Abstract
Attention is automatically guided towards stimuli that match the contents of working memory. This has been studied extensively using simplified computer tasks, but it has never been investigated whether (yet often assumed that) memory-driven guidance also affects real-life search. Here we tested this open question in a naturalistic environment that closely resembles real life. In two experiments, participants wore a mobile eye-tracker, and memorized a color, prior to a search task in which they looked for a target word among book covers on a bookshelf. The memory color was irrelevant to the search task. Nevertheless, we found that participants’ gaze was strongly guided towards book covers that matched the memory color. Crucially, this memory-driven guidance was evident from the very start of the search period. These findings support that attention is guided towards working-memory content in real-world search, and that this is fast and therefore likely reflecting an automatic process.
Significance statement A core concept in the field of visual working memory (VWM) is that visual attention is automatically guided towards things that resemble the content of VWM. For example, if you hold the color red in VWM, your attention and gaze would automatically be drawn towards red things in the environment. So far, studies on such memory-driven guidance have only been done with well-controlled computer tasks that used simplified search displays. Here we address the crucial and open question of whether attention is guided by the content of VWM in a naturalistic environment that closely resembles real life. To do so, we conducted two experiments with mobile eye tracking. Crucially, we found strong memory-driven guidance from the very early phase of the search, reflecting that this is a fast, and therefore likely automatic, process that also driven visual search in real life.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
This research was supported by the Chinese Scholarship Council to Cherie Zhou (Grant number 201807720069).
