\)\(\def\upmu{\unicode[Times]{x3BC}}\)\(\def\upnu{\unicode[Times]{x3BD}}\)\(\def\upxi{\unicode[Times]{x3BE}}\)\(\def\upomicron{\unicode[Times]{x3BF}}\)\(\def\uppi{\unicode[Times]{x3C0}}\)\(\def\uprho{\unicode[Times]{x3C1}}\)\(\def\upsigma{\unicode[Times]{x3C3}}\)\(\def\uptau{\unicode[Times]{x3C4}}\)\(\def\upupsilon{\unicode[Times]{x3C5}}\)\(\def\upphi{\unicode[Times]{x3C6}}\)\(\def\upchi{\unicode[Times]{x3C7}}\)\(\def\uppsy{\unicode[Times]{x3C8}}\)\(\def\upomega{\unicode[Times]{x3C9}}\)\(\def\bialpha{\boldsymbol{\alpha}}\)\(\def\bibeta{\boldsymbol{\beta}}\)\(\def\bigamma{\boldsymbol{\gamma}}\)\(\def\bidelta{\boldsymbol{\delta}}\)\(\def\bivarepsilon{\boldsymbol{\varepsilon}}\)\(\def\bizeta{\boldsymbol{\zeta}}\)\(\def\bieta{\boldsymbol{\eta}}\)\(\def\bitheta{\boldsymbol{\theta}}\)\(\def\biiota{\boldsymbol{\iota}}\)\(\def\bikappa{\boldsymbol{\kappa}}\)\(\def\bilambda{\boldsymbol{\lambda}}\)\(\def\bimu{\boldsymbol{\mu}}\)\(\def\binu{\boldsymbol{\nu}}\)\(\def\bixi{\boldsymbol{\xi}}\)\(\def\biomicron{\boldsymbol{\micron}}\)\(\def\bipi{\boldsymbol{\pi}}\)\(\def\birho{\boldsymbol{\rho}}\)\(\def\bisigma{\boldsymbol{\sigma}}\)\(\def\bitau{\boldsymbol{\tau}}\)\(\def\biupsilon{\boldsymbol{\upsilon}}\)\(\def\biphi{\boldsymbol{\phi}}\)\(\def\bichi{\boldsymbol{\chi}}\)\(\def\bipsy{\boldsymbol{\psy}}\)\(\def\biomega{\boldsymbol{\omega}}\)\(\def\bupalpha{\unicode[Times]{x1D6C2}}\)\(\def\bupbeta{\unicode[Times]{x1D6C3}}\)\(\def\bupgamma{\unicode[Times]{x1D6C4}}\)\(\def\bupdelta{\unicode[Times]{x1D6C5}}\)\(\def\bupepsilon{\unicode[Times]{x1D6C6}}\)\(\def\bupvarepsilon{\unicode[Times]{x1D6DC}}\)\(\def\bupzeta{\unicode[Times]{x1D6C7}}\)\(\def\bupeta{\unicode[Times]{x1D6C8}}\)\(\def\buptheta{\unicode[Times]{x1D6C9}}\)\(\def\bupiota{\unicode[Times]{x1D6CA}}\)\(\def\bupkappa{\unicode[Times]{x1D6CB}}\)\(\def\buplambda{\unicode[Times]{x1D6CC}}\)\(\def\bupmu{\unicode[Times]{x1D6CD}}\)\(\def\bupnu{\unicode[Times]{x1D6CE}}\)\(\def\bupxi{\unicode[Times]{x1D6CF}}\)\(\def\bupomicron{\unicode[Times]{x1D6D0}}\)\(\def\buppi{\unicode[Times]{x1D6D1}}\)\(\def\buprho{\unicode[Times]{x1D6D2}}\)\(\def\bupsigma{\unicode[Times]{x1D6D4}}\)\(\def\buptau{\unicode[Times]{x1D6D5}}\)\(\def\bupupsilon{\unicode[Times]{x1D6D6}}\)\(\def\bupphi{\unicode[Times]{x1D6D7}}\)\(\def\bupchi{\unicode[Times]{x1D6D8}}\)\(\def\buppsy{\unicode[Times]{x1D6D9}}\)\(\def\bupomega{\unicode[Times]{x1D6DA}}\)\(\def\bupvartheta{\unicode[Times]{x1D6DD}}\)\(\def\bGamma{\bf{\Gamma}}\)\(\def\bDelta{\bf{\Delta}}\)\(\def\bTheta{\bf{\Theta}}\)\(\def\bLambda{\bf{\Lambda}}\)\(\def\bXi{\bf{\Xi}}\)\(\def\bPi{\bf{\Pi}}\)\(\def\bSigma{\bf{\Sigma}}\)\(\def\bUpsilon{\bf{\Upsilon}}\)\(\def\bPhi{\bf{\Phi}}\)\(\def\bPsi{\bf{\Psi}}\)\(\def\bOmega{\bf{\Omega}}\)\(\def\iGamma{\unicode[Times]{x1D6E4}}\)\(\def\iDelta{\unicode[Times]{x1D6E5}}\)\(\def\iTheta{\unicode[Times]{x1D6E9}}\)\(\def\iLambda{\unicode[Times]{x1D6EC}}\)\(\def\iXi{\unicode[Times]{x1D6EF}}\)\(\def\iPi{\unicode[Times]{x1D6F1}}\)\(\def\iSigma{\unicode[Times]{x1D6F4}}\)\(\def\iUpsilon{\unicode[Times]{x1D6F6}}\)\(\def\iPhi{\unicode[Times]{x1D6F7}}\)\(\def\iPsi{\unicode[Times]{x1D6F9}}\)\(\def\iOmega{\unicode[Times]{x1D6FA}}\)\(\def\biGamma{\unicode[Times]{x1D71E}}\)\(\def\biDelta{\unicode[Times]{x1D71F}}\)\(\def\biTheta{\unicode[Times]{x1D723}}\)\(\def\biLambda{\unicode[Times]{x1D726}}\)\(\def\biXi{\unicode[Times]{x1D729}}\)\(\def\biPi{\unicode[Times]{x1D72B}}\)\(\def\biSigma{\unicode[Times]{x1D72E}}\)\(\def\biUpsilon{\unicode[Times]{x1D730}}\)\(\def\biPhi{\unicode[Times]{x1D731}}\)\(\def\biPsi{\unicode[Times]{x1D733}}\)\(\def\biOmega{\unicode[Times]{x1D734}}\)\((P = 0.012; - 13\% \)) and BCEA \((P = 0.005; - 16\% )\) were smaller, while SRR was greater (\(P = 0.018; + 16\% \)). There was a significant correlation between the intereye difference in BCEA, and differences in MD values (\({\rm{Spearman^{\prime} s}}\ r = 0.65;P = 0.01\)), while differences in SRR were associated with differences in visual acuity (\({\rm{Spearman^{\prime} s}}\ r = 0.64;P = 0.01\)). Furthermore, between-eye differences in BCEA were a significant predictor of between-eye differences in MD: for every 1-dB difference in MD, BCEA reduced by 6.2% (95% confidence interval, 1.6%-10.3%).

