Search, similarity, and integration of features between and within dimensions.
Abstract
Three experiments test the claim that conjunction search is difficult only because the target resembles each distractor, whereas the distractors are highly discriminable from each other. The results show that when similarity is controlled, there is an additional difficulty created by the need to conjoin features. In addition, a target with standard values (blue and vertical) is found more easily than targets with nonstandard values (e.g., violet and tilted). Similarity may result in shared components in the functional codes that represent the targets and the distractors. A hypothesis that is based on coarse coding of features values relates the difficulty of feature search with nonstandard targets to problems in coding conjunctions of features within dimensions. Consistent with this account, illusory targets are reported not only in the usual conjunction displays but also in displays containing different features that may share the same underlying components.
Cites (2)
- Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theoryShiffrin, Richard M., Schneider, Walter · 1977 · Psychological Review
- Guided search: An alternative to the feature integration model for visual search.Jeremy M. Wolfe, Kyle R. Cave, Susan L. Franzel · 1989 · Journal of Experimental Psychology Human Perception & Performance
Cited by (11)
- Neuronal Synchrony: A Versatile Code for the Definition of Relations?Singer, Wolf · 1999 · Neuron
- Spatial filtering during visual search: Evidence from human electrophysiology.Luck, Steven J., Hillyard, Steven A. · 1994 · Journal of Experimental Psychology: Human Perception and Performance
- Synchrony UnboundShadlen, Michael N., Movshon, J.Anthony · 1999 · Neuron
- Basal cortisol levels and cognitive deficits in human agingLupien, S, Lecours, AR, Lussier, I, Schwartz, G, Nair, NP, Meaney, MJ · 1994 · The Journal of Neuroscience
- The Temporal Correlation Hypothesis of Visual Feature IntegrationGray, Charles M. · 1999 · Neuron
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Search, similarity, and integration of features between and within dimensions. https://app.cochat.ai/papers/10.1037//0096-1523.17.3.652
- The paper
- Treisman, A. (1991). Search, similarity, and integration of features between and within dimensions. Journal of Experimental Psychology: Human Perception and Performance. https://doi.org/10.1037//0096-1523.17.3.652
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