Eyetracking Metrics in Young Onset Alzheimer's Disease: A Window into Cognitive Visual Functions

The Graded Incomplete Letters Test (GILT): a rapid test to detect cortical visual loss, with UK Biobank implementation

Impairments of object recognition are core features of neurodegenerative syndromes, in particular posterior cortical atrophy (PCA; the 'visual-variant Alzheimer's disease'). These impairments arise from damage to higher-level cortical visual regions and are often missed or misattributed to common ophthalmological conditions. Consequently, diagnosis can be delayed for years with considerable implications for patients. We report a new test for the rapid measurement of cortical visual loss - the Graded Incomplete Letters Test (GILT). The GILT is an optimised psychophysical variation of a test used to diagnose cortical visual impairment, which measures thresholds for recognising letters under levels of increasing visual degradation (decreasing "completeness") in a similar fashion to ophthalmic tests. The GILT was administered to UK Biobank participants (total n=2,359) and participants with neurodegenerative conditions characterised by initial cortical visual (PCA, n=18) or memory loss (typical Alzheimer's disease, n=9). UK Biobank participants, including both typical adults and those with ophthalmological conditions, were able to recognise letters under low levels of completeness. In contrast, participants with PCA consistently made errors with only modest decreases in completeness. GILT sensitivity to PCA was 83.3% for participants reaching the 80% accuracy cut-off, increasing to 88.9% using alternative cut-offs (60% or 100% accuracy). Specificity values were consistently over 94% when compared to UK Biobank participants without or with documented visual conditions, regardless of accuracy cut-off. These first-release UK Biobank and clinical verification data suggest the GILT has utility in both rapidly detecting visual perceptual losses following posterior cortical damage and differentiating perceptual losses from common eye-related conditions.

Automating the analysis of eye movement for different neurodegenerative disorders

The clinical observation and assessment of extra-ocular movements is common practice in assessing neurodegenerative disorders but remains observer-dependent. In the present study, we propose an algorithm that can automatically identify saccades, fixation, smooth pursuit, and blinks using a non-invasive eye tracker. Subsequently, response-to-stimuli-derived interpretable features were elicited that objectively and quantitatively assess patient behaviors. The cohort analysis encompasses persons with mild cognitive impairment (MCI), Alzheimer's disease (AD), Parkinson's disease (PD), Parkinson's disease mimics (PDM), and controls (CTRL). Overall, results suggested that the AD/MCI and PD groups had significantly different saccade and pursuit characteristics compared to CTRL when the target moved faster or covered a larger visual angle during smooth pursuit. These two groups also displayed more omitted antisaccades and longer average antisaccade latency than CTRL. When reading a text passage silently, people with AD/MCI had more fixations. During visual exploration, people with PD demonstrated a more variable saccade duration than other groups. In the prosaccade task, the PD group showed a significantly smaller average hypometria gain and accuracy, with the most statistical significance and highest AUC scores of features studied. The minimum saccade gain was a PD-specific feature different from CTRL and PDM. These features, as oculographic biomarkers, can be potentially leveraged in distinguishing different types of NDs, yielding more objective and precise protocols to diagnose and monitor disease progression.

Immersive Virtual Reality-Based Methods for Assessing Executive Functioning: Systematic Review

BACKGROUND

Neuropsychological assessments traditionally include tests of executive functioning (EF) because of its critical role in daily activities and link to mental disorders. Established traditional EF assessments, although robust, lack ecological validity and are limited to single cognitive processes. These methods, which are suitable for clinical populations, are less informative regarding EF in healthy individuals. With these limitations in mind, immersive virtual reality (VR)-based assessments of EF have garnered interest because of their potential to increase test sensitivity, ecological validity, and neuropsychological assessment accessibility.

OBJECTIVE

This systematic review aims to explore the literature on immersive VR assessments of EF focusing on (1) EF components being assessed, (2) how these assessments are validated, and (3) strategies for monitoring potential adverse (cybersickness) and beneficial (immersion) effects.

METHODS

EBSCOhost, Scopus, and Web of Science were searched in July 2022 using keywords that reflected the main themes of VR, neuropsychological tests, and EF. Articles had to be peer-reviewed manuscripts written in English and published after 2013 that detailed empirical, clinical, or proof-of-concept studies in which a virtual environment using a head-mounted display was used to assess EF in an adult population. A tabular synthesis method was used in which validation details from each study, including comparative assessments and scores, were systematically organized in a table. The results were summed and qualitatively analyzed to provide a comprehensive overview of the findings.

RESULTS

The search retrieved 555 unique articles, of which 19 (3.4%) met the inclusion criteria. The reviewed studies encompassed EF and associated higher-order cognitive functions such as inhibitory control, cognitive flexibility, working memory, planning, and attention. VR assessments commonly underwent validation against gold-standard traditional tasks. However, discrepancies were observed, with some studies lacking reported a priori planned correlations, omitting detailed descriptions of the EF constructs evaluated using the VR paradigms, and frequently reporting incomplete results. Notably, only 4 of the 19 (21%) studies evaluated cybersickness, and 5 of the 19 (26%) studies included user experience assessments.

CONCLUSIONS

Although it acknowledges the potential of VR paradigms for assessing EF, the evidence has limitations. The methodological and psychometric properties of the included studies were inconsistently addressed, raising concerns about their validity and reliability. Infrequent monitoring of adverse effects such as cybersickness and considerable variability in sample sizes may limit interpretation and hinder psychometric evaluation. Several recommendations are proposed to improve the theory and practice of immersive VR assessments of EF. Future studies should explore the integration of biosensors with VR systems and the capabilities of VR in the context of spatial navigation assessments. Despite considerable promise, the systematic and validated implementation of VR assessments is essential for ensuring their practical utility in real-world applications.

