title: A model of plaid motion perception based on recursive Bayesian integration of the 1-D and 2-D motions of plaid features.
abstract: We describe a theoretical and computational model of the perception of plaid pattern motion which fully accounts for the majority of cases in which misperception of the direction of motion of Type II plaids has been observed [Yo, C., & Wilson, H. (1992). Perceived direction of moving two-dimensional patterns depends on duration, contrast, and eccentricity. Vision Research 32, 135-147]. The model consists of two stages: in the first stage local motion detectors signal both the one-dimensional (1-D) and two-dimensional (2-D) motion of the high luminance features (blobs) in the plaid pattern; in the second stage these local motion signals are combined using a recursive Bayesian least squares estimation process. We demonstrate both theoretically and using simulations of the computational model that the estimated direction of the plaid motion for Type II plaids is initially dominated by the 1-D motion of the longer edges of the elongated blobs, which is in a direction close to the vector sum direction of the component gratings. The recursive estimation process which combines the local motion signals in the second stage of the model results in a dynamic shift in the estimated plaid direction towards the direction of the 2-D motion of the blobs, which corresponds to the veridical plaid direction.
authors.affiliation: Centre for Theoretical and Computational Neuroscience, University of Plymouth, Plymouth PL4 8AA, UK.
authors.forename: Kameliya D
authors.initials: KD
authors.lastname: Dimova
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Denham
mesh_terms: D001499:Bayes Theorem; D003198:Computer Simulation; D008962:Models, Theoretical; D009039:Motion Perception / Q000502:physiology*; D010364:Pattern Recognition, Visual / Q000502:physiology*