Conclusions

Eye movements are altered by visual field loss, and these changes are related to changes in clinical measures. Eye movements recorded while passively viewing images could potentially be used as biomarkers for visual field damage.

Evidence for alterations in fixational eye movements in glaucoma

Background

Fixation changes in glaucoma are generally overlooked, as they are not strikingly evident as in macular diseases. Fundus perimetry might give additional insights into this aspect, along with traditional perimetric measures. In this work we propose a novel method to quantify glaucomatous changes in fixation features as detected by fundus perimetry and relate them to the extent of glaucomatous damage.

Methods

We retrospectively analysed fixation data from 320 people (200 normal subjects and 120 with glaucoma) from the Preferred Retinal Locus (PRL) detection of a Compass perimeter. Fixation stability was measured as Bivariate Contour Ellipse Area (BCEA), and using two novel metrics: (1) Mean Euclidean Distance (MED) from the Preferred Retinal Locus, and (2) Sequential Euclidean Distance (SED) of sequential fixation locations. These measures were designed to capture the spread of fixation points, and the frequency of position changes during fixation, respectively.

Results

In the age corrected analysis, SED was significantly greater in glaucomatous subjects than controls (P = 0.002), but there was no difference in BCEA (P = 0.15) or MED (P = 0.054). Similarly, SED showed a significant association with Mean Deviation (P <  0.001), but neither BCEA nor MED were significantly correlated (P > 0.14 for both).

Conclusion

Changes in the scanning pattern detected by SED are better than traditional measures of fixation spread (BCEA) for describing the changes in fixation stability observed in glaucoma.

