Early Diagnosis of Mild Cognitive Impairment Based on Eye Movement Parameters in an Aging Chinese Population

Impacts of education level on Montreal Cognitive Assessment and saccades in community residents from Western China

OBJECTIVES

This cross-sectional study sought to evaluate the effectiveness of the Montreal Cognitive Assessment (MoCA) and saccade in discerning the cognitive function levels among community populations characterized by diverse educational backgrounds.

METHODS

Data from 665 Western China individuals encompassed MoCA scores and saccade performance. The study examined how education level and age influenced these assessments and highlighted the contrasting abilities of these measures in detecting cognitive abnormalities.

RESULTS

The saccade model revealed a consistent cognitive impairment prevalence (15.5%) compared to previous clinical data (9.7% to 23.3%), while MoCA exhibited variable rates (25.1% to 52.8%). Notably, saccades and MoCA significantly diverged in detecting cognitive dysfunction. Additionally, education level had a greater impact on MoCA (effect size: 0.272) compared to saccades (0.024) affecting all MoCA sub-items, with age exerting a smaller influence on MoCA (0.037) compared to saccades (0.056).

CONCLUSION

Saccades are less susceptible to the influence of education level when compared to MoCA, making saccade a potentially more suitable cognitive screening tool for rural community populations.

SIGNIFICANCE

This study represents a pioneering approach by employing saccade detection within community populations to distinguish cognitive function status.

Contextual novelty detection and novelty-related memory enhancement in amnestic mild cognitive impairment

INTRODUCTION

Though novelty processing plays a critical role in memory function, little is known about how it influences learning in memory-impaired populations, such as amnestic Mild Cognitive Impairment (aMCI).

METHODS

21 aMCI patients and 22 age- and education-matched healthy older participants performed two tasks-(i) an oddball paradigm where fractals that were often repeated (60 % of the stimuli), less frequently repeated (20 %), or novel (presented once each) were shown to assess novelty preference (longer viewing time for novel than familiar stimuli), and (ii) a Von Restorff paradigm assessing novelty-related effects on memory. Participants studied 22 lists of 10 words. Among these lists, 18 contained an isolated word different from the others by its distinctive aspect, here the font size (90-point, 120-point or 150-point against 60-point for non-isolated words). The remaining four were control lists without isolated words. After studying each list, participants freely recalled the maximum words possible.

RESULTS

For the oddball task, a group-by-stimulus type ANOVA on median viewing times revealed a significant effect of stimulus type, but not of group. Both groups spent more time on novel stimuli. For the Von Restorff task, both aMCI and healthy controls recalled the isolated words (presented in 120-point or 150-point, but not 90-point) better than others (excluding primacy and recency effects). Novelty-related memory benefit-gain factor-was computed as the difference between the recall scores for isolated and other words. A group-by-font size ANOVA on gain factors revealed no group effect, nor interaction, suggesting that aMCI patients benefited from novelty, alike controls.

CONCLUSION

Novelty preference and the boosting effect of isolation-related novelty on subsequent recall seem preserved despite impaired episodic memory in aMCI patients. This is discussed in the light of contemporary divergent theories regarding the relationship between novelty and memory, as either being independent or parts of a continuum.

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.

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.

Distinctive visual tasks for characterizing mild cognitive impairment and dementia using oculomotor behavior

Introduction

One's eye movement (in response to visual tasks) provides a unique window into the cognitive processes and higher-order cognitive functions that become adversely affected in cases with cognitive decline, such as those mild cognitive impairment (MCI) and dementia. MCI is a transitional stage between normal aging and dementia.

Methods

In the current work, we have focused on identifying visual tasks (such as horizontal and vertical Pro-saccade, Anti-saccade and Memory Guided Fixation tasks) that can differentiate individuals with MCI and dementia from their cognitively unimpaired healthy aging counterparts based on oculomotor Performance indices. In an attempt to identify the optimal combination of visual tasks that can be used to differentiate the participant groups, clustering was performed using the oculomotor Performance indices.

Results

Results of our study with a group of 60 cognitively unimpaired healthy aging individuals, a group with 60 individuals with MCI and a group with 60 individuals with dementia indicate that the horizontal and vertical Anti-saccade tasks provided the optimal combination that could differentiate individuals with MCI and dementia from their cognitively unimpaired healthy aging counterparts with clustering accuracy of ∼92% based on the saccade latencies. Also, the saccade latencies during both of these Anti-saccade tasks were found to strongly correlate with the Neuropsychological test scores.

Discussion

This suggests that the Anti-saccade tasks can hold promise in clinical practice for professionals working with individuals with MCI and dementia.

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.

