The effectiveness of eye tracking in the diagnosis of cognitive disorders: A systematic review and meta-analysis

Cognition and saccadic eye movement performance are impaired in chronic rhinosinusitis

BACKGROUND

Patients with chronic rhinosinusitis (CRS) can experience cognitive dysfunction. The literature on this topic mostly reflects patient-reported measurements. Our goal was to assess cognitive function in patients with CRS using objective measures, including saccadic eye movements-a behavioral response reflecting cognitive and sensory information integration that is often compromised in conditions with impaired cognition.

METHODS

Participants (N = 24 with CRS, N = 23 non-CRS healthy controls) enrolled from rhinology clinic underwent sinonasal evaluation, quality of life assessment (Sino-nasal Outcome Test 22 [SNOT-22]), and cognitive assessment with the Neuro-QOL Cognitive Function-Short Form, the Montreal Cognitive Assessment (MoCA), and recording of eye movements using video-oculography.

RESULTS

Participants with CRS were more likely to report cognitive dysfunction (Neuro-QOL; 45.8% vs. 8.7%; p = 0.005) and demonstrate mild or greater cognitive impairment (MoCA; 41.7% vs. 8.7%; p = 0.005) than controls. Additionally, participants with CRS performed worse on the MoCA overall and within the executive functioning and memory domains (all p < 0.05) and on the anti-saccade (p = 0.014) and delay saccade (p = 0.044) eye movement tasks. Poorer performance on the MoCA (r = -0.422; p = 0.003) and the anti-saccade (r = -0.347; p = 0.017) and delay saccade (r = -0.419; p = 0.004) eye movement tasks correlated with worse CRS severity according to SNOT-22 scores.

CONCLUSION

This study is the first to utilize objective eye movement assessments in addition to researcher-administered cognitive testing in patients with CRS. These patients demonstrated a high prevalence of cognitive dysfunction, most notably within executive functioning and memory domains, with the degree of dysfunction correlating with the severity of CRS.

Aging impairs reactive attentional control but not proactive distractor inhibition

Older adults tend to be more prone to distraction compared with young adults, and this age-related deficit has been attributed to a deficiency in inhibitory processing. However, recent findings challenge the notion that aging leads to global impairments in inhibition. To reconcile these mixed findings, we investigated how aging modulates multiple mechanisms of attentional control by tracking the timing and direction of eye movements. When engaged in feature-search mode and proactive distractor suppression, older adults made fewer first fixations to the target but inhibited the task-irrelevant salient distractor as effectively as did young adults. However, when engaged in singleton-search mode and required to reactively disengage from the distractor, older adults made significantly more first saccades toward the task-irrelevant salient distractor and showed increased fixation times in orienting to the target, longer dwell times on incorrect saccades, and increased saccadic reaction times compared with young adults. Our findings reveal that aging differently impairs attentional control depending on whether visual search requires proactive distractor suppression or reactive distractor disengagement. Furthermore, our oculomotor measures reveal both age-related deficits and age equivalence in various mechanisms of attention, including goal-directed orienting, selection history, disengagement, and distractor inhibition. These findings help explain why conclusions of age-related declines or age equivalence in mechanisms of attentional control are task specific and reveal that older adults do not exhibit global impairments in mechanisms of inhibition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Eye movements reveal age differences in how arousal modulates saliency priority but not attention processing speed

The arousal-biased competition theory posits that inducing arousal increases attentional priority of salient stimuli while reducing priority of non-pertinent stimuli. However, unlike in young adults, older adults rarely exhibit shifts in priority under increased arousal, and prior studies have proposed different neural mechanisms to explain how arousal differentially modulates selective attention in older adults. Therefore, we investigated how the threat of unpredictable shock differentially modulates attentional control mechanisms in young and older adults by observing eye movements. Participants completed two oculomotor search tasks in which the salient distractor was typically captured by attention (singleton search) or proactively suppressed (feature search). We found that arousal did not modulate attentional priority for any stimulus among older adults nor affect the speed of attention processing in either age group. Furthermore, we observed that arousal modulated pupil sizes and found a correlation between evoked pupil responses and oculomotor function. Our findings suggest age differences in how the locus coeruleus-noradrenaline system interacts with neural networks of attention and oculomotor function.

