R. M. Haefner

This paper introduces a hierarchical Bayesian model to explain motion perception by inferring reference frames from retinal velocities, supported by experiments and Gestalt principles.

The paper identifies sources of suboptimality in perceptual decision making using a causal inference task and shows increased computational precision with stimulus duration.

This study investigates how auditory and visual information are combined in a spatial discrimination task, finding that visual stimuli improve performance even when they provide no task-relevant information.

The paper shows that improved auditory spatial discrimination from aligned visual stimuli cannot be explained by an ideal observer model using causal inference.