ArticleBiological cybernetics2025
Bayesian Dynamical Modeling of Fixational Eye Movements.
Article in Biological cybernetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Force production with a subset of fingers: two aspects of unintentional finger involvement.Experimental brain research · 2026Article
- Stability of movement by a multi-element system: drifts and random walk within and orthogonal to the uncontrolled manifold during multi-finger force production.Experimental brain research · 2026Review
- Fixational eye movements and edge integration in lightness perception.Vision research · 2025Article
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3 authors.
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Abstract
Humans constantly move their eyes, even during visual fixations, where miniature (or fixational) eye movements occur involuntarily. Fixational eye movements comprise slow components (physiological drift and tremor) and fast components (microsaccades). The complex dynamics of physiological drift can be modeled qualitatively as a statistically self-avoiding random walk (SAW model, Engbert et al., 2011). In this study, we implement a data assimilation approach for the SAW model to explain statistics of fixational eye movements and microsaccades in experimental data obtained from high-resolution eye-tracking. We discuss and analyze the likelihood function for the SAW model, which allows us to apply Bayesian parameter estimation at the level of individual human observers. Based on model fitting, we find a relationship between the activation predicted by the SAW model and the occurrence of microsaccades. The model's latent activation relative to microsaccade onsets and offsets using experimental data lends support to the existence of a triggering mechanism for microsaccades. Our findings suggest that the SAW model can capture individual differences and serve as a tool for exploring the relationship between physiological drift and microsaccades as the two most essential components of fixational eye movements. Our results contribute to understanding individual variability in microsaccade behaviors and the role of fixational eye movements in visual information processing.
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