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

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

A detection model of cognitive impairment via the integrated gait and eye movement analysis from a large Chinese community cohort

INTRODUCTION

Whether the integration of eye-tracking, gait, and corresponding dual-task analysis can distinguish cognitive impairment (CI) patients from controls remains unclear.

METHODS

One thousand four hundred eighty-one participants, including 724 CI and 757 controls, were enrolled in this study. Eye movement and gait, combined with dual-task patterns, were measured. The LightGBM machine learning models were constructed.

RESULTS

A total of 105 gait and eye-tracking features were extracted. Forty-six parameters, including 32 gait and 14 eye-tracking features, showed significant differences between two groups (P < 0.05). Of these, the Gait_3Back-TurnTime and Dual-task cost-TurnTime patterns were significantly correlated with plasma phosphorylated tau 181 (p-tau181) level. A model based on dual-task gait, dual-task smooth pursuit, prosaccade, and anti-saccade achieved the best area under the receiver operating characteristics curve (AUC) of 0.987 for CI detection, while combined with p-tau181, the model discriminated mild cognitive impairment from controls with an AUC of 0.824.

DISCUSSION

Combining dual-task gait and dual-task eye-tracking analysis is feasible for the detection of CI.

HIGHLIGHTS

This is the first study to report the efficiency of integrated parameters of dual-task gait and eye-tracking for cognitive impairment (CI) detection in a large cohort. We identified 46 gait and eye-tracking features associated with CI, and two were correlated to plasma phosphorylated tau 181. We constructed the model based on dual-task gait, smooth pursuit, prosaccade, and anti-saccade, achieving the best area under the curve of 0.987 for CI detection.

Eye Tracking During Visual Paired-Comparison Tasks: A Systematic Review and Meta-Analysis of the Diagnostic Test Accuracy for Detecting Cognitive Decline

Background

Alzheimer's disease and mild cognitive impairment (MCI) progress silently, making early diagnosis challenging, especially in less educated populations. The visual paired comparison (VPC) task, utilizing eye-tracking movement (ETM) technology, offers a promising alternative for early detection of memory decline.

Objective

This systematic review and meta-analysis evaluated the efficacy of the VPC task, utilizing ETM as a tool for assessing age-related cognitive changes.

Methods

A comprehensive search across five databases and grey literature focused on healthy and impaired memory participants assessed through the ETM-based VPC task. The primary outcomes were novelty preference scores and eye movement metrics. The risk of bias of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Random-effects meta-analyses calculated Hedges' g effect size. Sensitivity and specificity of the VPC were meta-analytically pooled.

Results

The systematic review included 12 articles, involving 1,022 participants (aged 18 to 90 years, with education ranging from 6.5 to 20.0 years), with a low risk of bias and minimal applicability concerns across all items. Five studies contributed to the meta-analysis, revealing a significant effect favoring the VPC task for recognition memory detection (k = 9, g = -1.03). Pooled sensitivity and specificity analyses demonstrated VPC effectiveness as a recognition memory assessment tool (0.84 and 0.75, respectively).

Conclusions

The VPC task, utilizing ETM, may serve as a biomarker for early memory decline detection. Its use as a digital eye-tracking tool presents a possible alternative to traditional tests, warranting further research for application in neurodegenerative disease diagnosis.

Analyzing Eye Paths Using Fractals

Visual patterns reflect the anatomical and cognitive background underlying process governing how we perceive information, influenced by stimulus characteristics and our own visual perception. These patterns are both spatially complex and display self-similarity seen in fractal geometry at different scales, making them challenging to measure using the traditional topological dimensions used in Euclidean geometry.However, methods for measuring eye gaze patterns using fractals have shown success in quantifying geometric complexity, matchability, and implementation into machine learning methods. This success is due to the inherent capabilities that fractals possess when reducing dimensionality using Hilbert curves, measuring temporal complexity using the Higuchi fractal dimension (HFD), and determining geometric complexity using the Minkowski-Bouligand dimension.Understanding the many applications of fractals when measuring and analyzing eye gaze patterns can extend the current growing body of knowledge by identifying markers tied to neurological pathology. Additionally, in future work, fractals can facilitate defining imaging modalities in eye tracking diagnostics by exploiting their capability to acquire multiscale information, including complementary functions, structures, and dynamics.

