ArticleFrontiers in aging neuroscience2026
Multimodal data-driven eye-movement subtypes and their cerebral glucose metabolic patterns in Parkinson's disease.
Article in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- A Sensorimotor Framework for the Neurorehabilitation of Oculomotor Dysfunction in Parkinson's Disease.Journal of clinical medicine · 2026Review
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8 authors.
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Abstract
Background: Previously reported Parkinson's disease (PD) subtyping schemes often show limited stability and cross-cohort generalizability. Objective: To derive data-driven oculomotor subtypes in PD using multi-task eye-movement assessment and to characterize their cerebral glucose metabolic patterns. Methods: We administered a non-invasive multi-task eye-movement battery to 122 patients with PD and 69 healthy controls. Multidimensional oculomotor features were analyzed using unsupervised k-means clustering to identify PD subtypes. In a PD subset undergoing Results: Clustering identified two PD subtypes: an oculomotor-efficient subtype (PD-E) and an oculomotor-inefficient subtype (PD-I). The subtypes differed across multiple oculomotor parameters, with antisaccade (AS) metrics showing the most prominent divergence. Compared with PD-I, PD-E showed higher FDG uptake in frontotemporal cortices. Metabolic differences were directionally concordant with groupwise patterns in cognitive measures. Conclusion: Integrating eye-movement digital phenotypes with FDG-PET metabolism may provide complementary information for cognitive-domain profiling and assessment in PD. Longitudinal studies and independent cohort validation are needed to confirm stability and clinical translatability.
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