Detecting mental fatigue from eye-tracking data gathered while watching video: Evaluation in younger and older adults

Health monitoring technology in everyday situations is expected to improve quality of life and support aging populations. Mental fatigue among health indicators of individuals has become important due to its association with cognitive performance and health outcomes, especially in older adults. Previous models using eye-tracking measures allow inference of fatigue during cognitive tasks, such as driving, but they require us to engage in specific cognitive tasks. In addition, previous models were mainly tested by user groups that did not include older adults, although age-related changes in eye-tracking measures have been reported especially in older adults. Here, we propose a model to detect mental fatigue of younger and older adults in natural viewing situations. Our model includes two unique aspects: (i) novel feature sets to better capture fatigue in natural-viewing situations and (ii) an automated feature selection method to select a feature subset enabling the model to be robust to the target's age. To test our model, we collected eye-tracking data from younger and older adults as they watched video clips before and after performing cognitive tasks. Our model improved detection accuracy by up to 13.9% compared with a model based on the previous studies, achieving 91.0% accuracy (chance 50%).

Data on eye movements in people with glaucoma and peers with normal vision

Eye movements of glaucoma patients have been shown to differ from age-similar control groups when performing everyday tasks, such as reading (Burton et al., 2012; Smith et al., 2014) [1], [2], visual search (Smith et al., 2012) [3], face recognition (Glen et al., 2013) [4], driving, and viewing static images (Smith et al., 2012) [5]. Described here is the dataset from a recent publication in which we compared the eye-movements of 44 glaucoma patients and 32 age-similar controls, while they watched a series of short video clips taken from television programs (Crabb et al., 2018) [6]. Gaze was recorded at 1000 Hz using a remote eye-tracker. We also provide demographic information and results from a clinical examination of vision for each participant.

Unsupervised detection of microsaccades in a high-noise regime

Micromovements of the eye during visual fixations provide clues about how our visual system acquires information. The analysis of fixational eye movements can thus serve as a noninvasive means to detect age-related or pathological changes in visual processing, which can in turn reflect associated cognitive or neurological disorders. However, the utility of such diagnostic approaches relies on the quality and usability of detection methods applied for the eye movement analysis. Here, we propose a novel method for (micro)saccade detection that is resistant to high-frequency recording noise, a frequent problem in video-based eye tracking in either aged subjects or subjects suffering from a vision-related pathology. The method is fast, it does not require manual noise removal, and it can work with position, velocity, or acceleration features, or a combination thereof. The detection accuracy of the proposed method is assessed on a new dataset of manually labeled recordings acquired from 14 subjects of advanced age (69-81 years old), performing an ocular fixation task. It is demonstrated that the detection accuracy of the new method compares favorably to that of two frequently used reference methods and that it is comparable to the best of the two algorithms when tested on an existing low-noise eye-tracking dataset.

Scene and human face recognition in the central vision of patients with glaucoma

Primary open-angle glaucoma (POAG) firstly mainly affects peripheral vision. Current behavioral studies support the idea that visual defects of patients with POAG extend into parts of the central visual field classified as normal by static automated perimetry analysis. This is particularly true for visual tasks involving processes of a higher level than mere detection. The purpose of this study was to assess visual abilities of POAG patients in central vision. Patients were assigned to two groups following a visual field examination (Humphrey 24–2 SITA-Standard test). Patients with both peripheral and central defects and patients with peripheral but no central defect, as well as age-matched controls, participated in the experiment. All participants had to perform two visual tasks where low-contrast stimuli were presented in the central 6° of the visual field. A categorization task of scene images and human face images assessed high-level visual recognition abilities. In contrast, a detection task using the same stimuli assessed low-level visual function. The difference in performance between detection and categorization revealed the cost of high-level visual processing. Compared to controls, patients with a central visual defect showed a deficit in both detection and categorization of all low-contrast images. This is consistent with the abnormal retinal sensitivity as assessed by perimetry. However, the deficit was greater for categorization than detection. Patients without a central defect showed similar performances to the controls concerning the detection and categorization of faces. However, while the detection of scene images was well-maintained, these patients showed a deficit in their categorization. This suggests that the simple loss of peripheral vision could be detrimental to scene recognition, even when the information is displayed in central vision. This study revealed subtle defects in the central visual field of POAG patients that cannot be predicted by static automated perimetry assessment using Humphrey 24–2 SITA-Standard test.