Utilizing artificial intelligence-based eye tracking technology for screening ADHD symptoms in children

Objective

To explore the potential of using artificial intelligence (AI)-based eye tracking technology on a tablet for screening Attention-deficit/hyperactivity disorder (ADHD) symptoms in children.

Methods

We recruited 112 children diagnosed with ADHD (ADHD group; mean age: 9.40 ± 1.70 years old) and 325 typically developing children (TD group; mean age: 9.45 ± 1.59 years old). We designed a data-driven end-to-end convolutional neural network appearance-based model to predict eye gaze to permit eye-tracking under low resolution and sampling rates. The participants then completed the eye tracking task on a tablet, which consisted of a simple fixation task as well as 14 prosaccade (looking toward target) and 14 antisaccade (looking away from target) trials, measuring attention and inhibition, respectively.

Results

Two-way MANOVA analyses demonstrated that diagnosis and age had significant effects on performance on the fixation task [diagnosis: F(2, 432) = 8.231, ***p < 0.001; Wilks' Λ = 0.963; age: F(2, 432) = 3.999, *p < 0.019; Wilks' Λ = 0.982], prosaccade task [age: F(16, 418) = 3.847, ***p < 0.001; Wilks' Λ = 0.872], and antisaccade task [diagnosis: F(16, 418) = 1.738, *p = 0.038; Wilks' Λ = 0.938; age: F(16, 418) = 4.508, ***p < 0.001; Wilks' Λ = 0.853]. Correlational analyses revealed that participants with higher SNAP-IV score were more likely to have shorter fixation duration and more fixation intervals (r = -0.160, 95% CI [0.250, 0.067], ***p < 0.001), poorer scores on adjusted prosaccade accuracy, and poorer scores on antisaccade accuracy (Accuracy: r = -0.105, 95% CI [-0.197, -0.011], *p = 0.029; Adjusted accuracy: r = -0.108, 95% CI [-0.200, -0.015], *p = 0.024).

Conclusion

Our AI-based eye tracking technology implemented on a tablet could reliably discriminate eye movements of the TD group and the ADHD group, providing a potential solution for ADHD screening outside of clinical settings.

Antisaccade and memory-guided saccade in individuals at ultra-high-risk for bipolar disorder

BACKGROUND

Ultra-high-risk for bipolar disorder (UHR-BD) is an important paradigm to investigate the potential early-stage biomarkers of bipolar disorder, including eye-tracking abnormalities and cognitive functions. Antisaccade (AS) described as looking in the opposite direction of the target, and memory-guided saccade (MGS), identified as maintaining fixation, and remembering the location of the target, were used in this study. The aim of this study was to evaluate the differences in saccadic eye movements between UHR-BD and healthy controls (HCs) via AS-MGS.

METHODS

The study included 28 UHR-BD and 29 HCs. Participants were selected using a structured clinical interview for prodromal symptoms of BD. AS-MGS were measured with parameters like uncorrected errors, anticipatory saccades, and latency. Eye movements were recorded with the EyeLink 1000-Plus eye-tracker.

RESULTS

In the AS, the number of correct saccades was significantly decreased in UHR-BD (p = 0.020). Anticipatory (p = 0.009) and express saccades (p = 0.040) were increased in UHR-BD. In the MGS paradigm, the correct saccades were reduced in UHR-BD (p = 0.031). In addition, anticipatory (p = 0.004) and express saccades (p = 0.012) were significantly increased in cue-screen in UHR-BD.

CONCLUSIONS

To our knowledge, this is the first study to evaluate cognitive functions with eye movements in individuals at UHR-BD. The current findings showed that eye movement functions, particularly in saccadic parameters related to inhibition and spatial perception, may be affected in the UHR-BD group. Therefore, assessment of oculomotor functions may provide observation of clinical and cognitive functions in the early-stage of bipolar disorder. However, further research is needed because the potential effects of medication may affect saccadic results.