Clinical utility of square-wave jerks in neurology and psychiatry

Human eye fixation is steadily interrupted by small, physiological or abnormal, eye movements. Square-wave jerks (SWJ) are the most common saccadic intrusion which can be readily seen at the bedside and also quantified using oculographic techniques. Various neurological, neuropsychiatric and psychiatric disorders display abnormal fixational eye movement patterns characterized by frequent SWJ. For the clinician, SWJ are particularly important because they can be readily observed at the bedside. Here, we will discuss the pathological conditions that present with SWJ and explore the expanding body of literature suggesting that SWJ may serve as a potential indicator for various clinical conditions.

Differential eye movement features between Alzheimer's disease patients with and without depressive symptoms

BACKGROUND

Accurately diagnosing depressive symptoms in Alzheimer's disease (AD) patients is often challenging. Eye movement parameters have been demonstrated as biomarkers for assessing cognition and psychological conditions.

AIM

To investigate the differences in eye movement between AD patients with and without depressive symptoms.

METHODS

Eye movement data of 65 AD patients were compared between the depressed AD (D-AD) and non-depressed AD (nD-AD) groups. Logistic regression analysis was employed to identify diagnostic biomarkers and the ROC curve was plotted. The correlation between eye movement and HAMD-17 scores was assessed by partial correlation analysis.

RESULTS

The D-AD patients showed longer saccade latency and faster average/peak saccade velocities in the overlap prosaccade test, longer average reaction time and faster average saccade velocity in the gap prosaccade test, longer start-up durations, slower pursuit velocity, more offsets, and larger total offset degrees in the smooth pursuit test, and poorer fixation stability in both the central and lateral fixation tests compared to nD-AD patients. The start-up duration in the smooth pursuit test and the number of offsets in the central fixation test were identified as the diagnostic eye movement parameters for D-AD patients with the area under the ROC curves of 0.8011. Partial correlation analysis revealed that the start-up duration and pursuit velocity in the smooth pursuit test and the total offset degrees in the lateral fixation test were correlated with HAMD-17 scores in D-AD patients.

DISCUSSION AND CONCLUSIONS

Eye movement differences may help to differentiate D-AD patients from nD-AD patients in a non-invasive and cost-effective manner.

The application of saccades to assess cognitive impairment among older adults: a systematic review and meta-analysis

BACKGROUND

Saccade is a novel and feasible method for cognition assessment and has potential to screen older people with cognitive impairment.

OBJECTIVES

To systematically summarize the evidence and determine whether different saccade parameters can effectively identify patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD).

METHODS

English and Chinese databases were searched until 19 April 2022. Studies analyzing saccade parameters in older adults with normal cognition, MCI, or AD were included. Two researchers independently performed the screening, data extraction, and quality appraisal. Meta-analyses were conducted and standard mean differences and 95% confidence intervals were estimated with a random effects model.

RESULTS

Thirty-five studies were included, and 26 studies were pooled for the meta-analysis. The results demonstrated that patients with cognitive impairment exhibited longer latency and lower accuracy rates in the prosaccade and antisaccade tasks, along with lower corrected error rates in the antisaccade tasks. However, the pooled results for antisaccades were more stable, providing the ability to distinguish patients with cognitive impairment among older adults. The results of the subgroup analyses revealed that only the accuracy rates of the antisaccades differed significantly between people with MCI and AD. Regarding the differences between older adults with normal cognition and those with MCI, the effect sizes of latency and the accuracy rates of saccades as well as the corrected error rates of antisaccades were significant.

CONCLUSIONS

Saccades, especially antisaccades, are a potential screening and assessment tool for distinguishing older adults with MCI or AD from those with normal cognition.

Correlating Eye-Tracking Fixation Metrics and Neuropsychological Assessment after Ischemic Stroke

Background and Objectives: Stroke survivors commonly experience cognitive deficits, which significantly impact their quality of life. Integrating modern technologies like eye tracking into cognitive assessments can provide objective and non-intrusive measurements. Materials and Methods: This study aimed to evaluate the cognitive and visual processing capabilities of stroke patients using eye-tracking metrics and psychological evaluations. A cohort of 84 ischemic stroke patients from the N-PEP-12 clinical study was selected for secondary analysis, based on the availability of eye-tracking data collected during a visual search task using an adapted Trail Making Test. Standardized cognitive assessments, including the Montreal Cognitive Assessment (MoCA) and digit span tasks, were also conducted. Results: Correlation analyses revealed some notable relationships between eye-tracking metrics and cognitive measures, such as a positive correlation between Symbol Search performance and the number of fixations. Anxiety levels were found to be positively correlated with first fixation duration, while longer first fixation durations were associated with poorer cognitive performance. However, most correlations were not statistically significant. Nonparametric ANOVA showed no significant differences in fixation metrics across the visits. Conclusions: These findings suggest a complex relationship between cognitive status, gaze fixation behavior, and psychological well-being in stroke patients. Further research with larger sample sizes and analysis of saccadic eye movements is needed to better understand these relationships and inform effective interventions for stroke rehabilitation.

