title: Binding by temporal structure in multiple feature domains of an oscillatory neuronal network.
abstract: An important step in visual processing is the segregation of objects in a visual scene from one another and from the embedding background. According to current theories of visual neuroscience, the different features of a particular object are represented by cells which are spatially distributed across multiple visual areas in the brain. The segregation of an object therefore requires the unique identification and integration of the pertaining cells which have to be "bound" into one assembly coding for the object in question. Several authors have suggested that such a binding of cells could be achieved by the selective synchronization of temporally structured responses of the neurons activated by features of the same stimulus. This concept has recently gained support by the observation of stimulus-dependent oscillatory activity in the visual system of the cat, pigeon and monkey. Furthermore, experimental evidence has been found for the formation and segregation of synchronously active cell assemblies representing different stimuli in the visual field. In this study, we investigate temporally structured activity in networks with single and multiple feature domains. As a first step, we examine the formation and segregation of cell assemblies by synchronizing and desynchronizing connections within a single feature module. We then demonstrate that distributed assemblies can be appropriately bound in a network comprising three modules selective for stimulus disparity, orientation and colour, respectively. In this context, we address the principal problem of segregating assemblies representing spatially overlapping stimuli in a distributed architecture. Using synchronizing as well as desynchronizing mechanisms, our simulations demonstrate that the binding problem can be solved by temporally correlated responses of cells which are distributed across multiple feature modules.
authors.affiliation: Max-Planck-Institut für Hirnforschung, Frankfurt, Germany.
authors.forename: T B
authors.initials: TB
authors.lastname: Schillen
authors.forename: P
authors.initials: P
authors.lastname: König
mesh_terms: D000818:Animals; D002415:Cats; D010856:Columbidae; D000882:Haplorhini; D008433:Mathematics; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology*; D014796:Visual Perception