Sathishkumar Sundaramoorthy, M. Sc. in Neuroscience
PhD Student, Nantes University, Nantes, France
Early diagnosis of age-related neurodegenerative and psychiatric conditions such as Alzheimer’s disease (AD), Parkinson’s disease (PD), depression, and apathy remains a major challenge in clinical neuroscience. Conventional diagnostic approaches rely largely on subjective tools, including caregiver-reported scales and patient questionnaires such as the Geriatric Depression Scale and the Neuropsychiatric Inventory. While informative, these tools often lack sensitivity in early or prodromal stages and may be impractical for routine screening due to cost, specialised equipment requirements, or patient compliance issues. (1)
Current Diagnostic Approaches and Their Limitations
| Method | What It Helps Detect | What It Tells Us Early | Main Drawbacks |
|---|---|---|---|
| Questionnaires / Self-report | Early memory or mood changes | Simple screening; may indicate behavioural or emotional changes | Relies on self-report; limited biological sensitivity |
| Structural Brain MRI | Early Alzheimer’s-related changes | Identifies brain atrophy in memory-related regions | Often detects changes after damage; costly |
| Advanced MRI Techniques | Early Parkinson’s-related changes | Reveals subtle brain alterations before symptom onset | Requires specialised equipment; limited availability |
| Visual MRI Rating by Clinicians | Overt signs of dementia | Rapid visual assessment of key brain regions | Effective mainly after symptom onset; operator dependent |
Table 1: Comparison of Diagnostic Methods in Early and Prodromal Stages
Eye Movement Changes in Alzheimer’s and Parkinson’s Disease
Alzheimer’s disease, the most common form of dementia, presents with memory loss, visuospatial deficits, and executive dysfunction. Eye tracking metrics from these patients identified distinct oculomotor abnormalities in AD and its precursor, Mild Cognitive Impairment (MCI). For instance, patients with AD showed prolonged saccade latencies, reduced fixation durations, and increased errors in anti-saccade tasks (where individuals must look away from a target), showing deficits in inhibitory control and attention. (5) Parkinson’s disease, commonly determined as a motor disorder, is increasingly recognised for its cognitive and oculomotor impairments. Eye tracking metrics have shown hypometric saccades (smaller than normal eye movements), prolonged fixation durations, and impaired smooth pursuit in PD patients, particularly those with cognitive impairment. (6) Individuals with depression showing longer fixation times on negative stimuli and fewer fixations on positive stimuli during visual tasks, reflecting a bias toward negative emotional content. (7)
Traditional eye tracking tasks, such as antisaccade or reading exercises, have shown efficacy but are often limited to controlled settings. Recent advancements in serious game-based and Virtual Reality (VR) assessments have expanded the applicability of eye tracking to more naturalistic and engaging tasks, improving patient compliance and ecological validity. (8)
Figure 1: VR-Based Eye Tracking Device Demonstrating Modern Tools for Cognitive Assessment and Gaze Analysis
Conclusion
Eye tracking, particularly when combined with immersive and ecologically valid paradigms, shows strong potential as an adjunctive tool for early and differential diagnosis in clinical neuroscience. Advances in wearable eye-tracking technologies further support longitudinal monitoring in real-world environments, extending their utility beyond early detection to tracking disease progression and therapeutic outcomes. (7)
References
- Liu, Z., Yang, Z., Gu, Y., Liu, H., & Wang, P. (2021). Effectiveness of eye tracking in the diagnosis of cognitive disorders. PLOS One, 16(7), e0254059.
- Munro, C. E., et al. (2024). Depressive symptoms and amyloid accumulation. JAMA Network Open, 7(8), e2427248.
- Chouliaras, L., & O’Brien, J. T. (2023). Neuroimaging in early dementia diagnosis. Molecular Psychiatry, 28(10), 4084–4097.
- Zarkali, A., et al. (2024). Neuroimaging and biomarkers in Parkinson’s disease. Nature Communications, 15(1), 5661.
- Tokushige, S. I., et al. (2023). Eye tracking for early detection of Alzheimer’s disease. Frontiers in Aging Neuroscience, 15, 1123456.
- Archibald, N. K., et al. (2013). Visual exploration in Parkinson’s disease. Brain, 136(3), 739–750.
- Xu, Y., et al. (2024). Dementia screening using eye tracking and VR. NPJ Digital Medicine, 7(1), 219.
- Krebs, C., et al. (2021). Eye tracking in puzzle games as cognitive markers. JMIR Serious Games, 9(1), e24151.
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