2005 Special Issue: Modelling divided visual attention with a winner-take-all network

Authors:
Dominic I. Standage;Thomas P. Trappenberg;Raymond M. Klein
Affiliations:
Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada;Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada;Department of Psychology, Dalhousie University, Halifax, NS, Canada
Venue:
Neural Networks - 2005 Special issue: IJCNN 2005
Year:
2005

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Abstract

Experimental evidence on the distribution of visual attention supports the idea of a spatial saliency map, whereby bottom-up and top-down influences on attention are integrated by a winner-take-all mechanism. We implement this map with a continuous attractor neural network, and test the ability of our model to explain experimental evidence on the distribution of spatial attention. The majority of evidence supports the view that attention is unitary, but recent experiments provide evidence for split attentional foci. We simulate two such experiments. Our results suggest that the ability to divide attention depends on sustained endogenous signals from short term memory to the saliency map, stressing the interplay between working memory mechanisms and attention.