The reaction times for this experiment are shown in
Figures 2,
3, and
4, with the percentage accurate data for each condition represented in its corresponding bar. As shown in
Figure 2, this experiment replicated the important features of typical priming of pop-out investigations: Reaction times were 40 ms faster when the target maintained the same shape across consecutive trials,
F(1, 14) = 25.3,
p < .05, and 16 ms faster when the target maintained the same color across consecutive trials—this later difference was marginally significant,
F(1, 14) = 3.2,
p = .097. Also evidenced in this figure, reaction times were 44 ms faster when observers performed the same task across consecutive trials,
F(1, 14) = 14.4,
p < .05, and 320 ms faster when they responded to the color singleton compared to the shape singleton,
F(1, 14) = 127.5,
p < .05.
It is important to note that these advantages for the previous color and shape of the target were modified by the current task that the observers performed.
Figure 3 illustrates the importance of the current task in eliciting priming of pop-out for color (
Figure 3, left),
F(1, 14) = 26.8,
p < .05, and shape (
Figure 3, right),
F(1, 14) = 18.4,
p < .05. Repeating the color of the target benefited performance when the observers performed the color task,
F(1, 14) = 63.5,
p < .05, but not the shape task,
F(1, 14) < 1,
p > .1. Likewise, repeating the shape of the target benefited performance when the observers performed the shape task,
F(1, 14) = 30.2,
p < .05, but not the color task,
F(1, 14) < 1,
p > .1.
This dependence of priming on the current task was not affected by the previous task the observers performed—the same degree of priming was obtained, F values < 1, p values > .1. No other statistical comparisons were significant in this analysis—all F values < 2.3, all p values > .1.
In summary, repeating the features of a target across trials facilitates performance only when this feature is relevant to the current task: Repeating the color of the previous target facilitates performance when the observers perform the color task, and repeating the shape of the previous target benefits performance when the observers perform the shape task. Otherwise, there is no benefit.
Up to now, no consideration has been given as to how the repeated feature of the target was represented on the previous trial: Was the feature unique (a singleton) or not? This is an important question because the uniqueness of an object defines whether or not it is a target, and potentially, only these unique features are primed across trials. Alternatively, perhaps repetition priming is spread among all elements sharing the same feature. If repetition priming is dissipated under these conditions, then it might weaken the benefit. To address these issues, the data were recoded to reveal how the features of the previous color and shape singleton affected performance: The variable color singleton represented whether the color singleton possessed the same color or different colors across trials and the variable shape singleton indicated whether the shape singleton possessed the same shape or different shapes across trials. These consequences of the previous singletons were contrasted to the task the observers performed on the current trial (color or shape task) and the task the observers performed on the previous trial (same as or different than the current task).
The full outcome of this analysis is shown in
Figure 4. As shown in the previous analysis, performance was better when observers performed the color task (
Figure 4, top) compared to the shape task (
Figure 4, bottom; be watchful of the
y-axes) and when the task remained the same compared to when it changed across trials (left vs. right bars in each quadrant). What is most critical is how the color or shape singleton affected performance depending upon its relevance on the previous trial and its relevance on the current trial. The three-way interaction of these factors was significant for both color singletons,
F(1, 14) = 15.7,
p < .05, and shape singletons,
F(1, 14) = 6.6,
p < .05. This interaction originated from three theoretically important effects.
First, the singleton that is irrelevant to the current task does not affect performance. For the color task, repeating or changing the shape singleton did not affect performance alone or as part of an interaction, F values < 1. Similarly, for the shape task, repeating or changing the color singleton did not affect performance alone or as part of an interaction, F values < 1. Simply put, repeating a singleton has no consequence on performance when it is not relevant to the current task—even when it was the target on the previous trial.
A very different pattern was obtained for singletons that were relevant to the current trial. In this case, the consequences of the task-relevant singleton depended on the task the observers performed on the previous trial. This interaction was observed for the color task, F(1, 14) = 29.7, p < . 05, and the shape task, F(1, 14) = 10.0, p < .05. There are two facets of this interaction worth mentioning. First, changing the feature possessed by the task-relevant singleton across trials eliminates the costs involved in switching tasks. That is, for the color task, performance was equivalent when the task changed, provided that the color singleton also changed, F(1, 14) < 1. Similarly, for the shape task, performance was equivalent when the task changed, provided that the shape singleton also changed, F(1, 14) < 1. It is important to note that this same comparison for the task-irrelevant singleton (shape singleton, color task; color singleton, shape task) yielded significant task-switching costs, F values > 4.5, p values < .05. Thus, when the task-relevant singleton changes its feature from one trial to the next, this change appears to reset the system—all consequences of switching tasks are eliminated.
Second, keeping the feature defining the task-relevant singleton the same across trials reveals a pattern of facilitation or inhibition depending on its role in the previous task. When the observers performed the same task across trials, repeating the feature of the relevant singleton facilitated responding. This repetition advantage was significant for the color task, F(1, 14) = 14.6, p < .05, and the shape task, F(1, 14) = 5.5, p < .05. By contrast, when the observers performed a different task on the previous trial, repeating the feature of the now relevant (and previously distracting) singleton inhibited performance. This repetition disadvantage was significant for both the color task, F(1, 14) = 15.1, p < .05, and the shape task, F(1, 14) = 4.6, p = .05.
In summary, the influence of a singleton depends upon whether it is relevant to the current task and its role in the previous task. In general, repeating the features of a singleton has no impact on performance when this singleton is irrelevant to the current task. Although this statement may seem somewhat obvious, consider this—if priming of pop-out is an automatic process facilitating the attended feature on the previous trial and is uninfluenced by intentions of observers, then performance should be slower when the singleton is repeated and the task is changed. This pattern was not obtained.
A fundamentally different pattern is observed when the singleton is relevant to the task. When the feature defining the singleton changes between trials (e.g., red singleton on previous trial and green singleton on current trial), it acts as a “reset” button: All the benefits of performing the same task across trials are eliminated. By contrast, when the feature defining the singleton remains the same, then responding is facilitated when observers perform the same task across trials and responding is inhibited when observers performed a different task on the previous trial.