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Previous studies have shown that humans are sensitive to statistical patterns indicating the likely locations, identities, and timings of visual targets. Here we tested whether participants can also use this kind of information to ameliorate the attentional blink (AB)—a reduction in accuracy for the second of two targets (T1, T2) presented at brief intertarget intervals (lags). In particular, we asked whether participants can use patterns arising from differential distributions of intertarget lags across trials to predict the arrival of T2. We tested this by comparing the ABs in an aging versus a nonaging distribution of trials, where aging refers to the increased likelihood of T2, given that it has not yet occurred, when lags occur with equal frequencies. Experiments 1 and 2 showed that the aging condition yielded greater T2 accuracy at longer lags than did the nonaging condition. In Experiment 3, we used a more sensitive response time measure to show faster T2 discrimination at shorter lags in the nonaging condition. These results demonstrate that participants can predict the likely onset of T2 by using statistical patterns present in the AB task, and that they can use this ability to more effectively direct limited processing resources.

Temporal cues derived from statistical patterns can overcome resource limitations in the attentional blink