ArticleLearning & memory (Cold Spring Harbor, N.Y.)2019
VisMET: a passive, efficient, and sensitive assessment of visuospatial memory in healthy aging, mild cognitive impairment, and Alzheimer's disease.
Article in Learning & memory (Cold Spring Harbor, N.Y.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The effectiveness of eye tracking in the diagnosis of cognitive disorders: A systematic review and meta-analysis.PloS one · 2021Pooled it
- Theta Oscillations, Oculomotor Processing, and Neural Synchronization: A Review.Brain sciences · 2026Review
- Tracking the eyes to track decline: Global eye movement similarity as a novel neuropsychological marker of mild cognitive impairment.GeroScience · 2026Article
- Anticipatory eye gaze as a marker of memory.Communications psychology · 2025Article
- A portable and efficient dementia screening tool using eye tracking machine learning and virtual reality.NPJ digital medicine · 2024Article
- Development of an eye-tracking system based on a deep learning model to assess executive function in patients with mental illnesses.Scientific reports · 2024Article
- Eye-tracking paradigms for the assessment of mild cognitive impairment: a systematic review.Frontiers in psychology · 2023Review
- An investigation of privacy preservation in deep learning-based eye-tracking.Biomedical engineering online · 2022Article
- A novel deep learning approach for diagnosing Alzheimer's disease based on eye-tracking data.Frontiers in human neuroscience · 2022Article
- Article
- Exploratory Research on Key Technology of Human-Computer Interactive 2.5-Minute Fast Digital Early Warning for Mild Cognitive Impairment.Computational intelligence and neuroscience · 2022Article
- The challenge of neuropsychological assessment of visual/visuo-spatial memory: A critical, historical review, and lessons for the present and future.Frontiers in psychology · 2022Review
- The Potential of Naturalistic Eye Movement Tasks in the Diagnosis of Alzheimer's Disease: A Review.Brain sciences · 2021Review
- Deep Convolutional Neural Networks and Transfer Learning for Measuring Cognitive Impairment Using Eye-Tracking in a Distributed Tablet-Based Environment.IEEE transactions on bio-medical engineering · 2021Article
- Feedforward prediction error signals during episodic memory retrieval.Nature communications · 2020Article
- Triggering Postural Movements With Virtual Reality Technology in Healthy Young and Older Adults: A Cross-Sectional Validation Study for Early Dementia Screening.Frontiers in medicine · 2020Article
- Early Diagnosis of Mild Cognitive Impairment Based on Eye Movement Parameters in an Aging Chinese Population.Frontiers in aging neuroscience · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The entorhinal-hippocampal circuit is one of the earliest sites of cortical pathology in Alzheimer's disease (AD). Visuospatial memory paradigms that are mediated by the entorhinal-hippocampal circuit may offer a means to detect memory impairment during the early stages of AD. In this study, we developed a 4-min visuospatial memory paradigm called VisMET (Visuospatial Memory Eye-Tracking Task) that passively assesses memory using eye movements rather than explicit memory judgements. We had 296 control or memory-impaired participants view a set of images followed by a modified version of the images with either an object removed, or a new object added. Healthy controls spent significantly more time viewing these manipulations compared to subjects with mild cognitive impairment and AD. Using a logistic regression model, the amount of time that individuals viewed these manipulations could predict cognitive impairment and disease status with an out of sample area under the receiver-operator characteristic curve of 0.85. Based on these results, VisMET offers a passive, sensitive, and efficient memory paradigm capable of detecting objective memory impairment and predicting cognitive and disease status.
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Registered trials
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