Explicit Attentional Goals Unlock Implicit Spatial Statistical Learning

People can quickly learn spatial distributions of targets and direct attention to likely regions of targets. These implicitly learned spatial biases have been shown to be persistent, transferring to other similar visual search tasks. However, a persistent attentional bias is incompatible with frequently changing goals in our typical daily environment. We propose a flexible goal-specific probability cueing mechanism to address this discrepancy. We examined whether participants could learn and utilize target-specific spatial priority maps across five experiments (each N = 24). In Experiment 1, participants were faster to find the target at the target-specific high-probability location, in line with a goal-specific probability cueing effect. This demonstrated that separate spatial priorities derived from statistical learning can be flexibly activated based on the current goal. In Experiment 2, we ensured the results were not driven solely by intertrial priming. In Experiment 3, we ensured the results were driven by early attentional guidance effects. In Experiment 4, we extended our findings to a complex spatial distribution including four locations, supporting a sophisticated representation of target likelihood in the activated spatial priority maps. Finally, in Experiment 5, we confirmed that the effect was driven by the activation of an attentional template and not associative learning between the target cue and a spatial location. Our findings demonstrate a previously unrecognized mechanism for flexibility within statistical learning. The goal-specific probability cueing effect relies on coordination of feature-based and location-based attention, utilizing information that crosses traditional boundaries between top-down control and selection history.

Automated summary

People can quickly learn and transfer spatial biases in visual search tasks. However, these biases may not be compatible with frequently changing goals. We propose a flexible goal-specific probability cueing mechanism to address this issue.