Eyes on dementia: an overview of the interplay between eye movements and cognitive decline

The economic and disease burden of dementia is forecasted to continue increasing. Considering its cognitive effects, timely diagnosis is important in developing a stage-based treatment plan and gathering data to support advocacy efforts and plan healthcare and social services. Eye-tracking technology has emerged as an efficient diagnostic tool in clinical practice and experimental studies. This review aimed to comprehensively analyze various aspects of eye-tracking technology, including pupillometry parameters, eye movements, eye-tracking devices, and neuropsychological tools. We conducted a systematic review retrieving articles published in the last ten years from six databases. Our results provide a complex overview for each included form of dementia/cognitive decline in terms of patient characteristics (age, sex-disaggregated by included pathologies), inclusion and exclusion criteria, devices, and neuropsychological tools. We also summarized findings on fixation stability tasks, saccadic evaluation, pupillometry, scene perception, object recognition, spatial memory, eye-tracking video tasks, and visual search. The eye-tracking method has become more common in cognitive assessments.

Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury

The study of ocular manifestations of neurodegenerative disorders, Oculomics, is a growing field of investigation for early diagnostics, enabling structural and chemical biomarkers to be monitored overtime to predict prognosis. Traumatic brain injury (TBI) triggers a cascade of events harmful to the brain, which can lead to neurodegeneration. TBI, termed the "silent epidemic" is becoming a leading cause of death and disability worldwide. There is currently no effective diagnostic tool for TBI, and yet, early-intervention is known to considerably shorten hospital stays, improve outcomes, fasten neurological recovery and lower mortality rates, highlighting the unmet need for techniques capable of rapid and accurate point-of-care diagnostics, implemented in the earliest stages. This review focuses on the latest advances in the main neuropathophysiological responses and the achievements and shortfalls of TBI diagnostic methods. Validated and emerging TBI-indicative biomarkers are outlined and linked to ocular neuro-disorders. Methods detecting structural and chemical ocular responses to TBI are categorised along with prospective chemical and physical sensing techniques. Particular attention is drawn to the potential of Raman spectroscopy as a non-invasive sensing of neurological molecular signatures in the ocular projections of the brain, laying the platform for the first tangible path towards alternative point-of-care diagnostic technologies for TBI.

Low-level factors increase gaze-guidance under cognitive load: A comparison of image-salience and semantic-salience models

Growing evidence links eye movements and cognitive functioning, however there is debate concerning what image content is fixated in natural scenes. Competing approaches have argued that low-level/feedforward and high-level/feedback factors contribute to gaze-guidance. We used one low-level model (Graph Based Visual Salience, GBVS) and a novel language-based high-level model (Global Vectors for Word Representation, GloVe) to predict gaze locations in a natural image search task, and we examined how fixated locations during this task vary under increasing levels of cognitive load. Participants (N = 30) freely viewed a series of 100 natural scenes for 10 seconds each. Between scenes, subjects identified a target object from the scene a specified number of trials (N) back among three distracter objects of the same type but from alternate scenes. The N-back was adaptive: N-back increased following two correct trials and decreased following one incorrect trial. Receiver operating characteristic (ROC) analysis of gaze locations showed that as cognitive load increased, there was a significant increase in prediction power for GBVS, but not for GloVe. Similarly, there was no significant difference in the area under the ROC between the minimum and maximum N-back achieved across subjects for GloVe (t(29) = -1.062, p = 0.297), while there was a cohesive upwards trend for GBVS (t(29) = -1.975, p = .058), although not significant. A permutation analysis showed that gaze locations were correlated with GBVS indicating that salient features were more likely to be fixated. However, gaze locations were anti-correlated with GloVe, indicating that objects with low semantic consistency with the scene were more likely to be fixated. These results suggest that fixations are drawn towards salient low-level image features and this bias increases with cognitive load. Additionally, there is a bias towards fixating improbable objects that does not vary under increasing levels of cognitive load.

A single-center, randomized, parallel design study to evaluate the efficacy of donepezil in improving visuospatial abilities in patients with mild cognitive impairment using eye-tracker: the COG-EYE study protocol for a phase II trial

Background

Cholinesterase inhibitors (ChEIs) decrease long-term cognitive decline in patients with Alzheimer’s disease (AD); however, there is little evidence that ChEIs affect cognitive test scores in patients with mild cognitive impairment (MCI). Conventional endpoints, such as cognitive tests or clinical rating scores, may lack the sensitivity to subtle treatment effects in participants with MCI. Therefore, there is an immediate need to refocus on direct physiological assessments to detect the effects of ChEIs in patients with MCI due to AD.

Methods

We propose a randomized controlled trial to evaluate the effect of donepezil, a ChEI, on patients with MCI due to AD. We plan to recruit 78 participants (39 in each arm) with MCI who had amyloid positron emission tomography (PET)-positive results for this open-label study. To evaluate subtle differences, we will measure eye-tracking metrics and digital pen data while participants perform the simplified Rey Complex Figure (RCFT) and clock drawing tests. The primary outcome is a change in the ratio of the number of fixations (working space/perceptual space) performed using the simplified RCFT, from baseline to 12 weeks, as assessed using eye-tracking metrics. The secondary outcomes are changes in general cognition, clinical severity, activities of daily living, and visuospatial function assessed using standard rating scores and digital pen data. The analyses of the primary and secondary outcomes will be based on the difference in changes during follow-up between the donepezil and control groups using the t-test or Mann–Whitney U test, as well as adjusting for baseline values.

