title: A neural model of border-ownership from kinetic occlusion.
abstract: Camouflaged animals that have very similar textures to their surroundings are difficult to detect when stationary. However, when an animal moves, humans readily see a figure at a different depth than the background. How do humans perceive a figure breaking camouflage, even though the texture of the figure and its background may be statistically identical in luminance? We present a model that demonstrates how the primate visual system performs figure-ground segregation in extreme cases of breaking camouflage based on motion alone. Border-ownership signals develop as an emergent property in model V2 units whose receptive fields are nearby kinetically defined borders that separate the figure and background. Model simulations support border-ownership as a general mechanism by which the visual system performs figure-ground segregation, despite whether figure-ground boundaries are defined by luminance or motion contrast. The gradient of motion- and luminance-related border-ownership signals explains the perceived depth ordering of the foreground and background surfaces. Our model predicts that V2 neurons, which are sensitive to kinetic edges, are selective to border-ownership (magnocellular B cells). A distinct population of model V2 neurons is selective to border-ownership in figures defined by luminance contrast (parvocellular B cells). B cells in model V2 receive feedback from neurons in V4 and MT with larger receptive fields to bias border-ownership signals toward the figure. We predict that neurons in V4 and MT sensitive to kinetically defined figures play a crucial role in determining whether the foreground surface accretes, deletes, or produces a shearing motion with respect to the background.
authors.affiliation: Department of Cognitive Science, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180, USA; Center for Computational Neuroscience and Neural Technology, Boston University, 677 Beacon Street, Boston, MA 02215, USA.
authors.forename: Oliver W
authors.initials: OW
authors.lastname: Layton
authors.affiliation: Center for Computational Neuroscience and Neural Technology, Boston University, 677 Beacon Street, Boston, MA 02215, USA. Electronic address: yazdan@bu.edu.
authors.forename: Arash
authors.initials: A
authors.lastname: Yazdanbakhsh
mesh_terms: D000818:Animals; D006801:Humans; D007700:Kinetics; D008959:Models, Neurological; D009039:Motion Perception / Q000502:physiology; D010364:Pattern Recognition, Visual / Q000502:physiology*; D011323:Primates / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology*; D014795:Visual Pathways / Q000502:physiology*
keywords: Accretion/deletion; Border-ownership; Figure–ground; Inter-areal connection; Kinetic edge; Motion