Automatic Video-Oculography System for Detection of Minimal Hepatic Encephalopathy Using Machine Learning Tools

This article presents an automatic gaze-tracker system to assist in the detection of minimal hepatic encephalopathy by analyzing eye movements with machine learning tools. To record eye movements, we used video-oculography technology and developed automatic feature-extraction software as well as a machine learning algorithm to assist clinicians in the diagnosis. In order to validate the procedure, we selected a sample (n=47) of cirrhotic patients. Approximately half of them were diagnosed with minimal hepatic encephalopathy (MHE), a common neurological impairment in patients with liver disease. By using the actual gold standard, the Psychometric Hepatic Encephalopathy Score battery, PHES, patients were classified into two groups: cirrhotic patients with MHE and those without MHE. Eye movement tests were carried out on all participants. Using classical statistical concepts, we analyzed the significance of 150 eye movement features, and the most relevant (p-values ≤ 0.05) were selected for training machine learning algorithms. To summarize, while the PHES battery is a time-consuming exploration (between 25-40 min per patient), requiring expert training and not amenable to longitudinal analysis, the automatic video oculography is a simple test that takes between 7 and 10 min per patient and has a sensitivity and a specificity of 93%.

Oculomotor analysis to assess brain health: preliminary findings from a longitudinal study of multiple sclerosis using novel tablet-based eye-tracking software

A growing body of evidence supports the link between eye movement anomalies and brain health. Indeed, the oculomotor system is composed of a diverse network of cortical and subcortical structures and circuits that are susceptible to a variety of degenerative processes. Here we show preliminary findings from the baseline measurements of an ongoing longitudinal cohort study in MS participants, designed to determine if disease and cognitive status can be estimated and tracked with high accuracy based on eye movement parameters alone. Using a novel gaze-tracking technology that can reliably and accurately track eye movements with good precision without the need for infrared cameras, using only an iPad Pro embedded camera, we show in this cross-sectional study that several eye movement parameters significantly correlated with clinical outcome measures of interest. Eye movement parameters were extracted from fixation, pro-saccade, anti-saccade, and smooth pursuit visual tasks, whereas the clinical outcome measures were the scores of several disease assessment tools and standard cognitive tests such as the Expanded Disability Status Scale (EDSS), Brief International Cognitive Assessment for MS (BICAMS), the Multiple Sclerosis Functional Composite (MSFC) and the Symbol Digit Modalities Test (SDMT). Furthermore, partial least squares regression analyses show that a small set of oculomotor parameters can explain up to 84% of the variance of the clinical outcome measures. Taken together, these findings not only replicate previously known associations between eye movement parameters and clinical scores, this time using a novel mobile-based technology, but also the notion that interrogating the oculomotor system with a novel eye-tracking technology can inform us of disease severity, as well as the cognitive status of MS participants.

ETMT: A Tool for Eye-Tracking-Based Trail-Making Test to Detect Cognitive Impairment

The growing number of people with cognitive impairment will significantly increase healthcare demand. Screening tools are crucial for detecting cognitive impairment due to a shortage of mental health experts aiming to improve the quality of life for those living with this condition. Eye tracking is a powerful tool that can provide deeper insights into human behavior and inner cognitive processes. The proposed Eye-Tracking-Based Trail-Making Test, ETMT, is a screening tool for monitoring a person's cognitive function. The proposed system utilizes a fuzzy-inference system as an integral part of its framework to calculate comprehensive scores assessing visual search speed and focused attention. By employing an adaptive neuro-fuzzy-inference system, the tool provides an overall cognitive-impairment score, allowing psychologists to assess and quantify the extent of cognitive decline or impairment in their patients. The ETMT model offers a comprehensive understanding of cognitive abilities and identifies potential deficits in various domains. The results indicate that the ETMT model is a potential tool for evaluating cognitive impairment and can capture significant changes in eye movement behavior associated with cognitive impairment. It provides a convenient and affordable diagnosis, prioritizing healthcare resources for severe conditions while enhancing feedback to practitioners.

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.