Discussion

This study is designed to determine whether eye-tracking metrics can detect the effect of donepezil on visuospatial dysfunction more sensitively in patients with MCI. It is expected that multimodal data, such as eye-tracking and digital pen data, may provide helpful biomarkers for identifying subtle changes that are difficult to measure using conventional methods.

Trial registration

Clinical Research Information Service, Republic of Korea (CRIS, cris.nih.go.kr) KCT0006236. Registered on June 10, 2021.

Eye-Tracking Metrics for Figure-Copying Processes in Early- vs. Late-Onset Alzheimer's Disease

Visuospatial dysfunction is a common symptom in patients with Alzheimer's disease (AD). To more focus on copying processes rather than on finally completed figures, we conceptually split the copying processes into three stages: visuoperceptual function, visuoconstructional function, and working memory function. We constructed perceptual and working spaces to investigate the different stages of copying, and then, we compared the number and duration of fixations and saccades and the number of switches across the two spaces. We used eye-tracking glasses to assess eye-tracking metrics in patients with early-onset AD (EOAD), patients with late-onset AD (LOAD), and normal control (NC) participants while they copied the simplified Rey–Osterrieth complex figure test (RCFT). Regarding eye metrics on the perceptual space, the number and duration of fixations were greater in both groups of patients with AD than in the NC participants group (number: EOAD vs. NC: p < 0.001, LOAD vs. NC: p = 0. 003/ duration: EOAD vs. NC: p < 0.001, LOAD vs. NC: p < 0.001). On the working space, the number and duration of fixations were greater in the patients with EOAD than in the patients with LOAD and NC participants (number: EOAD vs. LOAD: p = 0. 007, EOAD vs. NC: p = 0. 001/duration: EOAD vs. LOAD: p = 0. 008, EOAD vs. NC: p = 0. 002). The number of saccades and switching was higher in patients with EOAD than in NC participants (p < 0.001). The eye-tracking metrics from the simplified RCFT correlated with the neuropsychological test scores. Patients with EOAD and LOAD achieved the same level of performance at the simplified and original RCFT scores. However, patients with EOAD than LOAD showed a greater number and duration of fixations on the working space and more frequent switching between the perceptual and working spaces, which may reflect more cognitive efforts to achieve the same level of performance.

Impact of Alzheimer's Disease in Ocular Motility and Visual Perception: A Narrative Review

PURPOSE

Alzheimer's disease (AD) is a neurodegenerative disease generating a progressive neuronal loss as well as cognitive deficiencies. This disease can be accompanied by ocular manifestations, including alterations in ocular motility and visual perception. The aim of the current review article was to collect all the information about these alterations and to analyze if there is scientific evidence supporting the potential use of these changes as biomarkers of the disease.

METHODS

A bibliographic search was performed using two different databases, Pubmed and Google Scholar, as well as a search of material in non-peer reviewed journals about Alzheimer's and Neurology. A total of 227 articles were found in the initial search, but only 76 were included considering their relevance according to the purpose of the reviewResults: This narrative review describes the findings obtained in this area to this date, confirming that deficiencies in saccades is the most common condition among AD patients. Furthermore, other visual alterations have also been reported in these patients, including a compromise of visual acuity and contrast sensitivity, fluctuations of colour vision, stereopsis impairment and visual field losses. Likewise, other complex visuo-spatial and visuo-perceptual impairments can be present. More studies are still needed to understand better what type of changes occurs in ocular alignment, binocularity, and fixation pattern in AD patients.

CONCLUSIONS

AD is associated to visual perception and ocular motility alterations. All the scientific information found in this review should be considered as a guide for designing future studies and to define adequate clinical protocols for the visual evaluation of patients with AD, considering the cognitive limitations that are normally present in this type of patients.

Pilot Study: The Queen Square Screening Test for Visual Deficits in Dementia

The Queen Square Screening Test for Visual Deficits (QS test) screens for changes in visual processing. Our pilot study aimed to review the applicability of the QS test in individuals with dementia compared with those with normal cognition. Participants with major and minor neurocognitive disorder scored 50/71 (n=12) and 61/71 (n=10) respectively on the QS test, compared to 65/71 for age-matched healthy controls (n=11). The QS test score correlated with cognitive impairment as measured using the Rowland Universal Dementia Assessment Scale (r = 0.74). The QS test is an affordable and easy bedside screening test for visual processing changes.

Classification of Alzheimer's Disease Leveraging Multi-task Machine Learning Analysis of Speech and Eye-Movement Data

Alzheimer's disease (AD) is a progressive neurodegenerative condition that results in impaired performance in multiple cognitive domains. Preclinical changes in eye movements and language can occur with the disease, and progress alongside worsening cognition. In this article, we present the results from a machine learning analysis of a novel multimodal dataset for AD classification. The cohort includes data from two novel tasks not previously assessed in classification models for AD (pupil fixation and description of a pleasant past experience), as well as two established tasks (picture description and paragraph reading). Our dataset includes language and eye movement data from 79 memory clinic patients with diagnoses of mild-moderate AD, mild cognitive impairment (MCI), or subjective memory complaints (SMC), and 83 older adult controls. The analysis of the individual novel tasks showed similar classification accuracy when compared to established tasks, demonstrating their discriminative ability for memory clinic patients. Fusing the multimodal data across tasks yielded the highest overall AUC of 0.83 ± 0.01, indicating that the data from novel tasks are complementary to established tasks.

