Ultra-Rapid Scene Categorization with a Wave of Spikes
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Recurrent network with large representational capacity
Neural Computation
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
Shape Saliency Modulates Contextual Processing in the Human Lateral Occipital Complex
Journal of Cognitive Neuroscience
Surrounding Suppression and Facilitation in the Determination of Border Ownership
Journal of Cognitive Neuroscience
Masking Disrupts Reentrant Processing in Human Visual Cortex
Journal of Cognitive Neuroscience
Journal of Cognitive Neuroscience
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
EURASIP Journal on Advances in Signal Processing - Special issue on biologically inspired signal processing: analyses, algorithms and applications
Journal of Cognitive Neuroscience
Figure-ground representation and its decay in primary visual cortex
Journal of Cognitive Neuroscience
A population-based inference framework for feature-based attention in natural scenes
BVAI'05 Proceedings of the First international conference on Brain, Vision, and Artificial Intelligence
Surrounding suppression and facilitation in the determination of border ownership
Journal of Cognitive Neuroscience
The parietal cortex in sensemaking: the dissociation of multiple types of spatial information
Computational Intelligence and Neuroscience - Special issue on Neurocognitive Models of Sense Making
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Here we propose a model of how the visual brain segregates 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 a 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.