Eye-tracking paradigms for the assessment of mild cognitive impairment: a systematic review

Mild cognitive impairment (MCI), representing the 'transitional zone' between normal cognition and dementia, has become a novel topic in clinical research. Although early detection is crucial, it remains logistically challenging at the same time. While traditional pen-and-paper tests require in-depth training to ensure standardized administration and accurate interpretation of findings, significant technological advancements are leading to the development of procedures for the early detection of Alzheimer's disease (AD) and facilitating the diagnostic process. Some of the diagnostic protocols, however, show significant limitations that hamper their widespread adoption. Concerns about the social and economic implications of the increasing incidence of AD underline the need for reliable, non-invasive, cost-effective, and timely cognitive scoring methodologies. For instance, modern clinical studies report significant oculomotor impairments among patients with MCI, who perform poorly in visual paired-comparison tasks by ascribing less attentional resources to novel stimuli. To accelerate the Global Action Plan on the Public Health Response to Dementia 2017-2025, this work provides an overview of research on saccadic and exploratory eye-movement deficits among older adults with MCI. The review protocol was drafted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Electronic databases were systematically searched to identify peer-reviewed articles published between 2017 and 2022 that examined visual processing in older adults with MCI and reported gaze parameters as potential biomarkers. Moreover, following the contemporary trend for remote healthcare technologies, we reviewed studies that implemented non-commercial eye-tracking instrumentation in order to detect information processing impairments among the MCI population. Based on the gathered literature, eye-tracking-based paradigms may ameliorate the screening limitations of traditional cognitive assessments and contribute to early AD detection. However, in order to translate the findings pertaining to abnormal gaze behavior into clinical applications, it is imperative to conduct longitudinal investigations in both laboratory-based and ecologically valid settings.

Alzheimer's early detection in post-acute COVID-19 syndrome: a systematic review and expert consensus on preclinical assessments

Introduction

The risk of developing Alzheimer's disease (AD) in older adults increasingly is being discussed in the literature on Post-Acute COVID-19 Syndrome (PACS). Remote digital Assessments for Preclinical AD (RAPAs) are becoming more important in screening for early AD, and should always be available for PACS patients, especially for patients at risk of AD. This systematic review examines the potential for using RAPA to identify impairments in PACS patients, scrutinizes the supporting evidence, and describes the recommendations of experts regarding their use.

Methods

We conducted a thorough search using the PubMed and Embase databases. Systematic reviews (with or without meta-analysis), narrative reviews, and observational studies that assessed patients with PACS on specific RAPAs were included. The RAPAs that were identified looked for impairments in olfactory, eye-tracking, graphical, speech and language, central auditory, or spatial navigation abilities. The recommendations' final grades were determined by evaluating the strength of the evidence and by having a consensus discussion about the results of the Delphi rounds among an international Delphi consensus panel called IMPACT, sponsored by the French National Research Agency. The consensus panel included 11 international experts from France, Switzerland, and Canada.

Results

Based on the available evidence, olfaction is the most long-lasting impairment found in PACS patients. However, while olfaction is the most prevalent impairment, expert consensus statements recommend that AD olfactory screening should not be used on patients with a history of PACS at this point in time. Experts recommend that olfactory screenings can only be recommended once those under study have reported full recovery. This is particularly important for the deployment of the olfactory identification subdimension. The expert assessment that more long-term studies are needed after a period of full recovery, suggests that this consensus statement requires an update in a few years.

Conclusion

Based on available evidence, olfaction could be long-lasting in PACS patients. However, according to expert consensus statements, AD olfactory screening is not recommended for patients with a history of PACS until complete recovery has been confirmed in the literature, particularly for the identification sub-dimension. This consensus statement may require an update in a few years.

Reliability of a Smooth Pursuit Eye-Tracking System (EyeGuide Focus) in Healthy Adolescents and Adults

Mild traumatic brain injury (mTBI) is the most common brain injury, seen in sports, fall, vehicle, or workplace injuries. Concussion is the most common type of mTBI. Assessment of impairments from concussion is evolving, with oculomotor testing suggested as a key component in a multimodality diagnostic protocol. The aim of this study was to evaluate the reliability of one eye-tracking system, the EyeGuide Focus. A group of 75 healthy adolescent and adult participants (adolescents: n = 28; female = 11, male = 17, mean age 16.5 ± 1.4 years; adults n = 47; female = 22; male = 25, mean age 26.7 ± 7.0 years) completed three repetitions of the EyeGuide Focus within one session. Intraclass correlation coefficient (ICC) analysis showed the EyeGuide Focus had overall good reliability (ICC 0.79, 95%CI: 0.70, 0.86). However, a familiarization effect showing improvements in subsequent trials 2 (9.7%) and 3 (8.1%) was noticeable in both cohorts (p < 0.001) with adolescent participants showing greater familiarization effects than adults (21.7% vs. 13.1%). No differences were observed between sexes (p = 0.69). Overall, this is the first study to address the concern regarding a lack of published reliability studies for the EyeGuide Focus. Results showed good reliability, suggesting that oculomotor pursuits should be part of a multimodality assessment protocol, but the observation of familiarization effects suggests that smooth-pursuit testing using this device has the potential to provide a biologically-based interpretation of the maturation of the oculomotor system, as well as its relationship to multiple brain regions in both health and injury.