Driving With Distraction: Measuring Brain Activity and Oculomotor Behavior Using fMRI and Eye-Tracking

Introduction

Driving motor vehicles is a complex task that depends heavily on how visual stimuli are received and subsequently processed by the brain. The potential impact of distraction on driving performance is well known and poses a safety concern - especially for individuals with cognitive impairments who may be clinically unfit to drive. The present study is the first to combine functional magnetic resonance imaging (fMRI) and eye-tracking during simulated driving with distraction, providing oculomotor metrics to enhance scientific understanding of the brain activity that supports driving performance.

Materials and Methods

As initial work, twelve healthy young, right-handed participants performed turns ranging in complexity, including simple right and left turns without oncoming traffic, and left turns with oncoming traffic. Distraction was introduced as an auditory task during straight driving, and during left turns with oncoming traffic. Eye-tracking data were recorded during fMRI to characterize fixations, saccades, pupil diameter and blink rate.

Results

Brain activation maps for right turns, left turns without oncoming traffic, left turns with oncoming traffic, and the distraction conditions were largely consistent with previous literature reporting the neural correlates of simulated driving. When the effects of distraction were evaluated for left turns with oncoming traffic, increased activation was observed in areas involved in executive function (e.g., middle and inferior frontal gyri) as well as decreased activation in the posterior brain (e.g., middle and superior occipital gyri). Whereas driving performance remained mostly unchanged (e.g., turn speed, time to turn, collisions), the oculomotor measures showed that distraction resulted in more consistent gaze at oncoming traffic in a small area of the visual scene; less time spent gazing at off-road targets (e.g., speedometer, rear-view mirror); more time spent performing saccadic eye movements; and decreased blink rate.

Conclusion

Oculomotor behavior modulated with driving task complexity and distraction in a manner consistent with the brain activation features revealed by fMRI. The results suggest that eye-tracking technology should be included in future fMRI studies of simulated driving behavior in targeted populations, such as the elderly and individuals with cognitive complaints - ultimately toward developing better technology to assess and enhance fitness to drive.

Eye tracking based dyslexia detection using a holistic approach

A new detection method for cognitive impairments is presented utilizing an eye tracking signals in a text reading test. This research enhances published articles that extract combination of various features. It does so by processing entire eye-tracking records either in time or frequency whereas applying only basic signal pre-processing. Such signals were classified as a whole by Convolutional Neural Networks (CNN) that hierarchically extract substantial features scatter either in time or frequency and nonlinearly binds them using machine learning to minimize a detection error. In the experiments we used a 100 fold cross validation and a dataset containing signals of 185 subjects (88 subjects with low risk and 97 subjects with high risk of dyslexia). In a series of experiments it was found that magnitude spectrum based representation of time interpolated eye-tracking signals recorded the best results, i.e. an average accuracy of 96.6% was reached in comparison to 95.6% that is the best published result on the same database. These findings suggest that a holistic approach involving small but complex enough CNNs applied to properly pre-process and expressed signals provides even better results than a combination of meticulously selected well-known features.

Visual Search Efficiency in Mild Cognitive Impairment and Alzheimer's Disease: An Eye Movement Study

BACKGROUND

Visual search abilities are essential to everyday life activities and are known to be affected in Alzheimer's disease (AD). However, little is known about visual search efficiency in mild cognitive impairment (MCI), a transitive state between normal aging and dementia. Eye movement studies and machine learning methods have been recently used to detect oculomotor impairments in individuals with dementia.

OBJECTIVE

The aim of the present study is to investigate the association between eye movement metrics and visual search impairment in MCI and AD.

METHODS

127 participants were tested: 43 healthy controls, 51 with MCI, and 33 with AD. They completed an eyetracking visual search task where they had to find a previously seen target stimulus among distractors.

RESULTS

Both patient groups made more fixations on the screen when searching for a target, with longer duration than controls. MCI and AD fixated the distractors more often and for a longer period of time than the target. Healthy controls were quicker and made less fixations when scanning the stimuli for the first time. Machine-learning methods were able to distinguish between controls and AD subjects and to identify MCI subjects with a similar oculomotor profile to AD with a good accuracy.

CONCLUSION

Results showed that eye movement metrics are useful for identifying visual search impairments in MCI and AD, with possible implications in the early identification of individuals with high-risk of developing AD.

Saccadic Eye Movement in Mild Cognitive Impairment and Alzheimer's Disease: A Systematic Review and Meta-Analysis

Alzheimer’s disease (AD) is the leading cause of dementia, and mild cognitive impairment (MCI) is considered the transitional state to AD dementia (ADD) and other types of dementia, whose symptoms are accompanied by altered eye movement. In this work, we reviewed the existing literature and conducted a meta-analysis to extract relevant eye movement parameters that are significantly altered owing to ADD and MCI. We conducted a systematic review of 35 eligible original publications in saccade paradigms and a meta-analysis of 27 articles with specified task conditions, which used mainly gap and overlap conditions in both prosaccade and antisaccade paradigms. The meta-analysis revealed that prosaccade and antisaccade latencies and frequency of antisaccade errors showed significant alterations for both MCI and ADD. First, both prosaccade and antisaccade paradigms differentiated patients with ADD and MCI from controls, however, antisaccade paradigms was more effective than prosaccade paradigms in distinguishing patients from controls. Second, during prosaccade in the gap and overlap conditions, patients with ADD had significantly longer latencies than patients with MCI, and the trend was similar during antisaccade in the gap condition as patients with ADD had significantly more errors than patients with MCI. The anti-effect magnitude was similar between controls and patients, and the magnitude of the latency of the gap effect varied among healthy controls and MCI and ADD subjects, but the effect size of the latency remained large in both patients. These findings suggest that, using gap effect, anti-effect, and specific choices of saccade paradigms and conditions, distinctions could be made between MCI and ADD patients as well as between patients and controls.