Scanpath modeling and classification with hidden Markov models

How people look at visual information reveals fundamental information about them; their interests and their states of mind. Previous studies showed that scanpath, i.e., the sequence of eye movements made by an observer exploring a visual stimulus, can be used to infer observer-related (e.g., task at hand) and stimuli-related (e.g., image semantic category) information. However, eye movements are complex signals and many of these studies rely on limited gaze descriptors and bespoke datasets. Here, we provide a turnkey method for scanpath modeling and classification. This method relies on variational hidden Markov models (HMMs) and discriminant analysis (DA). HMMs encapsulate the dynamic and individualistic dimensions of gaze behavior, allowing DA to capture systematic patterns diagnostic of a given class of observers and/or stimuli. We test our approach on two very different datasets. Firstly, we use fixations recorded while viewing 800 static natural scene images, and infer an observer-related characteristic: the task at hand. We achieve an average of 55.9% correct classification rate (chance = 33%). We show that correct classification rates positively correlate with the number of salient regions present in the stimuli. Secondly, we use eye positions recorded while viewing 15 conversational videos, and infer a stimulus-related characteristic: the presence or absence of original soundtrack. We achieve an average 81.2% correct classification rate (chance = 50%). HMMs allow to integrate bottom-up, top-down, and oculomotor influences into a single model of gaze behavior. This synergistic approach between behavior and machine learning will open new avenues for simple quantification of gazing behavior. We release SMAC with HMM, a Matlab toolbox freely available to the community under an open-source license agreement.

Comparison of Threshold Saccadic Vector Optokinetic Perimetry (SVOP) and Standard Automated Perimetry (SAP) in Glaucoma. Part II: Patterns of Visual Field Loss and Acceptability

Purpose

We compared patterns of visual field loss detected by standard automated perimetry (SAP) to saccadic vector optokinetic perimetry (SVOP) and examined patient perceptions of each test.

Methods

A cross-sectional study was done of 58 healthy subjects and 103 with glaucoma who were tested using SAP and two versions of SVOP (v1 and v2). Visual fields from both devices were categorized by masked graders as: 0, normal; 1, paracentral defect; 2, nasal step; 3, arcuate defect; 4, altitudinal; 5, biarcuate; and 6, end-stage field loss. SVOP and SAP classifications were cross-tabulated. Subjects completed a questionnaire on their opinions of each test.

Results

We analyzed 142 (v1) and 111 (v2) SVOP and SAP test pairs. SVOP v2 had a sensitivity of 97.7% and specificity of 77.9% for identifying normal versus abnormal visual fields. SAP and SVOP v2 classifications showed complete agreement in 54% of glaucoma patients, with a further 23% disagreeing by one category. On repeat testing, 86% of SVOP v2 classifications agreed with the previous test, compared to 91% of SAP classifications; 71% of subjects preferred SVOP compared to 20% who preferred SAP.

Conclusions

Eye-tracking perimetry can be used to obtain threshold visual field sensitivity values in patients with glaucoma and produce maps of visual field defects, with patterns exhibiting close agreement to SAP. Patients preferred eye-tracking perimetry compared to SAP.

Translational relevance

This first report of threshold eye tracking perimetry shows good agreement with conventional automated perimetry and provides a benchmark for future iterations.

Effect of glaucoma on eye movement patterns and laboratory-based hazard detection ability

Purpose

The mechanisms underlying the elevated crash rates of older drivers with glaucoma are poorly understood. A key driving skill is timely detection of hazards; however, the hazard detection ability of drivers with glaucoma has been largely unexplored. This study assessed the eye movement patterns and visual predictors of performance on a laboratory-based hazard detection task in older drivers with glaucoma.

Methods

Participants included 30 older drivers with glaucoma (71±7 years; average better-eye mean deviation (MD) = −3.1±3.2 dB; average worse-eye MD = −11.9±6.2 dB) and 25 age-matched controls (72±7 years). Visual acuity, contrast sensitivity, visual fields, useful field of view (UFoV; processing speeds), and motion sensitivity were assessed. Participants completed a computerised Hazard Perception Test (HPT) while their eye movements were recorded using a desk-mounted Tobii TX300 eye-tracking system. The HPT comprises a series of real-world traffic videos recorded from the driver’s perspective; participants responded to road hazards appearing in the videos, and hazard response times were determined.

Results

Participants with glaucoma exhibited an average of 0.42 seconds delay in hazard response time (p = 0.001), smaller saccades (p = 0.010), and delayed first fixation on hazards (p<0.001) compared to controls. Importantly, larger saccades were associated with faster hazard responses in the glaucoma group (p = 0.004), but not in the control group (p = 0.19). Across both groups, significant visual predictors of hazard response times included motion sensitivity, UFoV, and worse-eye MD (p<0.05).

