Certain aspects of the anatomy and physiology of the cerebral cortex
Parallel distributed processing: explorations in the microstructure of cognition, vol. 2
Preintegration lateral inhibition enhances unsupervised learning
Neural Computation
Journal of Cognitive Neuroscience
Selectivity and Stability via Dendritic Nonlinearity
Neural Computation
The Neural Basis for Visual Selective Attention in Young Infants: A Computational Account
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Masking Disrupts Reentrant Processing in Human Visual Cortex
Journal of Cognitive Neuroscience
A neural model for attentional modulation of lateral interactions in the visual cortex
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
Modeling attention: from computational neuroscience to computer vision
WAPCV'04 Proceedings of the Second international conference on Attention and Performance in Computational Vision
Modeling learned categorical perception in human vision
Neural Networks
A single functional model of drivers and modulators in cortex
Journal of Computational Neuroscience
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Feedback connections are a prominent feature of cortical anatomy and are likely to have a significant functional role in neural information processing. We present a neural network model of cortical feedback that successfully simulates neurophysiological data associated with attention. In this domain, our model can be considered a more detailed, and biologically plausible, implementation of the biased competition model of attention. However, our model is more general as it can also explain a variety of other top-down processes in vision, such as figure/ground segmentation and contextual cueing. This model thus suggests that a common mechanism, involving cortical feedback pathways, is responsible for a range of phenomena and provides a unified account of currently disparate areas of research.