The Investigation of Simultaneous EEG and Eye Tracking Characteristics During Fixation Task in Mild Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder that occurs many years before the first clinical symptoms. Finding more exact, significant, and valuable criteria or indices for the diagnosis of the mild form of Alzheimer's disease is very important for clinical and research purposes. Electroencephalography (EEG) and eye tracking biomarkers would provide noninvasive tools for the early detection of AD. Due to the advantages of EEG and eye tracking, in this study, we employed them simultaneously to conduct research on the mild AD. For this purpose, 19 patients with mild AD were compared with 19 gender- and age-matched normal subjects who did not have any history of cognitive or neurological disorders. EEG and eye-tracking data were concurrently collected in both groups in a fixation task. Our results revealed that the total fixation duration was significantly shorter for the AD patients, but their fixation frequency was more than that of the controls. In addition, increased theta power and decreased alpha power were observed in the AD group. Interestingly, there was a statistically significant correlation between fixation frequency and alpha power in the parietal area in the control group. However, this connection was not statistically significant in the AD group. The findings also indicated an elevated coherence in the AD patients in the parieto-occipital area. It is assumed that the AD patients might use the neural compensational processes for the fixation state. This study provides evidence for the simultaneously EEG and eye-tracking changes in the areas, which are involved in the control of the fixational eye movements.

Artificial intelligence in neurodegenerative diseases: A review of available tools with a focus on machine learning techniques

Neurodegenerative diseases have shown an increasing incidence in the older population in recent years. A significant amount of research has been conducted to characterize these diseases. Computational methods, and particularly machine learning techniques, are now very useful tools in helping and improving the diagnosis as well as the disease monitoring process. In this paper, we provide an in-depth review on existing computational approaches used in the whole neurodegenerative spectrum, namely for Alzheimer's, Parkinson's, and Huntington's Diseases, Amyotrophic Lateral Sclerosis, and Multiple System Atrophy. We propose a taxonomy of the specific clinical features, and of the existing computational methods. We provide a detailed analysis of the various modalities and decision systems employed for each disease. We identify and present the sleep disorders which are present in various diseases and which represent an important asset for onset detection. We overview the existing data set resources and evaluation metrics. Finally, we identify current remaining open challenges and discuss future perspectives.

Distinctive Oculomotor Behaviors in Alzheimer's Disease and Frontotemporal Dementia

Oculomotor behavior can provide insight into the integrity of widespread cortical networks, which may contribute to the differential diagnosis between Alzheimer's disease and frontotemporal dementia. Three groups of patients with Alzheimer's disease, behavioral variant of frontotemporal dementia (bvFTD) and semantic variant of primary progressive aphasia (svPPA) and a sample of cognitively unimpaired elders underwent an eye-tracking evaluation. All participants in the discovery sample, including controls, had a biomarker-supported diagnosis. Oculomotor correlates of neuropsychology and brain metabolism evaluated with 18F-FDG PET were explored. Machine-learning classification algorithms were trained for the differentiation between Alzheimer's disease, bvFTD and controls. A total of 93 subjects (33 Alzheimer's disease, 24 bvFTD, seven svPPA, and 29 controls) were included in the study. Alzheimer's disease was the most impaired group in all tests and displayed specific abnormalities in some visually-guided saccade parameters, as pursuit error and horizontal prosaccade latency, which are theoretically closely linked to posterior brain regions. BvFTD patients showed deficits especially in the most cognitively demanding tasks, the antisaccade and memory saccade tests, which require a fine control from frontal lobe regions. SvPPA patients performed similarly to controls in most parameters except for a lower number of correct memory saccades. Pursuit error was significantly correlated with cognitive measures of constructional praxis and executive function and metabolism in right posterior middle temporal gyrus. The classification algorithms yielded an area under the curve of 97.5% for the differentiation of Alzheimer's disease vs. controls, 96.7% for bvFTD vs. controls, and 92.5% for Alzheimer's disease vs. bvFTD. In conclusion, patients with Alzheimer's disease, bvFTD and svPPA exhibit differentiating oculomotor patterns which reflect the characteristic neuroanatomical distribution of pathology of each disease, and therefore its assessment can be useful in their diagnostic work-up. Machine learning approaches can facilitate the applicability of eye-tracking in clinical practice.

Augmenting Dementia Cognitive Assessment With Instruction-Less Eye-Tracking Tests

Eye-tracking technology is an innovative tool that holds promise for enhancing dementia screening. In this work, we introduce a novel way of extracting salient features directly from the raw eye-tracking data of a mixed sample of dementia patients during a novel instruction-less cognitive test. Our approach is based on self-supervised representation learning where, by training initially a deep neural network to solve a pretext task using well-defined available labels (e.g. recognising distinct cognitive activities in healthy individuals), the network encodes high-level semantic information which is useful for solving other problems of interest (e.g. dementia classification). Inspired by previous work in explainable AI, we use the Layer-wise Relevance Propagation (LRP) technique to describe our network's decisions in differentiating between the distinct cognitive activities. The extent to which eye-tracking features of dementia patients deviate from healthy behaviour is then explored, followed by a comparison between self-supervised and handcrafted representations on discriminating between participants with and without dementia. Our findings not only reveal novel self-supervised learning features that are more sensitive than handcrafted features in detecting performance differences between participants with and without dementia across a variety of tasks, but also validate that instruction-less eye-tracking tests can detect oculomotor biomarkers of dementia-related cognitive dysfunction. This work highlights the contribution of self-supervised representation learning techniques in biomedical applications where the small number of patients, the non-homogenous presentations of the disease and the complexity of the setting can be a challenge using state-of-the-art feature extraction methods.