Conclusions

Older drivers with glaucoma had delayed hazard response times compared to controls, with associated changes in eye movement patterns. The association between larger saccades and faster hazard response time in the glaucoma group may represent a compensatory behaviour to facilitate improved performance.

Searching for unity: Real-world versus item-based visual search in age-related eye disease

When studying visual search, item-based approaches using synthetic targets and distractors limit the real-world applicability of results. Everyday visual search can be impaired in patients with common eye diseases like glaucoma and age-related macular degeneration. We highlight some results in the literature that suggest assessment of real-word search tasks in these patients could be clinically useful.

Gradually Then Suddenly? Decline in Vision-Related Quality of Life as Glaucoma Worsens

Purpose. To evaluate the relationship between self-reported vision-related quality of life (VRQL) and visual field (VF) loss in people from glaucoma clinics. Methods. A postal survey using the National Eye Institute Visual Function Questionnaire (NEI VFQ-25) was administered to people with a range of VF loss identified from a UK hospital-based glaucoma service database. Trends were assessed in a composite score from NEI VFQ-25 against better-eye mean deviation (BEMD) using linear regression and a spline-fitting method that can highlight where a monotonic relationship may have different stages. Results. A total of 636 patients (median [interquartile range] BEMD -2.1 [-5.2, -0.4] dB, median age 70 [60, 77] years) were analysed. Analysis of trends in the data revealed an average patient loses approximately 2 units (out of 100) on NEI VFQ-25 for every loss of 1 dB (BEMD) as VF defects first become bilateral, up to BEMD -5 dB. NEI VFQ-25 deterioration then appears to slow before a more rapid phase of change (4-5 units per 1 dB loss) after BEMD worsens beyond -15 dB. Conclusions. Relationship between decline in VRQL and VF worsening in glaucoma is unlikely to be linear; it more likely has different phases, and these should be further explored in longitudinal studies.

Eye-Tracking as a Tool to Evaluate Functional Ability in Everyday Tasks in Glaucoma

To date, few studies have investigated the eye movement patterns of individuals with glaucoma while they undertake everyday tasks in real-world settings. While some of these studies have reported possible compensatory gaze patterns in those with glaucoma who demonstrated good task performance despite their visual field loss, little is known about the complex interaction between field loss and visual scanning strategies and the impact on task performance and, consequently, on quality of life. We review existing approaches that have quantified the effect of glaucomatous visual field defects on the ability to undertake everyday activities through the use of eye movement analysis. Furthermore, we discuss current developments in eye-tracking technology and the potential for combining eye-tracking with virtual reality and advanced analytical approaches. Recent technological developments suggest that systems based on eye-tracking have the potential to assist individuals with glaucomatous loss to maintain or even improve their performance on everyday tasks and hence enhance their long-term quality of life. We discuss novel approaches for studying the visual search behavior of individuals with glaucoma that have the potential to assist individuals with glaucoma, through the use of personalized programs that take into consideration the individual characteristics of their remaining visual field and visual search behavior.

Eye movements in neurodegenerative diseases

PURPOSE OF REVIEW

Abnormalities of oculomotor control accompany the pathological changes underlying many neurodegenerative diseases. Clinical examination of eye movements can contribute to differential diagnosis, whereas quantitative laboratory measures can provide detailed insight into the disease process. In this review of eye movements in neurodegenerative disease, we summarise recent empirical findings and conceptual advances.

RECENT FINDINGS

Oculomotor researchers continue to be particularly prolific in studying Parkinson's disease but there is also substantial activity in Alzheimer's disease and spinocerebellar ataxia. Interesting findings have been reported in Huntington's, motor neuron disease, and glaucoma. Most studies report laboratory-based investigations but useful progress in clinical description continues to be made.

SUMMARY

Eye movements remain an active field of investigation across a variety of neurodegenerative conditions. Progress continues to be made at the clinical level as well by using laboratory techniques.

