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A feature-integration theory of attention
Feature analysis in early vision: evidence from search asymmetries.
The results of a series of search experiments are interpreted as evidence that focused attention to single items or to groups is required to reduce background activity when the Weber fraction distinguishing the pooled feature activity with displayscontaining a target and with displays containing only distractors is too small to allow reliable discrimination.
Features and Objects: The Fourteenth Bartlett Memorial Lecture
  • A. Treisman
  • Psychology
    The Quarterly journal of experimental psychology…
  • 1 May 1988
(1988). Features and objects: The fourteenth bartlett memorial lecture. The Quarterly Journal of Experimental Psychology Section A: Vol. 40, No. 2, pp. 201-237.
Binding in short-term visual memory.
Working memory capacity is limited both by the independent capacity of simple feature stores and by demands on attention networks that integrate this distributed information into complex but unified thought objects.
Conjunction search revisited.
The results suggest a modification of feature integration theory, in which attention is controlled not only by a unitary "window" but also by a form of feature-based inhibition.
Search asymmetry: a diagnostic for preattentive processing of separable features.
Results are consistent with feature-integration theory, which predicts that a single feature should be detected by the mere presence of activity in the relevant feature map, whereas tasks that require subjects to locate multiple instances of a feature demand focused attention.
The binding problem
  • A. Treisman
  • Psychology, Biology
    Current Opinion in Neurobiology
  • 1 April 1996
Perceptual grouping and attention in visual search for features and for objects.
  • A. Treisman
  • Psychology
    Journal of experimental psychology. Human…
  • 1 April 1982
The effects of perceptual grouping on search for targets defined by separate features or by conjunction of features is explored, suggesting that preattentive grouping creates separate feature maps within each separable dimension rather than one global configuration.