Figure-ground segregation in a recurrent network architecture

P.R. Roelfsema, V.A.F. Lamme, H. Spekreijse, H. Bosch

Research output: Contribution to journalArticleAcademic

177 Citations (Scopus)

Abstract

Proposes a model of how the visual brain segregate textured scenes into figures and background. During texture segregation, locations where the properties of texture elements change abruptly are assigned to boundaries, whereas image regions that are relatively homogeneous are grouped together boundary detection and grouping of image regions require different connection schemes, which are accommodated in single network architecture by implementing them in different layers. As a result, all units carry signals related to boundary detection as well as grouping of image regions, in accordance with cortical physiology. Boundaries yield an early enhancement of network responses, but at a later point, an entire figural region is grouped together, because units that respond to it are labeled with enhanced activity. The model predicts which image regions are preferentially perceived as figure or as background and reproduces the spatio-temporal profile of neuronal activity in the visual cortex during texture segregation in intact animals, as well as in animals with cortical lesions.
Original languageEnglish
Pages (from-to)525-537
Number of pages13
JournalJournal of cognitive neuroscience
Volume14
Issue number4
DOIs
Publication statusPublished - 2002

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