Exercise promotes the expression of brain derived neurotrophic factor (BDNF) through the action of the ketone body β-hydroxybutyrate

Exercise induces beneficial responses in the brain, which is accompanied by an increase in BDNF, a trophic factor associated with cognitive improvement and the alleviation of depression and anxiety. However, the exact mechanisms whereby physical exercise produces an induction in brain Bdnf gene expression are not well understood. While pharmacological doses of HDAC inhibitors exert positive effects on Bdnf gene transcription, the inhibitors represent small molecules that do not occur in vivo. Here, we report that an endogenous molecule released after exercise is capable of inducing key promoters of the Mus musculus Bdnf gene. The metabolite β-hydroxybutyrate, which increases after prolonged exercise, induces the activities of Bdnf promoters, particularly promoter I, which is activity-dependent. We have discovered that the action of β-hydroxybutyrate is specifically upon HDAC2 and HDAC3, which act upon selective Bdnf promoters. Moreover, the effects upon hippocampal Bdnf expression were observed after direct ventricular application of β-hydroxybutyrate. Electrophysiological measurements indicate that β-hydroxybutyrate causes an increase in neurotransmitter release, which is dependent upon the TrkB receptor. These results reveal an endogenous mechanism to explain how physical exercise leads to the induction of BDNF.

DOI:http://dx.doi.org/10.7554/eLife.15092.001

Exercise is not only good for our physical health but it benefits our mental health and abilities too. Physical exercise can affect how much of certain proteins are made in the brain. In particular, the levels of a protein called brain derived neurotrophic factor (or BDNF for short) increase after exercise. BDNF has already been shown to enhance mental abilities at the same time as acting against anxiety and depression in mice, and might act in similar way in humans. Nevertheless, it is currently not clear how exercise increases the production of BDNF by cells in the brain.

Sleiman et al. have now investigated this question by comparing mice that were allowed to use a running wheel for 30 days with control mice that did not exercise. The comparison showed that the exercising mice had higher levels of BDNF in their brains than the control mice, which confirms the results of previous studies. Next, biochemical experiments showed that this change occurred when enzymes known as histone deacetylases stopped inhibiting the production of BDNF. Therefore Sleiman et al. hypothesised that exercise might produce a chemical that itself inhibits the histone deacetylases.

Indeed, the exercising mice produced more of a molecule called β-hydroxybutyrate in their livers, which travels through the blood into the brain where it could inhibit histone deacetylases. Further experiments showed that injecting β-hydroxybutyrate directly into the brains of mice led to increase in BDNF.

These new findings reveal with molecular detail one way in which exercise can affect the expression of proteins in the brain. This new understanding may provide ideas for new therapies to treat psychiatric diseases, such as depression, and neurodegenerative disorders, such as Alzheimer’s disease.

DOI:http://dx.doi.org/10.7554/eLife.15092.002

A view on glaucoma--are we seeing it clearly?

Successful clinical management of glaucoma should not simply be about control of intraocular pressure, but must equate to correct decisions about intensifying treatment when patients are at risk of developing 'visual disability'. Yet little is known about what visual field defects, at different stages of glaucoma, specifically affect patients' abilities to perform everyday visual tasks. One way to do this is to measure patient performance in tasks in a lab setting. Another way is to ask patients themselves. The latter can be revealing and demystify views about how patients perceive the world. This short commentary highlights some of the current research in this area.

Living with glaucoma: a qualitative study of functional implications and patients' coping behaviours

BACKGROUND

Sight loss from glaucoma can have a significant impact on functioning and performing everyday activities, but this varies between patients. The purpose of this study was to explore whether patients with glaucoma use different coping strategies in response to their vision loss.

METHODS

Audio-recorded semi-structured interviews were conducted with 16 patients (median age: 71 [interquartile range [IQR]: 68 to 77 years]; 50 % female) about their experiences of living with glaucoma. Patients had their glaucoma diagnosis for at least 5 years (range: 6 to 29 years) and had a range of disease severities (median best eye Mean Deviation was -9.1 dB [IQR: -12.9 to -4.1 dB]). A framework approach to analysis was taken whereby data was indexed using manual and computer-assisted methods, with codes applied to depict areas of functioning perceived to be impacted by glaucoma and coping behaviours used in response to these difficulties.

RESULTS

In order to maintain independence, some patients increased confidence by making practical changes such as adjusting lighting, using handrails and magnifying glasses, or actively changed aspects of their behaviour such as moving their head and eyes towards known areas of vision loss. Support from friends and family was often used, although some people worried about becoming a burden. Others imposed self-restrictions or gave up activities, thus compromising well-being and independence. Certain coping strategies were linked to time since diagnosis and location of vision loss. The type and quality of information received during clinical appointments, and the potential benefits of communication with other patients, emerged as other important themes.

CONCLUSIONS

Results from this qualitative study suggest that the adoption of certain coping behaviours and techniques may help some glaucomatous patients to adapt to their condition. An awareness of coping and adaptive strategies, in addition to the usual clinical tests, may provide a better insight into the impact of disease and help inform future educational and management strategies for glaucoma.