Research on the Correlation between Eye Movement Characteristics and Cognitive Impairment in Patients with Cerebral Small Vessel Disease
Download PDF

Keywords

Cerebral small vessel disease
Cognitive impairment
Eye-tracking
Antisaccade
Biomarker

DOI

10.26689/cr.v4i2.15395

Submitted : 2026-06-10
Accepted : 2026-06-25
Published : 2026-07-10

Abstract

Objective: To explore the eye movement characteristics of patients with cerebral small vessel disease (CSVD) and their correlation with cognitive impairment, and to validate the application value of eye-tracking technology in the early screening of CSVD-related cognitive impairment. Methods: A total of 81 subjects were included, with 51 in the CSVD group and 30 in the healthy control group. Cognitive assessment was conducted using the MoCA scale, and visual pairing and antisaccade tasks were detected using an AI-assisted eye-tracking system. Differences in eye movement parameters between the two groups were compared, and the correlation between eye movement indicators and cognitive scores was analyzed. Results: The saccade error rate in the CSVD group was significantly higher than that in the control group (P = 0.009). The total MoCA score, visuospatial and executive function, attention, and language function scores were significantly lower in the CSVD group than in the control group (all P < 0.05). The saccade error rate was significantly negatively correlated with the total MoCA score (rs = -0.382, P = 0.0005) and visuospatial and executive function score (rs = -0.313, P = 0.005). Conclusion: Patients with CSVD exhibit characteristic eye movement abnormalities, and the saccade error rate can serve as an objective biomarker reflecting their executive function and overall cognitive impairment. Eye-tracking technology provides a non-invasive, objective, and efficient new means for the early screening of CSVD-related cognitive impairment.

References

Zanon ZMC, Sveikata L, Viswanathan A, et al., 2021, Cerebral Small Vessel Disease and Vascular Cognitive Impairment: From Diagnosis to Management. Current Opinion in Neurology, 34(2): 246–257.

Miao S, Ji P, Zhu Y, et al., 2025, The Construction and Application of a Clinical Decision Support System for Cardiovascular Diseases: Multimodal Data-Driven Development and Validation Study. JMIR Medical Informatics, 13: e63186.

Ling Y, Sun P, Wang C, et al., 2026, A Novel Eye-Tracking Digital Marker Outperforms Plasma Biomarkers in Detecting Cognitive Impairment. Alzheimer’s & Dementia, 22(3): e71253.

Markus HS, de Leeuw FE, 2023, Cerebral Small Vessel Disease: Recent Advances and Future Directions. International Journal of Stroke, 18(1): 4–14.

Wang LS, Song JQ, Lv Y, 2023, Preliminary Establishment of a Logistics Regression Model for Diagnosing Alzheimer’s Disease Based on Eye-Tracking Technology. Journal of Army Medical University, 45(2): 102–110.

Ye J, Zhou L, Li Q, et al., 2026, Dysfunction of Hippocampal Cells and Its Role in Cognitive Impairment. Neural Regeneration Research, 21(8): 3479–3495.

Opwonya J, et al., 2022, Saccadic Eye Movement in Mild Cognitive Impairment and Alzheimer’s Disease: A Systematic Review and Meta-Analysis. Neuropsychology Review, 32(2): 193–227.

Ma J, Liu F, Yang B, et al., 2021, Selective Aberrant Functional–Structural Coupling of Multiscale Brain Networks in Subcortical Vascular Mild Cognitive Impairment. Neuroscience Bulletin, 37(3): 287–297.

Wang M, Yin X, Yin CY, et al., 2025, The Role of Saccade Characteristics in Early Diagnosis and Symptom Assessment of Parkinson’s Disease. Chinese Journal of Geriatric Heart Brain Vessel Diseases, 27(12): 1611–1616.

Godwin HJ, Hout MC, Barnhart AS, 2025, Pay Attention to Eye Movement Behavior. Behavioral and Brain Sciences, 48: e141.