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Eyetracking Metrics in Young Onset Alzheimer's Disease: A Window into Cognitive Visual Functions
Pavisic IM, Firth NC, Parsons S, Rego DM, Shakespeare TJ, Yong KXX, Slattery CF, Paterson RW et al.. Frontiers in neurology, 2017-08-07
Topic: Amyloid, tau and blood-test diagnosis
Young onset Alzheimer's disease (YOAD) is defined as symptom onset before the age of 65 years and is particularly associated with phenotypic heterogeneity. Atypical presentations, such as the clinic-radiological visual syndrome posterior cortical atrophy (PCA), often lead to delays in accurate diagnosis. Eyetracking has been used to demonstrate basic oculomotor impairments in individuals with dementia. In the present study, we aim to explore the relationship between eyetracking metrics and standard tests of visual cognition in individuals with YOAD. Fifty-seven participants were included: 36 individuals with YOAD ( n = 26 typical AD; n = 10 PCA) and 21 age-matched healthy controls. Participants completed three eyetracking experiments: fixation, pro-saccade, and smooth pursuit tasks. Summary metrics were used as outcome measures and their predictive value explored looking at correlations with visuoperceptual and visuospatial metrics. Significant correlations between eyetracking metrics and standard visual cognitive estimates are reported. A machine-learning approach using a classification method based on the smooth pursuit raw eyetracking data discriminates with approximately 95% accuracy patients and controls in cross-validation tests. Results suggest that the eyetracking paradigms of a relatively simple and specific nature provide measures not only reflecting basic oculomotor characteristics but also predicting higher order visuospatial and visuoperceptual impairments. Eyetracking measures can represent extremely useful markers during the diagnostic phase and may be exploited as potential outcome measures for clinical trials.
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APA 7th
Pavisic, I. M., Firth, N. C., Parsons, S., Rego, D. M., Shakespeare, T. J., Yong, K. X. X., et al. (2017). Eyetracking Metrics in Young Onset Alzheimer's Disease: A Window into Cognitive Visual Functions. Frontiers in neurology. https://doi.org/10.3389/fneur.2017.00377
Vancouver
Pavisic IM, Firth NC, Parsons S, Rego DM, Shakespeare TJ, Yong KXX, et al. Eyetracking Metrics in Young Onset Alzheimer's Disease: A Window into Cognitive Visual Functions. Frontiers in neurology. 2017. doi:10.3389/fneur.2017.00377. PMID: 28824534.
BibTeX
@article{pavisic2017-28824534,
author = {Pavisic, I. M. and Firth, N. C. and Parsons, S. and Rego, D. M. and Shakespeare, T. J. and Yong, K. X. X. and Slattery, C. F. and Paterson, R. W. and others},
title = {{Eyetracking Metrics in Young Onset Alzheimer's Disease: A Window into Cognitive Visual Functions}},
journal = {Frontiers in neurology},
year = {2017},
doi = {10.3389/fneur.2017.00377},
pmid = {28824534},
url = {https://doi.org/10.3389/fneur.2017.00377}
}
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Key findings
- Young onset Alzheimer's disease (YOAD) is defined as symptom onset before the age of 65 years and is particularly associated with phenotypic heterogeneity.
- Significant correlations between eyetracking metrics and standard visual cognitive estimates are reported.
- Results suggest that the eyetracking paradigms of a relatively simple and specific nature provide measures not only reflecting basic oculomotor characteristics but also predicting higher order visuospatial and visuoperceptual impairments.
Why it matters
Eyetracking metrics correlated with standard visual cognitive tests in young onset Alzheimer's disease, and a machine learning approach discriminated patients from controls with about 95% accuracy. This is a potential diagnostic tool and does not treat, cure, or prevent Alzheimer's disease.
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Study details
- Participants26
- Evidence strengthLow
How this study scored 48/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Frontiers in neurology) |
| Journal's citation record | 2 / 4 | Frontiers in Neurology: journal h-index 162 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2017 — within 10 year(s) of the newest study here |
| Sample size | 1 / 4 | 26 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 4 / 7 | Cited 96 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 8.7 citations a year over 11 year(s) since 2017 |
| Impact for its field and year | 3 / 6 | Cited 3.8× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 3 other studies in this library |
| Still being cited | 2 / 4 | Cited 41 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 1 / 4 | Last-listed author Silvia Primativo: h-index 14 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | University College London: institution h-index 2,029 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 28824534) |
| Free to read | 2 / 2 | Free to read |
| Total | 48 / 100 | — |
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Read the original
- DOI: 10.3389/fneur.2017.00377
- PubMed: 28824534
- Original source →
- Free full text: Frontiers in Neurology →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
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