Contextual cuing by global features

Abstract

In visual search tasks, attention can be guided to a target item--appearing amidst distractors--on the basis of simple features (e.g., finding the red letter among green). Chun and Jiang's (1998) contextual cuing effect shows that reaction times (RTs) are also speeded if the spatial configuration of items in a scene is repeated over time. In the present studies, we ask whether global properties of the scene can speed search (e.g., if the display is mostly red, then the target is at location X). In Experiment 1A, the overall background color of the display predicted the target location, and the predictive color could appear 0, 400, or 800 msec in advance of the search array. Mean RTs were faster in predictive than in nonpredictive conditions. However, there was little improvement in search slopes. The global color cue did not improve search efficiency. Experiments 1B-1F replicated this effect using different predictive properties (e.g., background orientation-texture and stimulus color). The results showed a strong RT effect of predictive background, but (at best) only a weak improvement in search efficiency. A strong improvement in efficiency was found, however, when the informative background was presented 1,500 msec prior to the onset of the search stimuli and when observers were given explicit instructions to use the cue (Experiment 2).

Figure 1

Example displays for Experiment 1a.

Figure 2

Mean correct RTs (msec) and search slopes (msec/item) for each SOA over epoch in Experiment 1a.

Figure 3

Example displays, RT differences (msec) and slope differences (msec/item) for Experiment 1b. The RT differences and slope differences both reflect the difference in random (non-predictive) and predictive trials averaged across epochs 5 - 7. Here the background texture/orientation was the predictive feature.

Figure 4

Example displays, RT differences (msec) and slope differences (msec/item) for Experiment 1c. The RT differences and slope differences both reflect the difference in random (non-predictive) and predictive trials averaged across epochs 5 - 7. Here the stimuli and placeholder color was the predictive feature.

Figure 5

Example displays, RT differences (msec) and slope differences (msec/item) for Experiment 1d. The RT differences and slope differences both reflect the difference in random (non-predictive) and predictive trials averaged across epochs 5 - 7. Here the stimuli and placeholder color was the predictive feature. The target in this condition was either a horizontal or vertical line and the distractors were made up of oblique lines orientated at -60, -30, 30 or 60 degrees.

Figure 6

Example displays, RT differences (msec) and slope differences (msec/item) for Experiment 1e. The RT differences and slope differences both reflect the difference in random (non-predictive) and predictive trials averaged across epochs 5 - 7. Here the background color was the predictive feature. The spatial configuration of the display remained constant throughout the experiment.

Figure 7

Example displays, RT differences (msec) and slope differences (msec/item) for Experiment 1f. The RT differences and slope differences both reflect the difference in random (non-predictive) and predictive trials averaged across epochs 5 - 7. Here the background color was the predictive feature. The target in this condition was either a horizontal or vertical line and the distractors were made up of oblique lines orientated at -60, -30, 30 or 60 degrees. The set size on a giving trial was either 18 or 24 items.

Figure 8

Individual search slopes (msec/item) for each participant in Experiment 1f for both predictive and non-predictive (random) trials.

Figure 9

Mean correct RTs (msec) and search slopes (msec/item) over epoch for Experiment 2. Participants were told in advance which background colors were predictive.