Pursuing motion illusions: A realistic oculomotor framework for Bayesian inference
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Research highlights
► Accuracy in estimating an object’s global motion over time is not only affected by the noise in visual motion information but also by the spatial limitation of the local motion analyzers (aperture problem). ► We propose a recursive extension to the Bayesian framework for motion processing cascaded with a model oculomotor plant to describe the dynamic integration of 1D and 2D motion information in the context of smooth pursuit eye movements. ► The model not only provides an accurate qualitative account of dynamic motion integration but also a quantitative account that is close to the smooth pursuit response across several conditions.
Keywords
Smooth pursuit eye movements
Motion perception
Aperture problem
Bayesian model
Temporal dynamics
Tracking error
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