Abstract
In hybrid search tasks, observers search the environment for multiple targets stored in memory (e.g., locating ingredients for a recipe in your pantry). Search performance improves linearly with the number of items in the search array but shows a logarithmic relationship with the number of targets in memory (Wolfe, 2012). Memory search is typically conceptualized as “searching through a mental list” (e.g., Wolfe, 2012). Here, we investigated how hybrid search performance is affected by the strength of the memory representations for target items. This is a critical issue because a strong effect of memory strength would provide an alternative view to the search-through-a-list metaphor. In each experiment, participants first memorized two sets of 16 targets and we increased the memory strength for one set by repeating items 8x (Exp. 1) or repeating and asking different questions about the items (e.g., “What is the primary use for this object?”) to encourage deeper processing (Exp. 2). After testing memory in an old/new recognition task, participants searched for the targets (50% present) in search arrays with 8 or 16 objects. Hybrid search performance was measured using inverse efficiency scores (IES = mean correct response time/proportion correct) to account for potential speed/accuracy tradeoffs. Across both experiments (overall N=80), IES scores on target absent trials were lower for the high strength memory condition than the low strength memory condition, indicating better search performance for target sets with stronger memory representations. A separate analysis revealed these effects were largely driven by differences in accuracy rather than response time. Broadly, these data contrast with the idea of a search through lists of items in memory. Instead, they suggest that differences in memory strength — and therefore differences in how accessible items are — can account for memory set size effects in hybrid search.