The Role of Eye Tracking Technology in Assessing Older Driver Safety

A growing body of literature is focused on the use of eye tracking (ET) technology to understand the association between objective visual parameters and higher order brain processes such as cognition. One of the settings where this principle has found practical utility is in the area of driving safety.

METHODS

We reviewed the literature to identify the changes in ET parameters with older adults and neurodegenerative disease.

RESULTS

This narrative review provides a brief overview of oculomotor system anatomy and physiology, defines common eye movements and tracking variables that are typically studied, explains the most common methods of eye tracking measurements during driving in simulation and in naturalistic settings, and examines the association of impairment in ET parameters with advanced age and neurodegenerative disease.

CONCLUSION

ET technology is becoming less expensive, more portable, easier to use, and readily applicable in a variety of clinical settings. Older adults and especially those with neurodegenerative disease may have impairments in visual search parameters, placing them at risk for motor vehicle crashes. Advanced driver assessment systems are becoming more ubiquitous in newer cars and may significantly reduce crashes related to impaired visual search, distraction, and/or fatigue.

Eye tracking metrics to screen and assess cognitive impairment in patients with neurological disorders

PURPOSE OF REVIEW

Eye tracking is a powerful method to investigate the relationship between behavior and neural mechanisms. In recent years, eye movement analysis has been used in patients with neurological disorders to assess cognitive function. In this review, we explore the latest eye tracking researches in neurological disorders that are commonly associated with cognitive deficits, specifically, amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), and epilepsy. We focus on the application of ocular measures in these disorders, with the goal of understanding how eye tracking technology can be used in the clinical setting.

FINDINGS

Eye tracking tasks (especially saccadic tasks) are often used as an adjunct to traditional scales for cognitive assessment. Eye tracking data confirmed that executive dysfunction is common in PD and ALS, whereas AD and MS are characterized by attention deficits. Research in evaluating cognitive function in epilepsy using eye tracking is still in its early stages, but this approach has shown advantages as a sensitive quantitative method with high temporal and spatial resolution. Eye tracking technology can facilitate the assessment of cognitive impairment with higher temporal resolution and finer granularity than traditional cognitive assessment. Oculomotor data collected during cognitive tasks can provide insight into biological processes. Eye tracking provides a nonverbal and less cognitively demanding method of measuring disease progression in cognitively impaired patients.

Systemic hepcidin quantified with LC-MS/MS in dementia in association with disease pathology and severity and with structural changes in the brain

Hepcidin is a peptide hormone regulating iron metabolism, the dyshomeostasis of which has been implicated in dementia. Yet, data on hepcidin status in dementia are scanty, limited to Alzheimer's disease (AD) and inconsistent due to methodological problems with its determination using immunoassays and/or lack of homogeneity of evaluated groups. Hepcidin association with vascular dementia (VaD) remains unknown. We proposed a mass spectrometry method of hepcidin quantification in sera and aimed at determining hepcidin systemic status in patients with dementia of AD, VaD, or mixed (MD) pathology, with reference to the degree of cognitive loss and structural changes in the brain as well as at evaluating the diagnostic potential of hepcidin as a biomarker. We found that hepcidin concentrations were significantly elevated in VaD and insignificantly so in AD or MD and that they positively correlated with the Clinical Dementia Rating and inversely with the Mini Mental State Examination. Hepcidin tended to be more pronouncedly elevated in patients with advanced cortical atrophy and white matter lesions. It displayed a biphasic relationship with the Hachinski Ischemic Scale and a good accuracy as dementia but not differential marker. Taken together, our results demonstrated that dementia of vascular and not neurodegenerative pathology is associated with significant elevation of systemic hepcidin. Hepcidin elevation reflects the degree of cognitive loss as well as the severity of structural changes in the brain. If confirmed in a prospective study, hepcidin quantification may hold promise as a diagnostic marker; its accuracy as a differential marker of VaD is insufficient.

Aging and eye tracking: in the quest for objective biomarkers

Recent applications of eye tracking for diagnosis, prognosis and follow-up of therapy in age-related neurological or psychological deficits have been reviewed. The review is focused on active aging, neurodegeneration and cognitive impairments. The potential impacts and current limitations of using characterizing features of eye movements and pupillary responses (oculometrics) as objective biomarkers in the context of aging are discussed. A closer look into the findings, especially with respect to cognitive impairments, suggests that eye tracking is an invaluable technique to study hidden aspects of aging that have not been revealed using any other noninvasive tool. Future research should involve a wider variety of oculometrics, in addition to saccadic metrics and pupillary responses, including nonlinear and combinatorial features as well as blink- and fixation-related metrics to develop biomarkers to trace age-related irregularities associated with cognitive and neural deficits.

Eye tracking - The overlooked method to measure cognition in neurodegeneration?

