The impact of probabilistic feature cueing depends on the level of cue abstraction

Allocation of attentional resources rests on predictions about the likelihood of events. While this effect has been extensively studied in the spatial attention domain where the location of a target stimulus is pre-cued, less is known about the cueing of stimulus features such as the color of a behaviorally relevant target. Moreover, there is disagreement about which types of color cues are effective for biasing attention. Here we investigated the effects of probabilistic context (percentage of cue validity, %CV) for different levels of cue abstraction to elucidate how feature-based search information is processed and used to direct attention. The color of a target was cued by presenting the perceptual color, the color word, or two-letter abbreviations. %CV, i.e., the probability that the cue indicated the color correctly, changed unpredictably between 50, 70, and 90%. Response times (RTs) for valid and invalid trials in each %CV condition were recorded in 60 datasets and analyzed with analyses of variance. The results showed that all cues were associated with comparable RT costs after invalid cueing. The modulation of RT costs by probabilities, however, depended upon level of cue abstraction and time on task: While a strong, immediate impact of %CV was found for two-letter cueing, the effect was solely observed in the second half of the experiment for perceptual and word cues. These results demonstrate that probabilistic feature-based information is processed differently for different levels of cue abstraction. Moreover, the modulatory effect of the environmental statistics differentially depends on the time on task for different feature cues.