Abstract
Spatial cueing effects have provided key evidence for understanding visual attention, since performance is enhanced at the cued location while being decreased everywhere else in the field. However, findings that subjects remember the location of an uninformative visual cue despite having no expectation to report it (Chen & Wyble 2015, Vision Research) suggest that subjects automatically build mental representations of the cue, and this automatic encoding may affect subsequent target report in a similar manner as the attentional blink. Our memory encoding cost (MEC) theory explains spatial cueing effects as a combination of attention and memory encoding. Unlike traditional cueing theories, which propose that invalidity costs and validity benefits are both caused by attentional allocation to the cued location, the MEC theory suggests that cueing benefits and costs stem from different sources. The theory predicts that cueing costs and benefits can be dissociated by altering the amount of information that subjects encode about the cue. Across several experiments we show that inducing subjects to encode information about a cue affects target report dramatically. Moreover we find that in typical cueing experiments without cue-report requirements, the invalidity costs are high during the start of an experiment and gradually dwindle over 200 trials, an effect which would be obscured by the standard practice of averaging across all trials. Despite the drop in costs, validity benefits remain stable, suggesting that subjects are not simply ignoring the cue, but rather learn how to use it to trigger attention without also encoding it into memory. This hypothesis was confirmed by a surprise-trial experiment, showing that subjects lost the ability to report the most recent cue's location toward the end of an experiment. This account substantially alters our understanding of visual cueing effects and suggests that visible stimuli can trigger attention without also being stored in memory.
Meeting abstract presented at VSS 2018