The FeatureGate model of visual selection
The FeatureGate model of visual selection
The model presented here is an attempt to explain the results from a number of different studies in visual attention, including parallel feature searches and serial conjunction searches, variations in search slope with variations in feature contrast and individual subject differences, attentional gradients triggered by cuing, feature-driven spatial selection, split attention, inhibition of distractor locations, and flanking inhibition. The model is implemented in a neural network consisting of a hierarchy of spatial maps. Attentional gates control the flow of information from each level of the hierarchy to the next. The gates are jointly controlled by a Bottom-Up System favoring locations with unique features and a Top-Down System favoring locations with features designated as target features. Because the gating of each location depends on the features present there, the model is called FeatureGate.
182-194
Cave, Kyle R.
38f1020d-3cf6-4165-b462-4d9efd448790
July 1999
Cave, Kyle R.
38f1020d-3cf6-4165-b462-4d9efd448790
Cave, Kyle R.
(1999)
The FeatureGate model of visual selection.
Psychological Research, 62 (2-3), .
(doi:10.1007/s004260050050).
Abstract
The model presented here is an attempt to explain the results from a number of different studies in visual attention, including parallel feature searches and serial conjunction searches, variations in search slope with variations in feature contrast and individual subject differences, attentional gradients triggered by cuing, feature-driven spatial selection, split attention, inhibition of distractor locations, and flanking inhibition. The model is implemented in a neural network consisting of a hierarchy of spatial maps. Attentional gates control the flow of information from each level of the hierarchy to the next. The gates are jointly controlled by a Bottom-Up System favoring locations with unique features and a Top-Down System favoring locations with features designated as target features. Because the gating of each location depends on the features present there, the model is called FeatureGate.
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Published date: July 1999
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Local EPrints ID: 56927
URI: http://eprints.soton.ac.uk/id/eprint/56927
ISSN: 0340-0727
PURE UUID: 33830e04-e8cf-4c06-9433-6d62d6a06674
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Date deposited: 18 Aug 2008
Last modified: 15 Mar 2024 11:04
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Author:
Kyle R. Cave
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