Abstract

We use attention to select relevant portions of our environment for detailed processing-a process often directed by feature-based goals. Feature-based attention guides visual information processing by strengthening early representations (i.e., within perceptual cortex). Here we examined how feature-based goals affect the way visual information is represented at later stages of processing, namely within visual working memory (VWM). To address this question we used a continuous partial-report VWM task (i.e., a colour-wheel task) and measured the effects of attention on guess rate (the probability that an item is encoded into VWM) and standard deviation (the resolution with which an item is represented). On each trial of Experiment 1, participants remembered the colours of two squares and two circles over a delay, and then reported the colour of one probed stimulus. To manipulate feature-based attention we instructed participants that square stimuli were more likely to be probed (counterbalanced): Across four blocks, squares were probed on 60%, 70%, 80%, or 90% of trials. We found that increasing the value of a feature-based goal increases the probability that a goal-matching item will be encoded into VWM without altering its resolution. This pattern reverses, however, for non-matching stimuli: Attention affects resolution but not guess rate. In Experiment 2, we increased set size from four to six items (three circles and three squares), and observed the same effects of attention. The double dissociation observed in both experiments suggests that feature-based attention can affect both VWM encoding probability and resolution, and, for a given stimulus, these effects can emerge independently. Broadly, our findings add to recent studies investigating how the value of an attentional goal impacts VWM. Interestingly, as attention type (attend to feature vs. space) and stimulus type (report colour vs. location) change, so do the effects on VWM, suggesting a need for more research. Meeting abstract presented at VSS 2015.

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