A novel tablet-based software for the acquisition and analysis of gaze and eye movement parameters: a preliminary validation study in Parkinson's disease

The idea that eye movements can reflect certain aspects of brain function and inform on the presence of neurodegeneration is not a new one. Indeed, a growing body of research has shown that several neurodegenerative disorders, such as Alzheimer's and Parkinson's Disease, present characteristic eye movement anomalies and that specific gaze and eye movement parameters correlate with disease severity. The use of detailed eye movement recordings in research and clinical settings, however, has been limited due to the expensive nature and limited scalability of the required equipment. Here we test a novel technology that can track and measure eye movement parameters using the embedded camera of a mobile tablet. We show that using this technology can replicate several well-known findings regarding oculomotor anomalies in Parkinson's disease (PD), and furthermore show that several parameters significantly correlate with disease severity as assessed with the MDS-UPDRS motor subscale. A logistic regression classifier was able to accurately distinguish PD patients from healthy controls on the basis of six eye movement parameters with a sensitivity of 0.93 and specificity of 0.86. This tablet-based tool has the potential to accelerate eye movement research via affordable and scalable eye-tracking and aid with the identification of disease status and monitoring of disease progression in clinical settings.

Eye Movement Latency Coefficient of Variation as a Predictor of Cognitive Impairment: An Eye Tracking Study of Cognitive Impairment

Studies demonstrated impairment in the control of saccadic eye movements in Alzheimer's disease (AD) and people with mild cognitive impairment (MCI) when conducting the pro-saccade and antisaccade tasks. Research showed that changes in the pro and antisaccade latencies may be particularly sensitive to dementia and general executive functioning. These tasks show potential for diagnostic use, as they provide a rich set of potential eye tracking markers. One such marker, the coefficient of variation (CV), is so far overlooked. For biological markers to be reliable, they must be able to detect abnormalities in preclinical stages. MCI is often viewed as a predecessor to AD, with certain classifications of MCI more likely than others to progress to AD. The current study examined the potential of CV scores on pro and antisaccade tasks to distinguish participants with AD, amnestic MCI (aMCI), non-amnesiac MCI (naMCI), and older controls. The analyses revealed no significant differences in CV scores across the groups using the pro or antisaccade task. Antisaccade mean latencies were able to distinguish participants with AD and the MCI subgroups. Future research is needed on CV measures and attentional fluctuations in AD and MCI individuals to fully assess this measure's potential to robustly distinguish clinical groups with high sensitivity and specificity.

Development of a Machine Learning Model to Discriminate Mild Cognitive Impairment Subjects from Normal Controls in Community Screening

Background: Mild cognitive impairment (MCI) is a transitional stage between normal aging and probable Alzheimer's disease. It is of great value to screen for MCI in the community. A novel machine learning (ML) model is composed of electroencephalography (EEG), eye tracking (ET), and neuropsychological assessments. This study has been proposed to identify MCI subjects from normal controls (NC). Methods: Two cohorts were used in this study. Cohort 1 as the training and validation group, includes184 MCI patients and 152 NC subjects. Cohort 2 as an independent test group, includes 44 MCI and 48 NC individuals. EEG, ET, Neuropsychological Tests Battery (NTB), and clinical variables with age, gender, educational level, MoCA-B, and ACE-R were selected for all subjects. Receiver operating characteristic (ROC) curves were adopted to evaluate the capabilities of this tool to classify MCI from NC. The clinical model, the EEG and ET model, and the neuropsychological model were compared. Results: We found that the classification accuracy of the proposed model achieved 84.5 ± 4.43% and 88.8 ± 3.59% in Cohort 1 and Cohort 2, respectively. The area under curve (AUC) of the proposed tool achieved 0.941 (0.893-0.982) in Cohort 1 and 0.966 (0.921-0.988) in Cohort 2, respectively. Conclusions: The proposed model incorporation of EEG, ET, and neuropsychological assessments yielded excellent classification performances, suggesting its potential for future application in cognitive decline prediction.

