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The FeatureGate model of visual selection was developed by Kyle Cave asan attempt to explain the results from a number of different studies in visual attention. The model follows a neural network consisting of a hierarchy of spatial maps.
Attentional gates control the flow of information at each level of the hierarchy. They 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.
The model is called FeatureGate because the gating of each location depends on the features present.
The model helps integrate a number of findings related to:
- Visual search: both parallel feature searches and serial conjunction searches; variations in search slope with variations in feature contrast etc
- Individual differences in attention,
- Attentional gradients triggered by cuing,
- feature-driven spatial selection,
- split attention,
- Object-based attention:both the inhibition of distractor locations, and flanking inhibition.
References & BibliographyEdit
- Cave, K.R. (1999). The FeatureGate Model of Visual Selection. Psychological Research, 62, 182-194.
- Kim, M-S., & Cave, K. R. (1999). Top-down and bottom-up attentional control: On the nature of the interference from a salient distractor. Perception & Psychophysics,61, 1009-1023.