Eye tracking (ET) studies are becoming increasingly popular due to rapid methodological and technological advances as well as the development of cost efficient and portable eye trackers. Although historically ET has been mostly employed in psychophysics or developmental cognition studies, there is also promising scope to use ET for movement disorders and measuring cognitive processes in neurodegeneration. Particularly, ET can be a powerful tool for cognitive and neuropsychological assessments of patients with pathologies affecting motor and verbal abilities, as tasks can be adapted without requiring motor (except eye movements) or verbal responses. In this review, we will examine the existing evidence of ET methods in neurodegenerative conditions and its potential clinical impact for cognitive assessment. We highlight that current evidence for ET is mostly focused on diagnostics of cognitive impairments in neurodegenerative disorders, where it is debatable whether it has any more sensitivity or specificity than existing cognitive assessments. By contrast, there is currently a lack of ET studies in more advanced disease stages, when patients' motor and verbal functions can be significantly affected, and standard cognitive assessments are challenging or often not possible. We conclude that ET is a promising method not only for cognitive diagnostics but more importantly, for potential cognitive disease tracking in progressive neurodegenerative conditions.

Novel Method for Rapid Assessment of Cognitive Impairment Using High-Performance Eye-Tracking Technology

A rapid increase in the number of patients with dementia has emerged as a global health challenge. Accumulating evidence suggests that early diagnosis and timely intervention can delay cognitive decline. The diagnosis of dementia is commonly performed using neuropsychological tests, such as the Mini-Mental State Examination (MMSE), administered by trained examiners. While these traditional neuropsychological tests are valid and reliable, they are neither simple nor sufficiently short as routine screening tools for dementia. Here, we developed a brief cognitive assessment utilizing an eye-tracking technology. The subject views a series of short (178 s) task movies and pictures displayed on a monitor while their gaze points are recorded by the eye-tracking device, and the cognitive scores are determined from the gaze plots data. The cognitive scores were measured by both an eye tracking-based assessment and neuropsychological tests in 80 participants, including 27 cognitively healthy controls (HC), 26 patients with mild cognitive impairment (MCI), and 27 patients with dementia. The eye tracking-based cognitive scores correlated well with the scores from the neuropsychological tests, and they showed a good diagnostic performance in detecting patients with MCI and dementia. Rapid cognitive assessment using eye-tracking technology can enable quantitative scoring and the sensitive detection of cognitive impairment.

Neural Mechanisms of Visual Dysfunction in Posterior Cortical Atrophy

Posterior cortical atrophy (PCA) is characterized predominantly by visual dysfunction that arises from bilateral impairments in occipital, parietal, and temporal regions of the brain. PCA is clinically identified based primarily on visual symptoms and neuroimaging findings. Region-specific gray and white matter deficits have been discussed in detail, and are associated with clinical manifestations that present with similar patterns of perfusion and metabolic findings. Here, we discuss both structural and functional changes in the ventral and dorsal visual streams along with their underlying relationships. We also discuss the most recent developments in neuroimaging characteristics and summarize correlations between distinct neuroimaging presentations.

Digital biomarkers for Alzheimer's disease: the mobile/ wearable devices opportunity

Alzheimer's Disease (AD) represents a major and rapidly growing burden to the healthcare ecosystem. A growing body of evidence indicates that cognitive, behavioral, sensory, and motor changes may precede clinical manifestations of AD by several years. Existing tests designed to diagnose neurodegenerative diseases, while well-validated, are often less effective in detecting deviations from normal cognitive decline trajectory in the earliest stages of the disease. In the quest for gold standards for AD assessment, there is a growing interest in the identification of readily accessible digital biomarkers, which harness advances in consumer grade mobile and wearable technologies. Topics examined include a review of existing early clinical manifestations of AD and a path to the respective sensor and mobile/wearable device usage to acquire domain-centric data towards objective, high frequency and passive digital phenotyping.

Eye Movements in Neuropsychological Tasks

This chapter reviews how recording and analysis of eye movements have been applied to understanding cognitive functioning in patients with neurological disease. Measures derived from the performance of instructed eye movement tests such as the anti-saccade and memory-guided saccade tasks have been shown to be associated with cognitive test performance and the early stages of neurodegenerative disorders including Alzheimer's and Parkinson's disease. Other researchers have taken an ecological approach and recorded the uninstructed pattern of saccades made by patients during performance of established neuropsychological tasks. Studies that have analysed the eye movement strategies used in a number of widely used tests are reviewed, including the Corsi blocks, Tower of London, 'CANTAB' Spatial Working Memory and Brixton Spatial Anticipation test. The findings illustrate that eye movements are not purely in the service of vision, but support visuospatial working memory and forward action planning. Eye movement tests and measures also have potential for application in the assessment and diagnosis of neurological disease and cognitive impairment. Establishing large-scale normative data sets in healthy older adults and use of machine learning multivariate classifier algorithms may be key to further developing eye tracking applications in neuropsychological assessment.

Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer's Disease: A Review

An opportune early diagnosis of Alzheimer's disease (AD) would help to overcome symptoms and improve the quality of life for AD patients. Research studies have identified early manifestations of AD that occur years before the diagnosis. For instance, eye movements of people with AD in different tasks differ from eye movements of control subjects. In this review, we present a summary and evolution of research approaches that use eye tracking technology and computational analysis to measure and compare eye movements under different tasks and experiments. Furthermore, this review is targeted to the feasibility of pioneer work on developing computational tools and techniques to analyze eye movements under naturalistic scenarios. We describe the progress in technology that can enhance the analysis of eye movements everywhere while subjects perform their daily activities and give future research directions to develop tools to support early AD diagnosis through analysis of eye movements.