Is There a Connection between the Metabolism of Copper, Sulfur, and Molybdenum in Alzheimer’s Disease? New Insights on Disease Etiology

Alzheimer’s disease (AD) and other forms of dementia was ranked 3rd in both the Americas and Europe in 2019 in a World Health Organization (WHO) publication listing the leading causes of death and disability worldwide. Copper (Cu) imbalance has been reported in AD and increasing evidence suggests metal imbalance, including molybdenum (Mo), as a potential link with AD occurrence.We conducted an extensive literature review of the last 60 years of research on AD and its relationship with Cu, sulfur (S), and Mo at out of range levels.Weanalyzed the interactions among metallic elements’ metabolisms;Cu and Mo are biological antagonists, Mo is a sulfite oxidase and xanthine oxidase co-factor, and their low activities impair S metabolism and reduce uric acid, respectively. We found significant evidence in the literature of a new potential mechanism linking Cu imbalance to Mo and S abnormalities in AD etiology: under certain circumstances, the accumulation of Cu not bound to ceruloplasmin might affect the transport of Mo outside the blood vessels, causing a mild Mo deficiency that might lowerthe activity of Mo and S enzymes essential for neuronal activity. The current review provides an updated discussion of the plausible mechanisms combining Cu, S, and Mo alterations in AD.

Unity Human Eye Model for Gaze Tracking with a Query-Driven Dynamic Vision Sensor

Objective measurement of gaze pattern and eye movement during untethered activity has important applications for neuroscience research and neurological disease detection. Current commercial eye-tracking tools rely on desk-top devices with infrared emitters and conventional frame-based cameras. Although wearable options do exist, the large power-consumption from their conventional cameras limit true long-term mobile usage. The query-driven Dynamic Vision Sensor (qDVS) is a neuromorphic camera which dramatically reduces power consumption by outputting only intensity-change threshold events, as opposed to full frames of intensity data. However, such hardware has not yet been implemented for on-body eye-tracking, but the feasibility can be demonstrated using a mathematical simulator to evaluate the eye-tracking ca-pabilities of the qDVS under controlled conditions. Specifically, a framework utilizing a realistic human eye model in the 3D graphics engine, Unity, is presented to enable the controlled and direct comparison of image-based gaze tracking methods. Eye-tracking based on qDVS frames was compared against two different conventional frame eye-tracking methods - the traditional ellipse pupil-fitting algorithm and a deep learning neural network inference model. Gaze accuracy from qDVS frames achieved an average of 93.2% for movement along the primary horizontal axis (pitch angle) and 93.1 % for movement along the primary vertical axis (yaw angle) under 4 different illumination conditions, demonstrating the feasibility for using qDVS hardware cameras for such applications. The quantitative framework for the direct comparison of eye tracking algorithms presented here is made open-source and can be extended to include other eye parameters, such as pupil dilation, reflection, motion artifact, and more.

Validation of a Saliency Map for Assessing Image Quality in Nuclear Medicine: Experimental Study Outcomes

Recently, the use of saliency maps to evaluate the image quality of nuclear medicine images has been reported. However, that study only compared qualitative visual evaluations and did not perform a quantitative assessment. The study’s aim was to demonstrate the possibility of using saliency maps (calculated from intensity and flicker) to assess nuclear medicine image quality by comparison with the evaluator’s gaze data obtained from an eye-tracking device. We created 972 positron emission tomography images by changing the position of the hot sphere, imaging time, and number of iterations in the iterative reconstructions. Pearson’s correlation coefficient between the saliency map calculated from each image and the evaluator’s gaze data during image presentation was calculated. A strong correlation (r ≥ 0.94) was observed between the saliency map (intensity) and the evaluator’s gaze data. This trend was also observed in images obtained from a clinical device. For short acquisition times, the gaze to the hot sphere position was higher for images with fewer iterations during the iterative reconstruction. However, no differences in iterations were found when the acquisition time increased. Saliency by flicker could be applied to clinical images without preprocessing, although compared with the gaze image, it increased slowly.