ReviewBrain sciences2021
The Potential of Naturalistic Eye Movement Tasks in the Diagnosis of Alzheimer's Disease: A Review.
Review in Brain sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 36 citations in OpenAlex.
- Naturalistic Eye Movement Tasks in Parkinson's Disease: A Systematic Review.Journal of Parkinson's disease · 2024Pooled it
- Oculomotor atypicalities in motor neurone disease: a systematic review.Frontiers in neuroscience · 2024Pooled it
- Article
- Enhancing Early Detection of Alzheimer's Disease: An Ensemble Model for Multi-Domain Cognitive Assessment Using Voice and Video.Sensors (Basel, Switzerland) · 2026Article
- Saccade length consistency during reading and shape-scanning.Attention, perception & psychophysics · 2026Article
- Eye-Tracking Technologies for Cognitive Assessment After Acquired Brain Injury: Systematic Review.JMIR rehabilitation and assistive technologies · 2026Review
- Simultaneous Analysis of Microsaccades and Pupil Size Variations in Age-Related Cognitive Impairment Using Eye-Tracking Technology.Journal of eye movement research · 2026Article
- A novel eye-tracking digital marker outperforms plasma biomarkers in detecting cognitive impairment.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Tablet-Based Assessment of Picture Naming in Prodromal Alzheimer's Disease: An Accessible and Effective Tool for Distinguishing Mild Cognitive Impairment from Normal Aging.Dementia and geriatric cognitive disorders · 2026Article
- Entorhinal grid-like codes for visual space during memory formation.Nature communications · 2025Article
- From Mechanical Instability to Virtual Precision: Digital Twin Validation for Next-Generation MEMS-Based Eye-Tracking Systems.Sensors (Basel, Switzerland) · 2025Article
- Altered GABAergic signaling and chloride homeostasis in eye movement circuits during late neurodevelopment: implications for Alzheimer's disease therapy.Frontiers in pharmacology · 2025Review
- Possibility of screening for mild cognitive impairment via an eye tracking-based cognitive scale.Frontiers in aging · 2025Article
- EM-COGLOAD: An investigation into age and cognitive load detection using eye tracking and deep learning.Computational and structural biotechnology journal · 2024Article
- A detection model of cognitive impairment via the integrated gait and eye movement analysis from a large Chinese community cohort.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Eye Movement Latency Coefficient of Variation as a Predictor of Cognitive Impairment: An Eye Tracking Study of Cognitive Impairment.Vision (Basel, Switzerland) · 2023Article
- Early detection of cognitive decline in Alzheimer's disease using eye tracking.Frontiers in aging neuroscience · 2023Article
- Eye-tracking paradigms for the assessment of mild cognitive impairment: a systematic review.Frontiers in psychology · 2023Review
- Article
- A novel deep learning approach for diagnosing Alzheimer's disease based on eye-tracking data.Frontiers in human neuroscience · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.