Antisaccadic eye movements in middle-aged individuals with a family history of Alzheimer's disease

Background

Antisaccade is closely associated with cognitive ability in Alzheimer's disease (AD). However, studies regarding antisaccade in the early stages of AD are scarce. Considering that first-degree family history is a well-established risk factor for AD, we explored the influence of family history on the performance of antisaccade tasks in individuals with normal cognition.

Methods

In total, 44 participants (aged 50-66 years) with a family history of AD (FH+) and 44 age-, gender-, and educational level-matched controls (FH-) were enrolled in our study. After cognitive assessment using the Montreal Cognitive Assessment and Mini-mental State Examination, participants underwent antisaccade trials, and all parameters were recorded using an eye tracker.

Results

While the average velocity was relatively lower in FH+ individuals than in FH- individuals (107.9 ± 14.3°/s vs. 132.9 ± 23.7°/s, p < 0.001), FH+ individuals surprisingly showed relatively fewer uninhibited reflexive saccades (44.7 ± 26.0% vs. 56.2 ± 24.7%, p = 0.037) than the control group. They also required a relatively shorter time to detect and correct false saccades (121.6 ± 40.7 ms vs. 143.9 ± 37.0 ms, p = 0.023).

Conclusions

This study showed that family history is associated with alterations in antisaccadic parameters, suggesting that eye tracking can be used to assess oculomotor control and executive function in individuals at risk of developing dementia.

A novel deep learning approach for diagnosing Alzheimer's disease based on eye-tracking data

Eye-tracking technology has become a powerful tool for biomedical-related applications due to its simplicity of operation and low requirements on patient language skills. This study aims to use the machine-learning models and deep-learning networks to identify key features of eye movements in Alzheimer's Disease (AD) under specific visual tasks, thereby facilitating computer-aided diagnosis of AD. Firstly, a three-dimensional (3D) visuospatial memory task is designed to provide participants with visual stimuli while their eye-movement data are recorded and used to build an eye-tracking dataset. Then, we propose a novel deep-learning-based model for identifying patients with Alzheimer's Disease (PwAD) and healthy controls (HCs) based on the collected eye-movement data. The proposed model utilizes a nested autoencoder network to extract the eye-movement features from the generated fixation heatmaps and a weight adaptive network layer for the feature fusion, which can preserve as much useful information as possible for the final binary classification. To fully verify the performance of the proposed model, we also design two types of models based on traditional machine-learning and typical deep-learning for comparison. Furthermore, we have also done ablation experiments to verify the effectiveness of each module of the proposed network. Finally, these models are evaluated by four-fold cross-validation on the built eye-tracking dataset. The proposed model shows 85% average accuracy in AD recognition, outperforming machine-learning methods and other typical deep-learning networks.

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.

The Use of Digital Technology to Assess Cognitive Function in Tunisian Adults

Background: There has been increasing evidence and support for the use of digital technology in the cognitive health field. Despite the growing use of innovative digital technology to assess cognitive function, such technology remains scarce in Arabic countries, particularly in Tunisia. Objective: To investigate the effectiveness of a digitally delivered cognitive assessment battery in differentiating varying degrees of cognitive function in older Tunisian adults. Methods: One hundred fifty-five Tunisian older adults (age: 62.24±7.52 years) were assigned to one of four groups: healthy controls (HC), at-risk (AR), mild cognitive impairment (MCI), and Alzheimer’s disease (AD). Participants completed a translated version of the Neurotrack digital cognitive battery. Results: The AD group performed significantly lower on the associative learning (p = 0.01) and associative memory assessments (p = 0.002), than the HC and AR groups. The AD group also performed worse on the inhibition measure (p = 0.008) than the HC, AR, and MCI groups. For recognition memory, the was a significant difference between all four groups (p <  0.0005), with AD having the lowest scores followed by the MCI, AR, and HC groups, respectively. There were no significant differences observed on attention, executive function and processing speed performance between the four groups (p >  0.05). Conclusion: The use of digital technology appears to be a viable solution to current cognitive assessment challenges for assessing cognitive function in a Tunisian population. These findings provide further support for the use of digital technology in cognitive assessment, particularly in understudied populations.

Aging changes the interactions between the oculomotor and memory systems

The use of multi-modal approaches, particularly in conjunction with multivariate analytic techniques, can enrich models of cognition, brain function, and how they change with age. Recently, multivariate approaches have been applied to the study of eye movements in a manner akin to that of neural activity (i.e., pattern similarity). Here, we review the literature regarding multi-modal and/or multivariate approaches, with specific reference to the use of eyetracking to characterize age-related changes in memory. By applying multi-modal and multivariate approaches to the study of aging, research has shown that aging is characterized by moment-to-moment alterations in the amount and pattern of visual exploration, and by extension, alterations in the activity and function of the hippocampus and broader medial temporal lobe (MTL). These methodological advances suggest that age-related declines in the integrity of the memory system has consequences for oculomotor behavior in the moment, in a reciprocal fashion. Age-related changes in hippocampal and MTL structure and function may lead to an increase in, and change in the patterns of, visual exploration in an effort to upregulate the encoding of information. However, such visual exploration patterns may be non-optimal and actually reduce the amount and/or type of incoming information that is bound into a lasting memory representation. This research indicates that age-related cognitive impairments are considerably broader in scope than previously realized.

Visual Function and Visual Perception among Senior Citizens with Mild Cognitive Impairment in Taiwan

Purpose: With the benefits of advanced medical technology, Taiwan has gradually changed from an aged society to a super-aged society. According to previous studies, the prevalence rate of mild cognitive impairment (MCI) over the age of 60 is 15% to 20%. Therefore, the main purpose of our study was to analyze the correlation of cognitive function with visual function (specifically, binocular vision and visual perception) in Taiwanese volunteers aged 60 years or older. Methods: Thirty-six healthy participants who were not taking psychiatric medications and who had not been diagnosed with any retinal or optic nerve diseases were enrolled. Addenbrooke’s cognitive examination III (ACE-III), binocular visual function, and visual perception evaluation were performed, and the data analyzed statistically by t-test, χ², linear regression, and MANOVA. Results: Cognitive function was closely correlated with visual function and visual perception; the horizontal adjustment time of binocular eye movement, stereopsis, the motor-free visual perception test-4 (MVPT-4), and peripheral awareness actually displayed higher explanatory power in predicting cognitive function. In addition, various interactive parameters between visual function and visual perception were found to affect specific aspects of ACE-III. Discussion: Our study revealed that there was a close correlation of cognitive function with visual function; as such, it may be possible to predict visual function deficits in patients with mild cognitive impairment.

The Potential of Naturalistic Eye Movement Tasks in the Diagnosis of Alzheimer's Disease: A Review

Extensive research has demonstrated that eye-tracking tasks can effectively indicate cognitive impairment. For example, lab-based eye-tracking tasks, such as the antisaccade task, have robustly distinguished between people with Alzheimer’s disease (AD) and healthy older adults. Due to the neurodegeneration associated with AD, people with AD often display extended saccade latencies and increased error rates on eye-tracking tasks. Although the effectiveness of using eye tracking to identify cognitive impairment appears promising, research considering the utility of eye tracking during naturalistic tasks, such as reading, in identifying cognitive impairment is limited. The current review identified 39 articles assessing eye-tracking distinctions between people with AD, mild cognitive impairment (MCI), and healthy controls when completing naturalistic task (reading, real-life simulations, static image search) or a goal-directed task involving naturalistic stimuli. The results revealed that naturalistic tasks show promising biomarkers and distinctions between healthy older adults and AD participants, and therefore show potential to be used for diagnostic and monitoring purposes. However, only twelve articles included MCI participants and assessed the sensitivity of measures to detect cognitive impairment in preclinical stages. In addition, the review revealed inconsistencies within the literature, particularly when assessing reading tasks. We urge researchers to expand on the current literature in this area and strive to assess the robustness and sensitivity of eye-tracking measures in both AD and MCI populations on naturalistic tasks.

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

Background

Eye tracking (ET) is a viable marker for the recognition of cognitive disorders. We assessed the accuracy and clinical value of ET for the diagnosis of cognitive disorders in patients.

Methods

We searched the Medline, Embase, Web of Science, Cochrane Library, and Pubmed databases from inception to March 2, 2021, as well as the reference lists of identified primary studies. We included articles written in English that investigated ET for cognitive disorder patients—Mild cognitive impairment (MCI), Alzheimer’s disease (AD), Amyotrophic lateral sclerosis (ALS), and dementia. Two independent researchers extracted the data and the characteristics of each study; We calculated pooled sensitivities and specificities. A hierarchical summary of receiver performance characteristics (HSROC) model was used to test the diagnostic accuracy of ET for cognitive impairment (CI).

Findings

11 studies met the inclusion criteria and were included in qualitative comprehensive analysis. Meta-analysis was performed on 9 trials using Neuropsychological Cognitive Testing (NCT) as the reference standard. The comprehensive sensitivity and specificity of ET for detecting cognitive disorders were 0.75 (95% CI 0.72–0.79) and 0.73 (95% CI 0.70 to 0.76), respectively. The combined positive likelihood ratio (LR+) was 2.74 (95%CI 2.32–3.24) and the negative likelihood ratio (LR−) was 0.27 (95%CI 0.18–0.42).

Conclusions

This review showed that ET technology could be used to detect the decline in CI, clinical use of ET techniques in combination with other tools to assess CI can be encouraged.